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REVIEW 3 major objections 4 minor 164 references

A Survey of Blockchain-Based Privacy Applications: An Analysis of Consent Management and Self-Sovereign Identity Approaches

T0 review · 3 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read A survey of 98 blockchain privacy, consent, and identity papers concludes that privacy is not inherent to blockchain and most proposed solutions rely on external trusted entities, with few public implementations.

desk verdict A useful but overclaiming survey: the joint privacy/consent/SSI synthesis is legitimate, yet the headline code-availability result is not verifiable from the paper's own tables. read the letter →

arxiv 2411.16404 v1 pith:HM6EFOMW submitted 2024-11-25 cs.CR cs.ET

Rodrigo Dutra Garcia , Gowri Ramachandran , Kealan Dunnett , Raja Jurdak , Caetano Ranieri , Bhaskar Krishnamachari , Jo Ueyama This is my paper · ORCID
classification cs.CRcs.ET
keywords blockchainprivacyconsentmanagementself-sovereignidentitydatasharingsurveyGDPRdecentralized
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper is a survey of 98 blockchain-based works on privacy, consent management, and self-sovereign identity, organized around three research questions about privacy mechanisms, identity control, and supporting platforms. It argues that blockchain offers transparency, auditability, and immutability for multi-stakeholder data sharing, but privacy is not built in and must be added through external schemes. Reviewing the corpus by use case, privacy technique, platform, and software availability, the survey concludes that most proposed schemes use cryptographic tools such as encryption and zero-knowledge proofs yet tend to depend on external entities and trusted third parties to protect and process sensitive information, which limits the privacy they can actually provide. It also finds that few works make their code publicly available. The survey positions itself as the first to connect privacy, consent, and identity management together with implementation availability, and it draws a list of open research opportunities from that gap.

What carries the argument

The argument is carried by a classification grid rather than by a single theorem. Each of the 98 selected works is sorted by use case, by the privacy technique it employs, by whether it addresses consent or self-sovereign identity, by the blockchain platform used for prototyping, and by whether its software is available. A second organizing device is the three-layer privacy taxonomy: Layer-0 covers network-level tools, Layer-1 covers on-chain protocol techniques from homomorphic encryption to confidential transactions, and Layer-2 covers off-chain proofs such as zk-SNARKs, zk-STARKs, and Bulletproofs. These two grids generate the survey's conclusions: privacy is always an add-on, and most add-ons route sensitive material through external parties.

What would settle it

A repeatable search that adds backward and forward citation chasing, preprint sources, and direct code checks, and that finds a substantial set of surveyed-period systems offering full privacy, no trusted third parties, and public software, would overturn the paper's conclusion that the field is mostly proposals with limited implementations.

Watch

Extended reading notes

Core claim

The central claim is that blockchain cannot deliver privacy by itself: because transactions and smart-contract inputs are visible to consensus nodes, any privacy guarantee must come from mechanisms layered around the ledger. Analyzing 40 privacy works, 33 consent works, and 25 self-sovereign identity works, the survey finds that the dominant privacy techniques are data encryption, homomorphic encryption, access control, and zk-SNARK-related proofs, organized by network-layer, on-chain, and off-chain strategies. Its cross-cutting finding is that these schemes tend to rely on external entities and trusted third parties to protect and process sensitive information, and that most do not provide software, so the literature is rich in proposals but thin in deployable, trust-minimized implementations. The paper further claims that earlier surveys treat privacy, consent, or identity separately and that no existing study combines these dimensions with an analysis of open-source availability.

Load-bearing premise

The survey's conclusions depend on the corpus being complete and accurately summarized, yet the search covered only titles in three bibliographic databases, without citation chasing, grey literature, or independent verification of the 98 summaries.

Editorial extensions

If this is right

  • Applications that need both GDPR-style consent and blockchain auditability must combine on-chain access-control records with off-chain encrypted storage; neither blockchain alone nor off-chain storage alone suffices.
  • Practitioners should treat a system's privacy claim as limited whenever a trusted third party or external entity can see or process the sensitive data.
  • Researchers evaluating these schemes should measure not only security properties but also whether working code exists, since the survey finds most works lack software availability.
  • Privacy-focused platforms such as the ones surveyed often trade away smart-contract support or introduce trusted setups, so choosing a platform means accepting one of these limitations.
  • Open problems identified include on-chain encryption performance, post-quantum NTRU schemes, differential privacy versus encryption, cross-chain transactions, confidential assets, and decentralized identity interoperability.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A consequence the authors leave implicit is that the field's bottleneck is deployment, not cryptographic invention: with most schemes never shipped, the next useful step is reference implementations and benchmarks rather than new schemes.
  • The survey's finding about trusted third parties suggests a testable taxonomy: rank the 98 works by the number and role of external trust assumptions and see whether privacy guarantees weaken as trust assumptions grow.
  • The layer table hints at a possible design rule: Layer-2 zero-knowledge proofs can give transactional privacy without trusted setups, so combining them with self-sovereign identity-based consent could yield fully trust-minimized systems; that combination is not yet evaluated in the surveyed corpus.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. This manuscript is a survey of blockchain-based privacy applications, with a stated focus on consent management and self-sovereign identity (SSI). The authors describe a title-based literature search across Google Scholar, Scopus, and ACM Digital Library that yields 98 works, and they organize the reviewed works into three areas: privacy-preserving data sharing, consent management, and SSI. They also review privacy-focused blockchain protocols and identity management platforms, and conclude with open challenges. The paper's central claims are that privacy must be supplied as an external layer on top of blockchain, that few proposed solutions provide publicly available implementations, and that many schemes rely on external entities and trusted third parties, limiting privacy. The contributions are primarily classificatory and expository: there are no formal derivations or empirical measurements to evaluate.

Significance. If the corpus is complete and the classifications are accurate, the survey is a useful reference for researchers entering the area: it provides a structured comparison of 98 works, an explicit search methodology, and a publicly listed dataset on GitHub [41]. The paper also makes a falsifiable practical claim, namely that most surveyed proposals lack accessible implementations, which is a valuable observation if it is supported by the data. At the same time, the survey's value depends entirely on the correctness and completeness of its literature corpus and on the accuracy of the summary tables, since there are no formal results to verify. The absence of machine-checked proofs, quantitative evaluations, or systematic quality appraisal means the contribution is an organizing and synthesizing one rather than a technical one.

major comments (3)
  1. [Section 5.2, Tables 2 and 3; Section 5.3, Tables 5 and 6] The central availability claim is not verifiable from the manuscript's own tables. The text in Section 5.2 states, "As presented in Tables 2 and 3 ... few solutions provide the code on GitHub, while most do not provide any software availability information," and the table captions promise a code/software availability column. However, Tables 2 and 3 contain only Work, Publication Year, Use Case, and Privacy Technique columns; Tables 5 and 6 contain only Work, Publication Year, Use Case, and Key Contribution columns. The claimed software availability information appears only in a small number of footnotes and in the external GitHub dataset [41]. As a result, the quantitative basis for the conclusion that "few solutions provide the code on GitHub" cannot be independently checked from the paper. The authors should either add the promised availability columns to the tables, or present an explicit count of available/unavailable implementations in the text with a precise definition of what counts as "available" (e.g., linked public repository versus code mentioned in the paper body), and clearly state which of the 98 sources were assessed and how.
  2. [Section 9, Conclusion; Section 5.2] The conclusion that surveyed schemes "tend to rely on external entities and trusted third parties to protect and process sensitive information, limiting privacy" is not operationalized or directly supported by the presented tables. The tables classify privacy techniques but do not include a column or coding for trust assumptions, such as whether a scheme requires a centralized proxy re-encryption server, a trusted authority for key management, or an off-chain storage provider. Without a definition of what counts as reliance on a trusted third party, and without a per-work classification, this statement is an impression rather than a survey result. The authors should either add a trust-assumption dimension to the classification or revise the conclusion to state this as an interpretive observation with the specific supporting examples from the surveyed works.
  3. [Section 4, Survey Methodology] The completeness claims of the survey are stronger than the search methodology justifies. The selection procedure uses only title-field keyword searches in three databases, with no backward or forward citation chasing, no grey literature or preprint coverage, and no independent verification of the 98 retrieved summaries. Given this, the claim in Section 2 that "no existing study connects these aspects" is too strong: it is a claim about the entire literature, not just about the title-matched corpus. The authors should soften this claim to "no study found by our search connects these aspects" and add an explicit limitations paragraph discussing recall risk, including the fact that relevant work with different title wording would be missed.
minor comments (4)
  1. [Section 4, search string listing] The search-string numbering is inconsistent: the privacy strings are labeled S01, S02, and S03, and then the consent strings reuse S03, followed by S04 and S05, while the identity strings jump to S07, S08, and S09, skipping S06. This should be renumbered for clarity.
  2. [Section 1, last paragraph of the introduction] The sentence "Sections 6, 7. Section 8 identifies the opportunities..." is grammatically incomplete; it should read something like "Section 6 reviews privacy-focused blockchain platforms, Section 7 reviews identity management platforms, and Section 8 identifies opportunities for further research."
  3. [References, entry [49]] The first author of reference [49] is listed only as "Raghav" without a surname; this should be corrected to the full author name as it appears in the source publication.
  4. [Table 4] The table lists both "Anonymization" and "K-anonymity" as separate techniques, and also lists "Hash Anonymous Identity" separately; since several works use multiple techniques, the table would be clearer if the relationship between these categories and the individual works' primary classification were explained in a note.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the survey's classifications and conclusions are literature syntheses, not derivations from fitted inputs or self-citations.

