pith. sign in

arxiv: 2605.16563 · v1 · pith:TTNKFCDVnew · submitted 2026-05-15 · 💻 cs.CR · cs.MM· eess.IV

A Method for Securely Transmitting Large Video Files Using Chaotic Compression and Encryption

Shiladitya Bhattacharjee , Subha Bhattacharya , Arnab Chatterjee , Sulabh Bansal , Saurabh Shukla This is my paper

Pith reviewed 2026-05-20 16:32 UTC · model grok-4.3

classification 💻 cs.CR cs.MMeess.IV
keywords chaotic encryptionHuffman encodingvideo compressionsecure transmissionlogistic mapSDCE systemlossless compression
0
0 comments X

The pith

A new system pairs logistic-map chaotic sequences with Huffman encoding to compress and encrypt large video files in one pass.

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

The paper presents an SDCE framework that generates a pseudo-random sequence from the logistic map, uses it for XOR encryption, and applies Huffman encoding for lossless compression. This single integrated process is claimed to cut computational load and processing time compared with separate compression-then-encryption pipelines. A sympathetic reader would care because real-time transmission of large videos often fails when security and compression are handled sequentially, and the method reports gains in throughput, compression ratio, PSNR, entropy, and avalanche effect while lowering bits per coefficient and data loss.

Core claim

The SDCE system using logistic map to generate pseudo-random chaotic sequence for XOR-based encryption combined with Huffman encoding for lossless compression markedly diminishes computational overhead while augmenting data security and produces superior throughput, compression ratio, PSNR, reduced BPC, greater entropy and avalanche effects with smaller percentage of data loss compared to existing methods.

What carries the argument

The SDCE framework that merges logistic-map chaotic sequence generation for XOR encryption with Huffman encoding for lossless compression, performing both operations together to reduce overhead.

If this is right

  • Real-time secure video streaming becomes feasible on resource-limited devices because separate compression and encryption steps are eliminated.
  • Higher entropy and avalanche effect reduce the chance that partial leaks reveal meaningful video content.
  • Lower BPC and data loss improve storage and transmission efficiency while preserving visual quality measured by PSNR.
  • The single-pass design shortens overall latency for applications that must both protect and shrink large files.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same logistic-map-plus-Huffman pairing could be tested on audio streams or image sequences to check whether the overhead reduction generalizes beyond video.
  • Replacing the logistic map with other chaotic generators might further improve the avalanche effect if the current choice proves limiting.
  • Hardware acceleration of the combined XOR and Huffman steps could push throughput even higher than the software results shown.

Load-bearing premise

That combining the logistic map sequence with Huffman encoding will reliably produce the reported security and performance gains on large video files without dataset-specific tuning or parameter adjustments.

What would settle it

A head-to-head run on the same large video test set that measures whether the claimed SDCE system actually exceeds prior methods in throughput, PSNR, entropy, avalanche effect, and data-loss percentage.

Figures

Figures reproduced from arXiv: 2605.16563 by Arnab Chatterjee, Saurabh Shukla, Shiladitya Bhattacharjee, Subha Bhattacharya, Sulabh Bansal.

Figure 1
Figure 1. Figure 1: shows a broad impression of the encoding of videos with chaotic encryption and compression at the transmitting end and decoding at the receiving end. Sending End Receiving End Communication Channel Playback Extracted Video Extracted Audio Input Video Input Audio Encoder Secure Compression Decoder [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: shows the exploration framework for chaos-based video compression and encryption. These three can be added to compress and cypher data contemporaneously; therefore, it is mainly worth probing chaos, contraction, and cryptography for practical operations [32, 33]. Chaotic Compression and Encryption Decompression and Decryption With Chaotic Algorithm Input Video Decrypted and Decompressed Video Chaotic Video… view at source ↗
Figure 3
Figure 3. Figure 3: Workings of lossless and lossy compression complete removal of redundant data sets during compression results in outstanding compression efficiency. In scenarios where the preservation of high data quality is not critical, lossy compression is preferable for these applications. The primary lossy compression methods for audio, video, image, and text media files include MP3, MP4, MPEG, and JPEG [7, 37]. Cons… view at source ↗
Figure 4
Figure 4. Figure 4: Workings of the proposed technique [PITH_FULL_IMAGE:figures/full_fig_p019_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: P SNR, offered by different chaotic approaches data loss during processing and transmission, relative to other comparable methods, thereby validating its ability to improve data integrity. According to the definition, any data processing and transmission system that ensures a reduced percentage of information loss is guaranteed to preserve data quality [13]. Consequently, the proposed chaotic strategy, alo… view at source ↗
Figure 6
Figure 6. Figure 6: P SNR, offered by different chaotic approaches [PITH_FULL_IMAGE:figures/full_fig_p031_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Bits Per Code, offered by different chaotic com￾pression approaches [PITH_FULL_IMAGE:figures/full_fig_p032_7.png] view at source ↗
read the original abstract