full rationale

This is a survey paper with no fitted parameters, no predictive model, and no equations whose outputs could reduce to inputs. The central classificatory claims (privacy techniques, consent mechanisms, SSI approaches) are read off the 98 summarized primary sources; the gap claim that 'no existing study connects these aspects' is a literature assessment, not a derivation. The only self-citation is reference [10], used as an example of encryption-based privacy enhancement in the introduction; nothing in the survey's taxonomies, tables, or research opportunities depends on that paper's results. The statement that 'few solutions provide the code on GitHub' rests on the authors' external GitHub dataset [41] rather than on the printed tables; even if the tables omit the promised availability column, that is a verifiability/reproducibility weakness, not circular reasoning, because the conclusion is not true by definition and is not derived from a quantity fitted in this paper. No load-bearing self-citation chain, ansatz-smuggled-in-via-citation, uniqueness-imported-from-authors, or renamed-known-result pattern was found.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

No free parameters or invented entities are introduced because the paper is a literature survey. Its contribution rests on two domain assumptions: the selected corpus is representative, and the authors' summaries of 98 external papers are accurate.

assumptions (2)
  • domain assumption The 98 works returned by the title-based search strings are representative of the blockchain privacy, consent, and self-sovereign identity literature.
    Section 4 limits searches to title fields in Google Scholar, Scopus, and ACM Digital Library, with no citation chasing, grey literature, or quality appraisal; the survey's classifications and gap analysis depend on this corpus being representative.
  • domain assumption The per-paper summaries in Tables 2 through 8 accurately reflect the technical content of each cited work.
    The survey does not provide independent verification or per-paper evidence for its 98 summaries; accuracy depends on the authors' reading of the cited papers.

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Cite this review

Pith. "Pith review of A Survey of Blockchain-Based Privacy Applications: An Analysis of Consent Management and Self-Sovereign Identity Approaches." pith.science (2026). https://pith.science/paper/HM6EFOMW

@misc{pith2026241116404,
  author       = {Pith},
  title        = {Pith review of: A Survey of Blockchain-Based Privacy Applications: An Analysis of Consent Management and Self-Sovereign Identity Approaches},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HM6EFOMW}},
  note         = {Machine review of arXiv:2411.16404}
}
read the original abstract

Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence (AI) and machine learning algorithms to automate business processes. The proliferation of modern AI technologies increases the data demand. However, real-world networks often include private and sensitive information of businesses, users, and other organizations. Emerging data-protection regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) introduce policies around collecting, storing, and managing digital data. While Blockchain technology offers transparency, auditability, and immutability for multi-stakeholder applications, it lacks inherent support for privacy. Typically, privacy support is added to a blockchain-based application by incorporating cryptographic schemes, consent mechanisms, and self-sovereign identity. This article surveys the literature on blockchain-based privacy-preserving systems and identifies the tools for protecting privacy. Besides, consent mechanisms and identity management in the context of blockchain-based systems are also analyzed. The article concludes by highlighting the list of open challenges and further research opportunities.

Figures

Figures reproduced from arXiv: 2411.16404 by the authors.

Figure 1
Figure 1. A timeline of some significant events in the context of blockchain, decentralized identity, and privacy regulations from 2008 [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Blockchain data structure: blocks connected in chronological order in an append-only manner using a cryptographic hash [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. The flow of consent requests, user control, and selective sharing [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: a) Centralized Identity Management and b) Federated Identity Management (FIM) models [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: The actors and roles in decentralized identity management [PITH_FULL_IMAGE:figures/full_fig_p011_5.png]
Figure 6
Figure 6. Figure 6: Relevant publications aligned with the objectives of this survey obtained from Google Scholar, Scopus, and ACM Digital [PITH_FULL_IMAGE:figures/full_fig_p012_6.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

164 extracted references · 61 canonical work pages

  1. [10]

    Blockchain-aided and privacy-preserving data governance in multi-stakeholder applications,

    R. D. Garcia, G. S. Ramachandran, R. Jurdak, and J. Ueyama, “Blockchain-aided and privacy-preserving data governance in multi-stakeholder applications, ”IEEE Transactions on Network and Service Management , vol. 19, no. 4, pp. 3781–3793, 2022

    2022

  2. [41]

    G. et al. Privacy and consent survey dataset. (accessed: 11-26-2023). [Online]. Available: https://github.com/rodrigodg1/privacy-survey

    2023

  3. [1]

    Chapter 6 - the growing role of internet of things in healthcare wearables,

    R. Indrakumari, T. Poongodi, P. Suresh, and B. Balamurugan, “Chapter 6 - the growing role of internet of things in healthcare wearables, ” in Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach , V. E. Balas, V. K. Solanki, and R. Kumar, Eds. Academic Press, 2020, pp. 163–194. [Online]. Available: https://www.sciencedirect.com/science...

    2020

  4. [2]

    Edge-computing-driven internet of things: A survey,

    L. Kong, J. Tan, J. Huang, G. Chen, S. Wang, X. Jin, P. Zeng, M. Khan, and S. K. Das, “Edge-computing-driven internet of things: A survey, ”ACM Comput. Surv., vol. 55, no. 8, dec 2022. [Online]. Available: https://doi.org/10.1145/3555308

    work page doi:10.1145/3555308 2022

  5. [3]

    A digital platform for remote healthcare monitoring,

    S. Enshaeifar, P. Barnaghi, S. Skillman, D. Sharp, R. Nilforooshan, and H. Rostill, “A digital platform for remote healthcare monitoring, ” inCompanion Proceedings of the Web Conference 2020 , 2020, pp. 203–206

    2020

  6. [4]

    Recovery cost of optus hack will be huge,

    O. Analytica, “Recovery cost of optus hack will be huge, ” Emerald Expert Briefings, no. oxan-es, 2022

    2022

  7. [5]

    Blockchain for healthcare management systems: A survey on interoperability and security,

    E. R. D. Villarreal, J. García-Alonso, E. Moguel, and J. A. H. Alegría, “Blockchain for healthcare management systems: A survey on interoperability and security, ”IEEE Access, vol. 11, pp. 5629–5652, 2023

    2023

  8. [6]

    A systematic review of blockchain for consent management,

    P. V. Kakarlapudi and Q. H. Mahmoud, “A systematic review of blockchain for consent management, ”Healthcare, vol. 9, no. 2, p. 137, 2021. [Online]. Available: https://doi.org/10.3390/healthcare9020137

    work page doi:10.3390/healthcare9020137 2021

Show all 164 references
  1. [7]

    Towards the classification of self-sovereign identity properties,

    S. Cucko, S. Becirovic, A. Kamisalic, S. Mrdovic, and M. Turkanovic, “Towards the classification of self-sovereign identity properties, ”IEEE Access, vol. 10, p. 88306–88329, 2022. [Online]. Available: http://dx.doi.org/10.1109/ACCESS.2022.3199414

    2022

  2. [8]

    Exploring the use of self-sovereign identity for event ticketing systems,

    S. Feulner, J. Sedlmeir, V. Schlatt, and N. Urbach, “Exploring the use of self-sovereign identity for event ticketing systems, ”Electronic Markets, vol. 32, no. 3, pp. 1759–1777, Jul. 2022. [Online]. Available: https://doi.org/10.1007/s12525-022-00573-9

    2022 doi

  3. [9]

    Bashir, Mastering blockchain

    I. Bashir, Mastering blockchain. Packt Publishing Ltd, 2017

    2017

  4. [11]

    Privacy protection for blockchain-based healthcare iot systems: A survey,

    M. Qi, Z. Wang, Q.-L. Han, J. Zhang, S. Chen, and Y. Xiang, “Privacy protection for blockchain-based healthcare iot systems: A survey, ”IEEE/CAA Journal of Automatica Sinica, pp. 1–20, 2022

    2022

  5. [12]

    A survey on privacy protection in blockchain system,

    Q. Feng, D. He, S. Zeadally, M. K. Khan, and N. Kumar, “A survey on privacy protection in blockchain system, ”Journal of Network and Computer Applications, vol. 126, pp. 45–58, 2019

    2019

  6. [13]

    Privacy-preserving solutions for blockchain: Review and challenges,

    J. Bernal Bernabe, J. L. Canovas, J. L. Hernandez-Ramos, R. Torres Moreno, and A. Skarmeta, “Privacy-preserving solutions for blockchain: Review and challenges, ”IEEE Access, vol. 7, pp. 164 908–164 940, 2019

    2019

  7. [14]

    Blockchain technology: A survey on applications and security privacy Challenges,

    B. K. Mohanta, D. Jena, S. S. Panda, and S. Sobhanayak, “Blockchain technology: A survey on applications and security privacy Challenges, ”Internet of Things, vol. 8, p. 100107, 2019

    2019

  8. [15]

    Privacy preservation in permissionless blockchain: A survey,

    L. Peng, W. Feng, Z. Yan, Y. Li, X. Zhou, and S. Shimizu, “Privacy preservation in permissionless blockchain: A survey, ”Digital Communications and Networks, vol. 7, no. 3, pp. 295–307, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2352864819303827

    2021

  9. [16]

    Applications of blockchain in ensuring the security and privacy of electronic health record systems: A survey,

    S. Shi, D. He, L. Li, N. Kumar, M. K. Khan, and K.-K. R. Choo, “Applications of blockchain in ensuring the security and privacy of electronic health record systems: A survey, ”Computers & Security, vol. 97, pp. 101 966–101 966, 2020. Manuscript submitted to ACM A Survey of Blo...

    2020

  10. [17]

    Untangling blockchain technology: A survey on state of the art, security threats, privacy services, applications and future research directions,

    B. Bhushan, P. Sinha, K. M. Sagayam, and A. J, “Untangling blockchain technology: A survey on state of the art, security threats, privacy services, applications and future research directions, ”Computers & Electrical Engineering , vol. 90, p. 106897, 2021

    2021

  11. [18]

    Decentralized and self-sovereign identity in the era of blockchain: A survey,

    Y. Bai, H. Lei, S. Li, H. Gao, J. Li, and L. Li, “Decentralized and self-sovereign identity in the era of blockchain: A survey, ” in2022 IEEE International Conference on Blockchain (Blockchain) , 2022, pp. 500–507

    2022

  12. [19]

    Blockchain-based self-sovereign identity: Survey, requirements, use-cases, and comparative study,

    R. Nokhbeh Zaeem, K. C. Chang, T.-C. Huang, D. Liau, W. Song, A. Tyagi, M. Khalil, M. Lamison, S. Pandey, and K. S. Barber, “Blockchain-based self-sovereign identity: Survey, requirements, use-cases, and comparative study, ” inIEEE/WIC/ACM International Conference on Web Intel...

    2022

  13. [20]

    Blockchain-based identity management system and self-sovereign identity ecosystem: A comprehensive survey,

    M. R. Ahmed, A. K. M. M. Islam, S. Shatabda, and S. Islam, “Blockchain-based identity management system and self-sovereign identity ecosystem: A comprehensive survey, ”IEEE Access, vol. 10, pp. 113 436–113 481, 2022

    2022

  14. [21]

    A survey on blockchain systems: Attacks, defenses, and privacy preservation,

    Y. Chen, H. Chen, Y. Zhang, M. Han, M. Siddula, and Z. Cai, “A survey on blockchain systems: Attacks, defenses, and privacy preservation, ” High-Confidence Computing, vol. 2, no. 2, p. 100048, 2022

    2022

  15. [22]

    Bitcoin: A peer-to-peer electronic cash system,

    S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system, ” Dec 2008, accessed: 11-26-2023. [Online]. Available: https://bitcoin.org/bitcoin.pdf

    2008

  16. [23]

    Achieving cybersecurity in blockchain-based systems: A survey,

    M. Gimenez-Aguilar, J. M. de Fuentes, L. Gonzalez-Manzano, and D. Arroyo, “Achieving cybersecurity in blockchain-based systems: A survey, ”Future Generation Computer Systems, vol. 124, pp. 91–118, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S01...

    2021

  17. [24]

    Potential requirements and opportunities of blockchain-based industrial iot in supply chain: A survey,

    Z.-H. Sun, Z. Chen, S. Cao, and X. Ming, “Potential requirements and opportunities of blockchain-based industrial iot in supply chain: A survey, ” IEEE Transactions on Computational Social Systems , vol. 9, no. 5, pp. 1469–1483, 2022

    2022

  18. [25]

    Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey,

    D. Li, D. Han, T.-H. Weng, Z. Zheng, H. Li, H. Liu, A. Castiglione, and K.-C. Li, “Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey, ” Soft Computing , vol. 26, no. 9, pp. 4423–4440, nov 2021. [Online]. Available: https://...

    2021

  19. [26]

    A survey and taxonomy of consensus protocols for blockchains,

    A. Singh, G. Kumar, R. Saha, M. Conti, M. Alazab, and R. Thomas, “A survey and taxonomy of consensus protocols for blockchains, ”Journal of Systems Architecture, vol. 127, p. 102503, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1383762122000777

    2022

  20. [27]

    Reid and M

    F. Reid and M. Harrigan, An Analysis of Anonymity in the Bitcoin System . New York, NY: Springer New York, 2013, pp. 197–223. [Online]. Available: https://doi.org/10.1007/978-1-4614-4139-7_10

    2013 doi

  21. [28]

    Formalizing and securing relationships on public networks,

    N. Szabo, “Formalizing and securing relationships on public networks, ” First monday, 1997

    1997

  22. [29]

    A survey of smart contract formal specification and verification,

    P. Tolmach, Y. Li, S.-W. Lin, Y. Liu, and Z. Li, “A survey of smart contract formal specification and verification, ”ACM Comput. Surv., vol. 54, no. 7, jul 2021. [Online]. Available: https://doi.org/10.1145/3464421

    2021 doi

  23. [30]

    A survey of application research based on blockchain smart contract,

    S.-Y. Lin, L. Zhang, J. Li, L.-l. Ji, and Y. Sun, “A survey of application research based on blockchain smart contract, ”Wireless Networks, vol. 28, no. 2, pp. 635–690, 2022

    2022

  24. [31]

    Differential privacy for industrial internet of things: Opportunities, applications, and challenges,

    B. Jiang, J. Li, G. Yue, and H. Song, “Differential privacy for industrial internet of things: Opportunities, applications, and challenges, ”IEEE Internet of Things Journal, vol. 8, no. 13, pp. 10 430–10 451, 2021

    2021

  25. [32]

    A survey of security and privacy issues in the internet of things from the layered context,

    S. Deep, X. Zheng, A. Jolfaei, D. Yu, P. Ostovari, and A. Kashif Bashir, “A survey of security and privacy issues in the internet of things from the layered context, ” Transactions on Emerging Telecommunications Technologies , vol. 33, no. 6, p. e3935, 2022. [Online]. Availabl...

    2022 doi

  26. [33]

    A survey on anonymity and privacy in bitcoin-like digital cash systems,

    M. C. Kus Khalilov and A. Levi, “A survey on anonymity and privacy in bitcoin-like digital cash systems, ”IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2543–2585, 2018

    2018

  27. [34]

    Sok: How private is bitcoin? classification and evaluation of bitcoin privacy techniques,

    S. Ghesmati, W. Fdhila, and E. Weippl, “Sok: How private is bitcoin? classification and evaluation of bitcoin privacy techniques, ” inProceedings of the 17th International Conference on A vailability, Reliability and Security , ser. ARES ’22. New York, NY, USA: Association for...

    2022

  28. [35]

    Device identification in blockchain-based internet of things,

    A. Dorri, C. Roulin, S. Pal, S. Baalbaki, R. Jurdak, and S. S. Kanhere, “Device identification in blockchain-based internet of things, ”IEEE Internet of Things Journal, vol. 9, no. 24, pp. 24 767–24 776, 2022

    2022

  29. [36]

    Complete guide to gdpr compliance

    GDPR. Complete guide to gdpr compliance. (accessed: 11-26-2023). [Online]. Available: https://gdpr.eu/

    2023

  30. [37]

    California consumer privacy act

    CCPA. California consumer privacy act. (accessed: 11-26-2023). [Online]. Available: https://oag.ca.gov/privacy/ccpa

    2023

  31. [38]

    Compliance with HIPAA and GDPR in blockchain-based electronic health record,

    M. Shuaib, S. Alam, M. S. Alam, and M. S. Nasir, “Compliance with HIPAA and GDPR in blockchain-based electronic health record, ”Materials Today: Proceedings, Mar. 2021. [Online]. Available: https://doi.org/10.1016/j.matpr.2021.03.059

    2021 doi

  32. [39]

    General personal data protection act (lgpd)

    ECOMPLY. General personal data protection act (lgpd). (accessed: 12-22-2022). [Online]. Available: https://lgpd-brazil.info/

    2022

  33. [40]

    Ensuring privacy in the application of the brazilian general data protection law (lgpd),

    E. T. V. de Castro, G. R. S. Silva, and E. D. Canedo, “Ensuring privacy in the application of the brazilian general data protection law (lgpd), ” in Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing , ser. SAC ’22. New York, NY, USA: Association for Computing M...