Conventional techniques for compression and encryption are frequently laborious and resource-intensive, rendering them inappropriate for real-time applications. A plethora of research has been presented in the current literature to address these difficulties together; yet, it fails to propose any suitable strategy. Therefore, this study introduces an innovative simultaneous data compression and encryption (SDCE) system specifically designed for large video files. The methodology amalgamates chaotic map-based encryption with Huffman encoding for lossless compression into a cohesive framework, markedly diminishing computational overhead and processing duration while augmenting data security. The logistic map is utilized to produce a pseudo-random chaotic sequence for XOR-based encryption, guaranteeing robust security against unwanted access. The research findings demonstrate its efficacy in enhancing data privacy compared to other existing and related strategies, particularly in terms of generating greater entropy and avalanche effects. It produces superior throughput, compression ratio, peak signal-to-noise ratio (PSNR), and reduced bits per rate (BPC), along with a smaller percentage of data loss, which further supports its ability to provide enhanced data integrity compared to other existing methods.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper proposes a simultaneous data compression and encryption (SDCE) framework for large video files that combines logistic-map-generated chaotic sequences for XOR encryption with Huffman encoding for lossless compression. It claims this integrated approach reduces computational overhead and processing time while providing robust security, evidenced by higher entropy and avalanche effects, along with improved throughput, compression ratio, PSNR, lower BPC, and reduced data loss relative to existing methods.

Significance. If the performance and security claims were substantiated through rigorous, reproducible experiments with independent baselines and attack simulations, the work could contribute a lightweight combined compression-encryption pipeline suitable for real-time video transmission in bandwidth-limited settings. The integration of a simple chaotic map with Huffman coding is conceptually straightforward and could be of practical interest if the reported gains hold under scrutiny.

major comments (2)
  1. [Abstract] Abstract: The manuscript asserts superior metrics including higher entropy, avalanche effects, throughput, PSNR, compression ratio, and lower BPC and data loss compared to 'other existing methods,' yet supplies no numerical results, tables, figures, error bars, or explicit baseline comparisons. This absence prevents verification of the central performance claims.
  2. [Methodology] Methodology (logistic map XOR stage): The security augmentation is attributed to the pseudo-random sequence from the logistic map (typically r=4) used for XOR, but the text provides no key-space analysis, period-length evaluation under finite precision, differential cryptanalysis, or resistance to known-plaintext reconstruction attacks. These omissions are load-bearing for the 'robust security' and 'greater entropy and avalanche effects' assertions.
minor comments (1)
  1. [Abstract] Abstract contains minor phrasing issues such as 'reduced bits per rate (BPC)' (should be 'bits per code' or 'bits per pixel') and repeated use of 'other existing methods' without citation.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the thoughtful and constructive review. The comments highlight important areas where the presentation of results and the depth of security analysis can be strengthened. We will revise the manuscript accordingly to improve clarity and rigor while preserving the core contributions of the SDCE framework.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The manuscript asserts superior metrics including higher entropy, avalanche effects, throughput, PSNR, compression ratio, and lower BPC and data loss compared to 'other existing methods,' yet supplies no numerical results, tables, figures, error bars, or explicit baseline comparisons. This absence prevents verification of the central performance claims.

    Authors: We agree that the abstract should provide concrete numerical evidence to support the performance claims. The full manuscript contains experimental results with tables comparing our method against existing approaches, but these were not summarized numerically in the abstract. In the revised version we will update the abstract to include specific quantitative values (e.g., entropy, avalanche effect percentage, throughput in Mbps, compression ratio, PSNR, BPC, and data-loss percentage) along with the corresponding baseline methods used for comparison. revision: yes

  2. Referee: [Methodology] Methodology (logistic map XOR stage): The security augmentation is attributed to the pseudo-random sequence from the logistic map (typically r=4) used for XOR, but the text provides no key-space analysis, period-length evaluation under finite precision, differential cryptanalysis, or resistance to known-plaintext reconstruction attacks. These omissions are load-bearing for the 'robust security' and 'greater entropy and avalanche effects' assertions.

    Authors: The referee is correct that a formal security analysis section is currently missing and is necessary to substantiate the security claims. The manuscript reports empirical entropy and avalanche-effect measurements obtained from the chaotic sequence, but does not include key-space calculations, finite-precision period analysis, or explicit cryptanalytic evaluations. We will add a new subsection titled “Security Analysis” that provides: (1) key-space size based on the logistic-map parameters and initial conditions, (2) discussion of sequence periodicity under IEEE-754 floating-point arithmetic, (3) results from differential cryptanalysis experiments, and (4) resistance to known-plaintext attacks demonstrated through reconstruction attempts on sample video frames. These additions will be supported by additional experiments if needed. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper proposes a combined SDCE framework that applies a logistic map to generate a sequence for XOR encryption and pairs it with Huffman encoding for compression. It then reports empirical measurements of standard metrics (entropy, avalanche effect, PSNR, BPC, throughput, compression ratio) on video data and compares those measurements to results from other published methods. No equations or definitions are shown to be self-referential, no fitted parameters are relabeled as independent predictions, and no load-bearing claim reduces to a self-citation whose content is itself unverified. The reported performance numbers are obtained by direct execution of the described algorithm on test files and are therefore falsifiable against external implementations or datasets.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard assumptions about chaotic maps generating usable pseudo-random sequences for encryption and Huffman coding achieving lossless compression; no new entities are introduced and the logistic map parameter is a typical free choice in such systems.