    2022

  34. [42]

    Decentralizing Privacy: Using Blockchain to Protect Personal Data,

    G. Zyskind, O. Nathan, and A. Pentland, “Decentralizing Privacy: Using Blockchain to Protect Personal Data, ” 2015 IEEE Security and Privacy Workshops, pp. 180–184, 2015

    2015

  35. [43]

    Permissioned blockchain-based secure and privacy-preserving data sharing protocol,

    Z. Wang, Q. Chen, and L. Liu, “Permissioned blockchain-based secure and privacy-preserving data sharing protocol, ” IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10 698–10 707, Jun. 2023. [Online]. Available: https://doi.org/10.1109/jiot.2023.3242959

    2023

  36. [44]

    PDPChain: A consortium blockchain-based privacy protection scheme for personal data,

    W. Liang, Y. Yang, C. Yang, Y. Hu, S. Xie, K.-C. Li, and J. Cao, “PDPChain: A consortium blockchain-based privacy protection scheme for personal data, ”IEEE Transactions on Reliability , vol. 72, no. 2, pp. 586–598, Jun. 2023. [Online]. Available: https://doi.org/10.1109/tr.20...

    2023

  37. [45]

    Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control,

    X. Yue, H. Wang, D. Jin, M. Li, and W. Jiang, “Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control, ”Journal of Medical Systems , vol. 40, no. 10, p. 218, 2016

    2016

  38. [46]

    MediBchain: A Blockchain Based Privacy Preserving Platform for Healthcare Data,

    A. A. Omar, M. S. Rahman, A. Basu, and S. Kiyomoto, “MediBchain: A Blockchain Based Privacy Preserving Platform for Healthcare Data, ”Lecture Notes in Computer Science , pp. 534–543, 2017

    2017

  39. [47]

    A Blockchain-Based Medical Data Sharing Mechanism with Attribute-Based Access Control and Privacy Protection,

    Y. Chen, L. Meng, H. Zhou, and G. Xue, “A Blockchain-Based Medical Data Sharing Mechanism with Attribute-Based Access Control and Privacy Protection, ”Wireless Communications and Mobile Computing , vol. 2021, pp. 1–12, 2021

    2021

  40. [48]

    Designated-verifier aggregate signature scheme with sensitive data privacy protection for permissioned blockchain-assisted IIoT,

    T. Li, H. Wang, D. He, and J. Yu, “Designated-verifier aggregate signature scheme with sensitive data privacy protection for permissioned blockchain-assisted IIoT, ” IEEE Transactions on Information Forensics and Security , vol. 18, pp. 4640–4651, 2023. [Online]. Available: ht...

    2023

  41. [49]

    Privacy-preserving cloud data sharing for healthcare systems with hybrid blockchain,

    Raghav, N. Andola, S. Venkatesan, and S. Verma, “Privacy-preserving cloud data sharing for healthcare systems with hybrid blockchain, ” Peer-to-Peer Networking and Applications, vol. 16, no. 5, pp. 2525–2547, Aug. 2023. [Online]. Available: https://doi.org/10.1007/s12083-023-01521-w

    2023 doi

  42. [50]

    Blockchain-aided privacy-preserving medical data sharing scheme for e-healthcare system,

    J. Liu, Y. Fan, R. Sun, L. Liu, C. Wu, and S. Mumtaz, “Blockchain-aided privacy-preserving medical data sharing scheme for e-healthcare system, ” IEEE Internet of Things Journal , pp. 1–1, 2023. [Online]. Available: https://doi.org/10.1109/jiot.2023.3287636

    2023

  43. [51]

    Towards Secure and Privacy-Preserving Data Sharing in e-Health Systems via Consortium Blockchain,

    A. Zhang and X. Lin, “Towards Secure and Privacy-Preserving Data Sharing in e-Health Systems via Consortium Blockchain, ”Journal of Medical Systems, vol. 42, no. 8, p. 140, 2018

    2018

  44. [52]

    Towards Secure and Privacy-Preserving Data Sharing for COVID-19 Medical Records: A Blockchain-Empowered Approach,

    L. Tan, K. Yu, N. Shi, C. Yang, W. Wei, and H. Lu, “Towards Secure and Privacy-Preserving Data Sharing for COVID-19 Medical Records: A Blockchain-Empowered Approach, ”IEEE Transactions on Network Science and Engineering , vol. 9, no. 1, pp. 271–281, 2020

    2020

  45. [53]

    Bpds: A blockchain based privacy-preserving data sharing for electronic medical records,

    J. Liu, X. Li, L. Ye, H. Zhang, X. Du, and M. Guizani, “Bpds: A blockchain based privacy-preserving data sharing for electronic medical records, ” in 2018 IEEE Global Communications Conference (GLOBECOM) . IEEE, 2018, pp. 1–6

    2018

  46. [54]

    hOCBS: A privacy-preserving blockchain framework for healthcare data leveraging an on-chain and off-chain system design,

    K. Miyachi and T. K. Mackey, “hOCBS: A privacy-preserving blockchain framework for healthcare data leveraging an on-chain and off-chain system design, ”Information Processing & Management , vol. 58, no. 3, p. 102535, 2021

    2021

  47. [55]

    Cp-bdhca: Blockchain-based confidentiality-privacy preserving big data scheme for healthcare clouds and applications,

    H. Ghayvat, S. Pandya, P. Bhattacharya, M. Zuhair, M. Rashid, S. Hakak, and K. Dev, “Cp-bdhca: Blockchain-based confidentiality-privacy preserving big data scheme for healthcare clouds and applications, ”IEEE Journal of Biomedical and Health Informatics , vol. 26, no. 5, pp. 1...

    1937

  48. [56]

    SPChain: Blockchain-based medical data sharing and privacy-preserving eHealth system,

    R. Zou, X. Lv, and J. Zhao, “SPChain: Blockchain-based medical data sharing and privacy-preserving eHealth system, ”Information Processing & Management, vol. 58, no. 4, p. 102604, 2021

    2021

  49. [57]

    A blockchain-based preserving and sharing system for medical data privacy,

    Z. Chen, W. Xu, B. Wang, and H. Yu, “A blockchain-based preserving and sharing system for medical data privacy, ”Future Generation Computer Systems, vol. 124, pp. 338–350, 2021

    2021

  50. [58]

    MedShare: A Privacy-Preserving Medical Data Sharing System by Using Blockchain,

    M. Wang, Y. Guo, C. Zhang, C. Wang, H. Huang, and X. Jia, “MedShare: A Privacy-Preserving Medical Data Sharing System by Using Blockchain, ” IEEE Transactions on Services Computing , vol. PP, no. 99, pp. 1–1, 2021

    2021

  51. [59]

    Scalable blockchain model using off-chain ipfs storage for healthcare data security and privacy,

    J. Jayabalan and N. Jeyanthi, “Scalable blockchain model using off-chain ipfs storage for healthcare data security and privacy, ”Journal of Parallel and Distributed Computing, vol. 164, pp. 152–167, 2022

    2022

  52. [60]

    A comprehensive survey on blockchain in industrial internet of things: Motivations, research progresses, and future challenges,

    R. Huo, S. Zeng, Z. Wang, J. Shang, W. Chen, T. Huang, S. Wang, F. R. Yu, and Y. Liu, “A comprehensive survey on blockchain in industrial internet of things: Motivations, research progresses, and future challenges, ”IEEE Communications Surveys & Tutorials , vol. 24, no. 1, pp....

    2022

  53. [61]

    Data Privacy Based on IoT Device Behavior Control Using Blockchain,

    F. Loukil, C. Ghedira-Guegan, K. Boukadi, A.-N. Benharkat, and E. Benkhelifa, “Data Privacy Based on IoT Device Behavior Control Using Blockchain, ”ACM Transactions on Internet Technology (TOIT) , vol. 21, no. 1, pp. 1–20, 2021

    2021

  54. [62]

    PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities,

    I. Makhdoom, I. Zhou, M. Abolhasan, J. Lipman, and W. Ni, “PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities, ”Computers & Security, vol. 88, p. 101653, 2020

    2020

  55. [63]

    Galaxy: A scalable BFT and privacy-preserving pub/sub IoT data sharing framework based on blockchain,

    Y. Zhang, X. Wang, X. He, N. Zhang, Z. Zheng, and K. Xu, “Galaxy: A scalable BFT and privacy-preserving pub/sub IoT data sharing framework based on blockchain, ”IEEE Internet of Things Journal , pp. 1–1, 2023. [Online]. Available: https://doi.org/10.1109/jiot.2023.3307073

    2023

  56. [64]

    A data privacy protection scheme for Internet of things based on blockchain,

    J. Gong, Y. Mei, F. Xiang, H. Hong, Y. Sun, and Z. Sun, “A data privacy protection scheme for Internet of things based on blockchain, ”Transactions on Emerging Telecommunications Technologies, vol. 32, no. 5, 2021

    2021

  57. [65]

    Privacy protection for fog computing and the internet of things data based on blockchain,

    Y. Liu, J. Zhang, and J. Zhan, “Privacy protection for fog computing and the internet of things data based on blockchain, ”Cluster Computing, vol. 24, no. 2, pp. 1331–1345, 2021

    2021

  58. [66]

    Blockchain-based privacy-preserving and rewarding private data sharing for iot,

    T. Li, H. Wang, D. He, and J. Yu, “Blockchain-based privacy-preserving and rewarding private data sharing for iot, ”IEEE Internet of Things Journal , 2022

    2022

  59. [67]

    Privacy-Preserving IoT Data Aggregation Based on Blockchain and Homomorphic Encryption,

    F. Loukil, C. Ghedira-Guegan, K. Boukadi, and A.-N. Benharkat, “Privacy-Preserving IoT Data Aggregation Based on Blockchain and Homomorphic Encryption, ”Sensors, vol. 21, no. 7, p. 2452, 2021

    2021

  60. [68]

    PD2s: A privacy-preserving differentiated data sharing scheme based on blockchain and federated learning,

    Y. Liu, P. Liu, W. Jing, and H. H. Song, “PD2s: A privacy-preserving differentiated data sharing scheme based on blockchain and federated learning, ” IEEE Internet of Things Journal , pp. 1–1, 2023. [Online]. Available: https://doi.org/10.1109/jiot.2023.3295763

    2023

  61. [69]

    DS2pm: A data-sharing privacy protection model based on blockchain and federated learning,

    Y. Chen, J. Li, F. Wang, K. Yue, Y. Li, B. Xing, L. Zhang, and L. Chen, “DS2pm: A data-sharing privacy protection model based on blockchain and federated learning, ” IEEE Internet of Things Journal , vol. 10, no. 14, pp. 12 112–12 125, Jul. 2023. [Online]. Available: https://d...

    2023

  62. [70]

    Blockchain-based privacy-preserving remote data integrity checking scheme for IoT information systems,

    Q. Zhao, S. Chen, Z. Liu, T. Baker, and Y. Zhang, “Blockchain-based privacy-preserving remote data integrity checking scheme for IoT information systems, ”Information Processing & Management , vol. 57, no. 6, p. 102355, 2020

    2020

  63. [71]

    Data security sharing model based on privacy protection for blockchain-enabled industrial Internet of Things,

    Q. Zhang, Y. Li, R. Wang, L. Liu, Y.-a. Tan, and J. Hu, “Data security sharing model based on privacy protection for blockchain-enabled industrial Internet of Things, ”International Journal of Intelligent Systems , vol. 36, no. 1, pp. 94–111, 2021. Manuscript submitted to ACM ...

    2021

  64. [72]

    Enterprise data sharing with privacy-preserved based on hyperledger fabric blockchain in iiot’s application,

    C.-L. Chen, J. Yang, W.-J. Tsaur, W. Weng, C.-M. Wu, and X. Wei, “Enterprise data sharing with privacy-preserved based on hyperledger fabric blockchain in iiot’s application, ”Sensors, vol. 22, no. 3, p. 1146, 2022

    2022

  65. [73]

    Blockchain and homomorphic encryption-based privacy-preserving data aggregation model in smart grid,

    P. Singh, M. Masud, M. S. Hossain, and A. Kaur, “Blockchain and homomorphic encryption-based privacy-preserving data aggregation model in smart grid, ”Computers & Electrical Engineering , vol. 93, p. 107209, 2021

    2021

  66. [74]

    VC-DCPS: Verifiable cross-domain data collection and privacy-persevering sharing scheme based on lattice in blockchain-enhanced smart grids,

    P.-B. Wang, K.-C. Li, R.-H. Shi, and B.-S. Shao, “VC-DCPS: Verifiable cross-domain data collection and privacy-persevering sharing scheme based on lattice in blockchain-enhanced smart grids, ”IEEE Internet of Things Journal , vol. 10, no. 14, pp. 12 449–12 461, Jul. 2023. [Onl...

    2023

  67. [75]

    Edge Blockchain Assisted Lightweight Privacy-Preserving Data Aggregation for Smart Grid,

    W. Lu, Z. Ren, J. Xu, and S. Chen, “Edge Blockchain Assisted Lightweight Privacy-Preserving Data Aggregation for Smart Grid, ”IEEE Transactions on Network and Service Management , vol. 18, no. 2, pp. 1246–1259, 2021

    2021

  68. [76]

    Provchain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability,

    X. Liang, S. Shetty, D. Tosh, C. Kamhoua, K. Kwiat, and L. Njilla, “Provchain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability, ” in2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGR...

    2017

  69. [77]

    Query integrity meets blockchain: A privacy-preserving verification framework for outsourced encrypted data,

    S. Jiang, J. Liu, J. Chen, Y. Liu, L. Wang, and Y. Zhou, “Query integrity meets blockchain: A privacy-preserving verification framework for outsourced encrypted data, ”IEEE Transactions on Services Computing , pp. 1–13, 2022. [Online]. Available: https://doi.org/10.1109/tsc.20...

    2022

  70. [78]

    Analysis of Using Blockchain to Protect the Privacy of Drone Big Data,

    Z. Lv, L. Qiao, M. S. Hossain, and B. J. Choi, “Analysis of Using Blockchain to Protect the Privacy of Drone Big Data, ”IEEE Network, vol. 35, no. 1, pp. 44–49, 2021

    2021

  71. [79]

    Privacy preserving in blockchain-based government data sharing: A service-on-chain (soc) approach,

    C. Piao, Y. Hao, J. Yan, and X. Jiang, “Privacy preserving in blockchain-based government data sharing: A service-on-chain (soc) approach, ” Information Processing & Management , vol. 58, no. 5, p. 102651, 2021

    2021

  72. [80]

    Blockchain-based privacy-preserving positioning data sharing for IoT-enabled maritime transportation systems,

    K. Gai, H. Tang, G. Li, T. Xie, S. Wang, L. Zhu, and K.-K. R. Choo, “Blockchain-based privacy-preserving positioning data sharing for IoT-enabled maritime transportation systems, ” IEEE Transactions on Intelligent Transportation Systems , pp. 1–15, 2022. [Online]. Available: h...

    2022

  73. [81]

    BFOD: Blockchain-based privacy protection and security sharing scheme of flight operation data,

    X. Li, H. Zhao, and W. Deng, “BFOD: Blockchain-based privacy protection and security sharing scheme of flight operation data, ”IEEE Internet of Things Journal, pp. 1–1, 2023. [Online]. Available: https://doi.org/10.1109/jiot.2023.3296460

    2023

  74. [82]

    Blockchain-based fair and fine-grained data trading with privacy preservation,

    L. Xue, J. Ni, D. Liu, X. Lin, and X. Shen, “Blockchain-based fair and fine-grained data trading with privacy preservation, ”IEEE Transactions on Computers, vol. 72, no. 9, pp. 2440–2453, Sep. 2023. [Online]. Available: https://doi.org/10.1109/tc.2023.3251846

    2023

  75. [83]

    MedRec: Using Blockchain for Medical Data Access and Permission Management,

    A. Azaria, A. Ekblaw, T. Vieira, and A. Lippman, “MedRec: Using Blockchain for Medical Data Access and Permission Management, ”2016 2nd International Conference on Open and Big Data (OBD) , pp. 25–30, 2016

    2016

  76. [84]

    MedChain: A Design of Blockchain-Based System for Medical Records Access and Permissions Management,

    E.-Y. Daraghmi, Y.-A. Daraghmi, and S.-M. Yuan, “MedChain: A Design of Blockchain-Based System for Medical Records Access and Permissions Management, ”IEEE Access, vol. 7, pp. 164 595–164 613, 2019

    2019

  77. [85]

    Design and implementation of a blockchain-based e-health consent management framework,

    C. C. Agbo and Q. H. Mahmoud, “Design and implementation of a blockchain-based e-health consent management framework, ” in 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) , 2020, pp. 812–817

    2020

  78. [87]

    Heimdall: Blockchain-based consent management framework,

    F. M. V. Filho, B. L. De Alcantara Batista, J. C. Júnior, and J. N. De Souza, “Heimdall: Blockchain-based consent management framework, ” in2023 International Conference on Information Networking (ICOIN) , 2023, pp. 487–492

    2023

  79. [88]

    Design and implementation of a personal health record platform based on patient-consent blockchain technology,

    H. Kim, S. Lee, H. Kwon, and E. K. and, “Design and implementation of a personal health record platform based on patient-consent blockchain technology, ”KSII Transactions on Internet and Information Systems , vol. 15, no. 12, pp. 4400–4419, December 2021

    2021

  80. [89]

    A Blockchain-Based Dynamic Consent Architecture to Support Clinical Genomic Data Sharing (ConsentChain): Proof-of-Concept Study,

    F. Albalwy, A. Brass, and A. Davies, “A Blockchain-Based Dynamic Consent Architecture to Support Clinical Genomic Data Sharing (ConsentChain): Proof-of-Concept Study, ”JMIR Medical Informatics, vol. 9, no. 11, p. e27816, 2021

    2021

  81. [90]

    DynamiChain: Development of Medical Blockchain Ecosystem Based on Dynamic Consent System,

    T. M. Kim, S.-J. Lee, D.-J. Chang, J. Koo, T. Kim, K.-H. Yoon, and I.-Y. Choi, “DynamiChain: Development of Medical Blockchain Ecosystem Based on Dynamic Consent System, ”Applied Sciences, vol. 11, no. 4, p. 1612, 2021

    2021

  82. [91]

    Blockchain-based multi-hop permission delegation scheme with controllable delegation depth for electronic health record sharing,

    Y. Gao, A. Zhang, S. Wu, and J. Chen, “Blockchain-based multi-hop permission delegation scheme with controllable delegation depth for electronic health record sharing, ” High-Confidence Computing , vol. 2, no. 4, p. 100084, 2022. [Online]. Available: https: //www.sciencedirect...

    2022

  83. [92]

    Metory: Development of a demand-driven blockchain-based dynamic consent platform tailored for clinical trials,

    K. Y. Huh, S.-u. Jeong, S. J. Moon, M.-J. Kim, W. Yang, M. Jeong, I. Song, Y.-G. Kwak, S. Lee, and M.-G. Kim, “Metory: Development of a demand-driven blockchain-based dynamic consent platform tailored for clinical trials, ” Frontiers in Medicine , vol. 9, 2022. [Online]. Avail...

    2022

  84. [93]

    CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing,

    C. Hu, C. Li, G. Zhang, Z. Lei, M. Shah, Y. Zhang, C. Xing, J. Jiang, and R. Bao, “CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing, ”World Wide Web, pp. 1–27, 2022

    2022

  85. [94]

    Dwarna: a blockchain solution for dynamic consent in biobanking,

    N. Mamo, G. M. Martin, M. Desira, B. Ellul, and J.-P. Ebejer, “Dwarna: a blockchain solution for dynamic consent in biobanking, ”European Journal of Human Genetics, vol. 28, no. 5, pp. 609–626, 2020

    2020

  86. [95]

    Mukhopadhyay and A

    I. Mukhopadhyay and A. Ghosh, Blockchain-Based Framework for Managing Customer Consent in Open Banking . Singapore: Springer Singapore, 2021, pp. 77–90. [Online]. Available: https://doi.org/10.1007/978-981-15-9317-8_3

    2021 doi

  87. [96]

    Gdpr compliant consent driven data protection in online social networks: A blockchain-based approach,

    J. Ahmed, S. Yildirim, M. Nowostaki, R. Ramachandra, O. Elezaj, and M. Abomohara, “Gdpr compliant consent driven data protection in online social networks: A blockchain-based approach, ” in2020 3rd International Conference on Information and Computer Technologies (ICICT) , 202...

    2020

  88. [97]

    Double-Blind Consent-Driven Data Sharing on Blockchain,

    K. Bhaskaran, P. Ilfrich, D. Liffman, C. Vecchiola, P. Jayachandran, A. Kumar, F. Lim, K. Nandakumar, Z. Qin, V. Ramakrishna, E. G. Teo, and C. H. Suen, “Double-Blind Consent-Driven Data Sharing on Blockchain, ”2018 IEEE International Conference on Cloud Engineering (IC2E) , p...

    2018

  89. [98]

    Implementing a forms of consent smart contract on an iot-based blockchain to promote user trust,

    C. S. Kouzinopoulos, K. M. Giannoutakis, K. Votis, D. Tzovaras, A. Collen, N. A. Nijdam, D. Konstantas, G. Spathoulas, P. Pandey, and S. Katsikas, “Implementing a forms of consent smart contract on an iot-based blockchain to promote user trust, ” in2018 Innovations in Intellig...

    2018

  90. [99]

    Advocate: a consent management platform for personal data processing in the iot using blockchain technology,

    K. Rantos, G. Drosatos, K. Demertzis, C. Ilioudis, A. Papanikolaou, and A. Kritsas, “Advocate: a consent management platform for personal data processing in the iot using blockchain technology, ” inInternational Conference on Security for Information Technology and Communicati...

    2018

  91. [100]

    Blockchain based permission delegation and access control in Internet of Things (BACI),

    G. Ali, N. Ahmad, Y. Cao, M. Asif, H. Cruickshank, and Q. E. Ali, “Blockchain based permission delegation and access control in Internet of Things (BACI), ”Computers & Security, vol. 86, pp. 318–334, 2019

    2019

  92. [101]

    Privacy of fitness applications and consent management in blockchain,

    M. Alhajri, A. Salehi Shahraki, and C. Rudolph, “Privacy of fitness applications and consent management in blockchain, ” in Australasian Computer Science Week 2022, ser. ACSW 2022. New York, NY, USA: Association for Computing Machinery, 2022, p. 65–73. [Online]. Available: htt...

    2022

  93. [102]

    AC2M: An Automated Consent Management Model for Blockchain Financial Services Platform,

    Z. Xu, T. Jiao, Z. Wang, S. Wen, S. Chen, and Y. Xiang, “AC2M: An Automated Consent Management Model for Blockchain Financial Services Platform, ”2021 IEEE International Conference on Smart Data Services (SMDS) , vol. 00, pp. 33–41, 2021

    2021

  94. [103]

    Blockchain enabled data trading with user consent,

    P. Banerjee, A. Muthaiah, and S. Ruj, “Blockchain enabled data trading with user consent, ” in2021 International Conference on COMmunication Systems & NETworkS (COMSNETS), 2021, pp. 263–271

    2021

  95. [104]

    A novel blockchain-based revocable permission management on cp-abe scheme,

    Q. Xv, Y. Song, X. Li, A. Hu, and J. Wang, “A novel blockchain-based revocable permission management on cp-abe scheme, ” inAdvances in Artificial Intelligence and Security, X. Sun, X. Zhang, Z. Xia, and E. Bertino, Eds. Cham: Springer International Publishing, 2021, pp. 650–663

    2021

  96. [105]

    Blockchain based model for consent management and data transparency assurance,

    D. Ameyed, F. Jaafar, F. Charette-Migneault, and M. Cheriet, “Blockchain based model for consent management and data transparency assurance, ” in 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C) , 2021, pp. 1050–1059

    2021

  97. [106]

    Blockchain for student data privacy and consent,

    S. Gilda and M. Mehrotra, “Blockchain for student data privacy and consent, ” in2018 International Conference on Computer Communication and Informatics (ICCCI), 2018, pp. 1–5

    2018

  98. [107]

    Unichain: A design of blockchain-based system for electronic academic records access and permissions management,

    E.-Y. Daraghmi, Y.-A. Daraghmi, and S.-M. Yuan, “Unichain: A design of blockchain-based system for electronic academic records access and permissions management, ”Applied Sciences, vol. 9, no. 22, 2019. [Online]. Available: https://www.mdpi.com/2076-3417/9/22/4966

    2019

  99. [108]

    A blockchain-based consent platform for active assisted living: Modeling study and conceptual framework,

    P. E. Velmovitsky, P. A. D. S. E. S. Miranda, H. Vaillancourt, T. Donovska, J. Teague, and P. P. Morita, “A blockchain-based consent platform for active assisted living: Modeling study and conceptual framework, ”J Med Internet Res , vol. 22, no. 12, p. e20832, Dec 2020. [Onlin...

    2020

  100. [109]

    A blockchain-based privacy-preserving model for consent and transparency in human-centered internet of things,

    J. E. Rivadeneira, M. B. Jiménez, R. Marculescu, A. Rodrigues, F. Boavida, and J. S. Silva, “A blockchain-based privacy-preserving model for consent and transparency in human-centered internet of things, ” inProceedings of the 8th ACM/IEEE Conference on Internet of Things Desi...

    2023

  101. [110]

    A formal model for blockchain-based consent management in data sharing,

    N. Peyrone and D. Wichadakul, “A formal model for blockchain-based consent management in data sharing, ”Journal of Logical and Algebraic Methods in Programming, vol. 134, p. 100886, Aug. 2023. [Online]. Available: https://doi.org/10.1016/j.jlamp.2023.100886

    2023

  102. [111]

    Blockchain protocols in clinical trials: Transparency and traceability of consent,

    M. Benchoufi, R. Porcher, and P. Ravaud, “Blockchain protocols in clinical trials: Transparency and traceability of consent, ”F1000Research, vol. 6, p. 66, 2017

    2017

  103. [112]

    A Consent Model for Blockchain-Based Health Data Sharing Platforms,

    V. Jaiman and V. Urovi, “A Consent Model for Blockchain-Based Health Data Sharing Platforms, ”IEEE Access, vol. 8, pp. 143 734–143 745, 2020

    2020

  104. [113]

    Patient consent management by a purpose-based consent model for electronic health record based on blockchain technology,

    D. Tith, “Patient consent management by a purpose-based consent model for electronic health record based on blockchain technology, ”Healthcare Informatics Research, vol. 26, no. 4, pp. 265–273, 2020, query date: 2022-04-02 08:52:14

    2020

  105. [114]

    Dynamic consent management for clinical trials via private blockchain technology,

    G. Albanese, J.-P. Calbimonte, M. Schumacher, and D. Calvaresi, “Dynamic consent management for clinical trials via private blockchain technology, ” Journal of ambient intelligence and humanized computing , vol. 11, no. 11, pp. 4909–4926, 2020

    2020

  106. [115]

    Blockchain, consent and prosent for medical research,

    S. Porsdam Mann, J. Savulescu, P. Ravaud, and M. Benchoufi, “Blockchain, consent and prosent for medical research, ”Journal of Medical Ethics , vol. 47, no. 4, pp. 244–250, 2021. [Online]. Available: https://jme.bmj.com/content/47/4/244

    2021

  107. [116]

    Bdss: Blockchain-based data sharing scheme with fine-grained access control and permission revocation in medical environment,

    L. Zhang, Y. Zou, M. H. Yousuf, W. Wang, Z. Jin, Y. Su, and K. S. and, “Bdss: Blockchain-based data sharing scheme with fine-grained access control and permission revocation in medical environment, ”KSII Transactions on Internet and Information Systems , vol. 16, no. 5, pp. 16...

    2022

  108. [117]

    Self-sovereign dynamic digital identities based on blockchain technology,

    H. Gulati and C.-T. Huang, “Self-sovereign dynamic digital identities based on blockchain technology, ” in2019 SoutheastCon, 2019, pp. 1–6

    2019

  109. [118]

    An innovative and decentralized identity framework based on blockchain technology,

    D. Maldonado-Ruiz, J. Torres, N. El Madhoun, and M. Badra, “An innovative and decentralized identity framework based on blockchain technology, ” in 2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS) , 2021, pp. 1–8

    2021

  110. [119]

    Blockchain and self-sovereign identity empowered cyber threat information sharing platform,

    E. Bandara, X. Liang, P. Foytik, and S. Shetty, “Blockchain and self-sovereign identity empowered cyber threat information sharing platform, ” in 2021 IEEE International Conference on Smart Computing (SMARTCOMP) , 2021, pp. 258–263

    2021

  111. [120]

    Hei-bct: A framework to implement blockchain-based self-sovereign identity solution in higher education institutions,

    S. A. Mansoori and P. Maheshwari, “Hei-bct: A framework to implement blockchain-based self-sovereign identity solution in higher education institutions, ” in2022 8th International Conference on Information Technology Trends (ITT) , 2022, pp. 6–10

    2022

  112. [121]

    uport open-source identity management system: An assessment of self-sovereign identity and user-centric data platform built on blockchain,

    N. Naik and P. Jenkins, “uport open-source identity management system: An assessment of self-sovereign identity and user-centric data platform built on blockchain, ” in2020 IEEE International Symposium on Systems Engineering (ISSE) , 2020, pp. 1–7

    2020

  113. [122]

    Everssdi: Blockchain-based framework for verification, authorisation and recovery of self-sovereign identity using smart contracts,

    T. Zhou, X. Li, and H. Zhao, “Everssdi: Blockchain-based framework for verification, authorisation and recovery of self-sovereign identity using smart contracts, ”Int. J. Comput. Appl. Technol., vol. 60, no. 3, p. 281–295, jan 2019. [Online]. Available: https://doi.org/10.1504...

    2019

  114. [123]

    A self-sovereign identity management system using blockchain,

    T. Rathee and P. Singh, “A self-sovereign identity management system using blockchain, ” inCyber Security and Digital Forensics , K. Khanna, V. V. Estrela, and J. J. P. C. Rodrigues, Eds. Singapore: Springer Singapore, 2022, pp. 371–379

    2022

  115. [124]

    A self-sovereign decentralized identity platform based on blockchain,

    Y. Chen, C. Liu, Y. Wang, and Y. Wang, “A self-sovereign decentralized identity platform based on blockchain, ” in2021 IEEE Symposium on Computers and Communications (ISCC), 2021, pp. 1–7

    2021

  116. [125]

    Decentralized cross-network identity management for blockchain interoperation,

    B. C. Ghosh, V. Ramakrishna, C. Govindarajan, D. Behl, D. Karunamoorthy, E. Abebe, and S. Chakraborty, “Decentralized cross-network identity management for blockchain interoperation, ” in2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) , 2021, pp. 1–9

    2021

  117. [126]

    Technical design and development of a self-sovereign identity management platform for patient-centric healthcare using blockchain technology,

    D. T. Harrell, M. Usman, L. Hanson, M. Abdul-Moheeth, I. Desai, J. Shriram, E. de Oliveira, J. R. Bautista, E. T. Meyer, and A. Khurshid, “Technical design and development of a self-sovereign identity management platform for patient-centric healthcare using blockchain technolo...

    2022

  118. [127]

    Towards convergence of blockchain and self-sovereign identity for privacy-preserving secure federated learning,

    R. U. Haque, A. S. M. T. Hasan, A. Daria, Q. Qu, and Q. Jiang, “Towards convergence of blockchain and self-sovereign identity for privacy-preserving secure federated learning, ” inBig Data and Security , Y. Tian, T. Ma, M. K. Khan, V. S. Sheng, and Z. Pan, Eds. Singapore: Spri...

    2022

  119. [128]

    Health-id: A blockchain-based decentralized identity management for remote healthcare,

    I. T. Javed, F. Alharbi, B. Bellaj, T. Margaria, N. Crespi, and K. N. Qureshi, “Health-id: A blockchain-based decentralized identity management for remote healthcare, ”Healthcare, vol. 9, no. 6, 2021. [Online]. Available: https://www.mdpi.com/2227-9032/9/6/712

    2021

  120. [129]

    A decentralized identity-based blockchain solution for privacy-preserving licensing of individual-controlled data to prevent unauthorized secondary data usage,

    M. Kang and V. Lemieux, “A decentralized identity-based blockchain solution for privacy-preserving licensing of individual-controlled data to prevent unauthorized secondary data usage, ”Ledger, vol. 6, Nov. 2021. [Online]. Available: https://ledger.pitt.edu/ojs/ledger/article/view/239

    2021

  121. [130]

    A decentralized iiot identity framework based on self-sovereign identity using blockchain,

    A. Dixit, M. Smith-Creasey, and M. Rajarajan, “A decentralized iiot identity framework based on self-sovereign identity using blockchain, ” in2022 IEEE 47th Conference on Local Computer Networks (LCN) , 2022, pp. 335–338

    2022

  122. [131]

    Securing emission data of smart vehicles with blockchain and self-sovereign identities,

    S. Terzi, C. Savvaidis, K. Votis, D. Tzovaras, and I. Stamelos, “Securing emission data of smart vehicles with blockchain and self-sovereign identities, ” in 2020 IEEE International Conference on Blockchain (Blockchain) , 2020, pp. 462–469

    2020

  123. [132]

    Designing a framework for digital kyc processes built on blockchain-based self-sovereign identity,

    V. Schlatt, J. Sedlmeir, S. Feulner, and N. Urbach, “Designing a framework for digital kyc processes built on blockchain-based self-sovereign identity, ”Information & Management, vol. 59, no. 7, p. 103553, 2022, blockchain Innovations: Business Opportunities and Management Cha...

    2022

  124. [133]

    Bbm: A blockchain-based model for open banking via self-sovereign identity,

    C. Dong, Z. Wang, S. Chen, and Y. Xiang, “Bbm: A blockchain-based model for open banking via self-sovereign identity, ” inBlockchain – ICBC 2020 , Z. Chen, L. Cui, B. Palanisamy, and L.-J. Zhang, Eds. Cham: Springer International Publishing, 2020, pp. 61–75

    2020

  125. [134]

    Deployment of a blockchain-based self-sovereign identity,

    Q. Stokkink and J. Pouwelse, “Deployment of a blockchain-based self-sovereign identity, ” in2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE...

    2018

  126. [135]

    Enhancing the security and privacy of self-sovereign identities on hyperledger indy blockchain,

    M. P. Bhattacharya, P. Zavarsky, and S. Butakov, “Enhancing the security and privacy of self-sovereign identities on hyperledger indy blockchain, ” in 2020 International Symposium on Networks, Computers and Communications (ISNCC) , 2020, pp. 1–7

    2020

  127. [136]

    A blockchain-based self-sovereign identity approach for inter-organizational business processes,

    A. Abid, S. Cheikhrouhou, S. Kallel, and M. Jmaiel, “A blockchain-based self-sovereign identity approach for inter-organizational business processes, ” in 2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS) . IEEE, 2022, pp. 685–694

    2022

  128. [137]

    Blockchain-enabled decentralized identity management: The case of self-sovereign identity in public transportation,

    L. Stockburger, G. Kokosioulis, A. Mukkamala, R. R. Mukkamala, and M. Avital, “Blockchain-enabled decentralized identity management: The case of self-sovereign identity in public transportation, ”Blockchain: Research and Applications, vol. 2, no. 2, p. 100014, 2021. [Online]. ...

    2021

  129. [138]

    Governing principles of self-sovereign identity applied to blockchain enabled privacy preserving identity management systems,

    N. Naik and P. Jenkins, “Governing principles of self-sovereign identity applied to blockchain enabled privacy preserving identity management systems, ” in2020 IEEE International Symposium on Systems Engineering (ISSE) , 2020, pp. 1–6

    2020

  130. [139]

    Blockchain and self sovereign identity to support quality in the food supply chain,

    L. Cocco, R. Tonelli, and M. Marchesi, “Blockchain and self sovereign identity to support quality in the food supply chain, ”Future Internet, vol. 13, no. 12, 2021. [Online]. Available: https://www.mdpi.com/1999-5903/13/12/301

    2021

  131. [140]

    In search of self-sovereign identity leveraging blockchain technology,

    M. S. Ferdous, F. Chowdhury, and M. O. Alassafi, “In search of self-sovereign identity leveraging blockchain technology, ”IEEE Access, vol. 7, pp. 103 059–103 079, 2019

    2019

  132. [141]

    Self-sovereign identity specifications: Govern your identity through your digital wallet using blockchain technology,

    N. Naik and P. Jenkins, “Self-sovereign identity specifications: Govern your identity through your digital wallet using blockchain technology, ” in 2020 8th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) , 2020, pp. 90–95

    2020

  133. [142]

    Awesome zero knowledge proofs,

    M. Labs, “Awesome zero knowledge proofs, ” https://github.com/matter-labs/awesome-zero-knowledge-proofs?ref=blog.pantherprotocol.io, 2021, gitHub repository

    2021

  134. [143]

    Succinct non-interactive zero knowledge for a von neumann architecture,

    E. Ben-Sasson, A. Chiesa, E. Tromer, and M. Virza, “Succinct non-interactive zero knowledge for a von neumann architecture, ” inProceedings of the 23rd USENIX Conference on Security Symposium , ser. SEC’14. USA: USENIX Association, 2014, p. 781–796

    2014

  135. [144]

    Scalable, transparent, and post-quantum secure computational integrity,

    E. Ben-Sasson, I. Bentov, Y. Horesh, and M. Riabzev, “Scalable, transparent, and post-quantum secure computational integrity, ” Cryptology ePrint Archive, Paper 2018/046, 2018, https://eprint.iacr.org/2018/046. [Online]. Available: https://eprint.iacr.org/2018/046

    2018

  136. [145]

    Bulletproofs: Short proofs for confidential transactions and more,

    S. Research, “Bulletproofs: Short proofs for confidential transactions and more, ” 05 2019. [Online]. Available: https://sikoba.com/docs/SKOR_DK_ Bulletproofs_201905.pdf

    2019

  137. [146]

    Candidate indistinguishability obfuscation and functional encryption for all circuits,

    S. Garg, C. Gentry, S. Halevi, M. Raykova, A. Sahai, and B. Waters, “Candidate indistinguishability obfuscation and functional encryption for all circuits, ”SIAM Journal on Computing , vol. 45, no. 3, pp. 882–929, Jan. 2016. [Online]. Available: https://doi.org/10.1137/14095772x

    2016 doi

  138. [147]

    A fully homomorphic encryption scheme,

    C. Gentry, “A fully homomorphic encryption scheme, ” Ph.D. dissertation, Stanford University, 2009, crypto.stanford.edu/craig

    2009

  139. [148]

    Enigma: Decentralized computation platform with guaranteed privacy,

    G. Zyskind, O. Nathan, and A. Pentland, “Enigma: Decentralized computation platform with guaranteed privacy, ” 2015. Manuscript submitted to ACM 34 Garcia R.D, et al

    2015

  140. [149]

    Ekiden: A platform for confidentiality-preserving, trustworthy, and performant smart contracts,

    R. Cheng, F. Zhang, J. Kos, W. He, N. Hynes, N. Johnson, A. Juels, A. Miller, and D. Song, “Ekiden: A platform for confidentiality-preserving, trustworthy, and performant smart contracts, ” in2019 IEEE European Symposium on Security and Privacy (EuroS&P) , 2019, pp. 185–200

    2019

  141. [150]

    A mixing scheme using a decentralized signature protocol for privacy protection in bitcoin blockchain,

    R. Xiao, W. Ren, T. Zhu, and K.-K. R. Choo, “A mixing scheme using a decentralized signature protocol for privacy protection in bitcoin blockchain, ” IEEE Transactions on Dependable and Secure Computing , vol. 18, no. 4, pp. 1793–1803, 2021

    2021

  142. [151]

    Privacy-preserving cross-chain atomic swaps,

    A. Deshpande and M. Herlihy, “Privacy-preserving cross-chain atomic swaps, ” inFinancial Cryptography and Data Security . Springer International Publishing, 2020, pp. 540–549. [Online]. Available: https://doi.org/10.1007/978-3-030-54455-3_38

    2020 doi

  143. [152]

    Dandelion: Redesigning the bitcoin network for anonymity,

    S. B. Venkatakrishnan, G. Fanti, and P. Viswanath, “Dandelion: Redesigning the bitcoin network for anonymity, ” 2017

    2017

  144. [153]

    Dandelion++: Lightweight cryptocurrency networking with formal anonymity guarantees,

    G. Fanti, S. B. Venkatakrishnan, S. Bakshi, B. Denby, S. Bhargava, A. Miller, and P. Viswanath, “Dandelion++: Lightweight cryptocurrency networking with formal anonymity guarantees, ” 2018

    2018

  145. [154]

    Tumblebit++:: A comprehensive privacy protocol providing anonymity and amount-invisibility,

    Y. Liu, Z. Liu, Y. Long, Z. Liu, D. Gu, F. Huan, and Y. Jia, “Tumblebit++:: A comprehensive privacy protocol providing anonymity and amount-invisibility, ” inProvable Security. Springer International Publishing, 2019, pp. 339–346. [Online]. Available: https://doi.org/10.1007/9...

    2019 doi

  146. [155]

    Mimblewimble,

    T. E. Jedusor, “Mimblewimble, ” July 2016, accessed: 2022-12-26. [Online]. Available: https://github.com/mimblewimble/docs/wiki/MimbleWimble- Origin

    2016

  147. [156]

    Scalable blockchain model using off-chain ipfs storage for healthcare data security and privacy,

    J. Jayabalan and N. Jeyanthi, “Scalable blockchain model using off-chain ipfs storage for healthcare data security and privacy, ”Journal of Parallel and Distributed Computing, vol. 164, pp. 152–167, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S...

    2022

  148. [157]

    Towards design and implementation of security and privacy framework for internet of medical things (IoMT) by leveraging blockchain and IPFS technology,

    R. Kumar and R. Tripathi, “Towards design and implementation of security and privacy framework for internet of medical things (IoMT) by leveraging blockchain and IPFS technology, ” The Journal of Supercomputing , vol. 77, no. 8, pp. 7916–7955, Jan. 2021. [Online]. Available: h...

    2021 doi

  149. [158]

    A survey on blockchain-based self-sovereign patient identity in healthcare,

    B. Houtan, A. S. Hafid, and D. Makrakis, “A survey on blockchain-based self-sovereign patient identity in healthcare, ” IEEE Access, vol. 8, pp. 90 478–90 494, 2020

    2020

  150. [159]

    Self-sovereign identity in university context,

    A. Queiruga-Dios, J. José Bullón Pérez, and L. Hernández Encinas, “Self-sovereign identity in university context, ” in 2022 31st Conference of Open Innovations Association (FRUCT), 2022, pp. 259–264

    2022

  151. [160]

    Short group signatures,

    D. Boneh, X. Boyen, and H. Shacham, “Short group signatures, ” inAdvances in Cryptology – CRYPTO 2004 , M. Franklin, Ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004, pp. 41–55

    2004

  152. [161]

    The bbs signature scheme,

    D. I. Foundation, “The bbs signature scheme, ” https://github.com/decentralized-identity/bbs-signature, 2023, accessed: 2023-02-20

    2023

  153. [162]

    A survey of blockchain consensus safety and security: State-of-the-art, challenges, and future work,

    Q. Bao, B. Li, T. Hu, and X. Sun, “A survey of blockchain consensus safety and security: State-of-the-art, challenges, and future work, ”Journal of Systems and Software, vol. 196, p. 111555, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S016412122200231X

    2023

  154. [163]

    A systematic review of blockchain scalability: Issues, solutions, analysis and future research,

    A. I. Sanka and R. C. Cheung, “A systematic review of blockchain scalability: Issues, solutions, analysis and future research, ”Journal of Network and Computer Applications, vol. 195, p. 103232, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1084...

    2021

  155. [164]

    A survey on blockchain-based iomt systems: Towards scalability,

    A. Adavoudi Jolfaei, S. F. Aghili, and D. Singelee, “A survey on blockchain-based iomt systems: Towards scalability, ” IEEE Access, vol. 9, pp. 148 948–148 975, 2021

    2021

  156. [165]

    Solutions to scalability of blockchain: A survey,

    Q. Zhou, H. Huang, Z. Zheng, and J. Bian, “Solutions to scalability of blockchain: A survey, ” IEEE Access, vol. 8, pp. 16 440–16 455, 2020. Manuscript submitted to ACM

    2020

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.