free parameters (1)
  • Logistic map control parameter
    Value chosen to place the map in chaotic regime for generating the encryption sequence; typical in logistic-map crypto papers and not derived from first principles here.
axioms (2)
  • domain assumption Logistic map in chaotic regime produces sequences with sufficient randomness for XOR encryption to resist unwanted access
    Invoked when stating the sequence guarantees robust security; standard assumption in chaotic cryptography but not proven in this work.
  • domain assumption Huffman encoding combined with prior XOR step remains lossless and yields the reported compression ratios
    Assumed when claiming reduced BPC and data integrity; follows from properties of Huffman coding but integration effects are unexamined.

pith-pipeline@v0.9.0 · 5733 in / 1570 out tokens · 58210 ms · 2026-05-20T16:32:25.706994+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

90 extracted references · 90 canonical work pages

  1. [1]

    Improved chaos-based video steganography using dna alphabets.ICT Express, 4(1):6–13, 2018

    Nirmalya Kar, Kaushik Mandal, and Baby Bhattacharya. Improved chaos-based video steganography using dna alphabets.ICT Express, 4(1):6–13, 2018

    work page 2018

  2. [2]

    Efficient encryption tech- nique for h

    Fatma K Tabash and Muhammed Izharuddin. Efficient encryption tech- nique for h. 264/avc videos based on cabac and logistic map.Multimedia Tools and Applications, 78(6):7365–7379, 2019

    work page 2019

  3. [3]

    Big data: survey, technologies, opportu- nities, and challenges.The scientific world journal, 2014(1):712826, 2014

    Nawsher Khan, Ibrar Yaqoob, Ibrahim Abaker Targio Hashem, Zakira In- ayat, Waleed Kamaleldin Mahmoud Ali, Muhammad Alam, Muhammad Shiraz, and Abdullah Gani. Big data: survey, technologies, opportu- nities, and challenges.The scientific world journal, 2014(1):712826, 2014

    work page 2014

  4. [4]

    Big data innovations in enterprise information systems: strategies formation for new generation entrepreneurs.Enterprise Information Systems, 19(1-2):2449261, 2025

    Brij B Gupta, Akshat Gaurav, Varsha Arya, and Prabin Kumar Pani- grahi. Big data innovations in enterprise information systems: strategies formation for new generation entrepreneurs.Enterprise Information Systems, 19(1-2):2449261, 2025

    work page 2025

  5. [5]

    Optimal key gener- ation for privacy preservation in big data applications based on the marine predator whale optimization algorithm.Annals of Data Science, 12(2):539–569, 2025

    Poonam Samir Jadhav and Gautam M Borkar. Optimal key gener- ation for privacy preservation in big data applications based on the marine predator whale optimization algorithm.Annals of Data Science, 12(2):539–569, 2025

    work page 2025

  6. [6]

    Depreciating motivation and empirical security analysis of chaos- based image and video encryption.IEEE Transactions on Information Forensics and Security, 13(9):2137–2150, 2018

    Mario Preishuber, Thomas H¨ utter, Stefan Katzenbeisser, and Andreas Uhl. Depreciating motivation and empirical security analysis of chaos- based image and video encryption.IEEE Transactions on Information Forensics and Security, 13(9):2137–2150, 2018

    work page 2018

  7. [7]

    Level by level image compression-encryption algorithm based on quantum chaos map.Journal of King Saud University-Computer and Information Sciences, 33(7):844–851, 2021

    Ranjeet Kumar Singh, Binod Kumar, Dilip Kumar Shaw, and Danish Ali Khan. Level by level image compression-encryption algorithm based on quantum chaos map.Journal of King Saud University-Computer and Information Sciences, 33(7):844–851, 2021

    work page 2021

  8. [8]

    Efficient pro- tection using chaos for context-adaptive binary arithmetic coding in h

    Yanjie Song, Zhiliang Zhu, Wei Zhang, and Hai Yu. Efficient pro- tection using chaos for context-adaptive binary arithmetic coding in h. 264/advanced video coding.Multimedia Tools and Applications, 78(14):18967–18994, 2019

    work page 2019

  9. [9]

    An efficient video slice encryption scheme and its application.Cybersecurity, 8(1):40, 2025

    Qinyou Huang, Luping Wang, and Jie Chen. An efficient video slice encryption scheme and its application.Cybersecurity, 8(1):40, 2025

    work page 2025

  10. [10]

    Video encryption/compression using com- pressive coded rotating mirror camera.Scientific Reports, 11(1):23191, 2021

    Amir Matin and Xu Wang. Video encryption/compression using com- pressive coded rotating mirror camera.Scientific Reports, 11(1):23191, 2021

    work page 2021

  11. [11]

    A security scheme to minimize information loss during big data transmission over the internet

    Shiladitya Bhattacharjee, Lukman Bin A Rahim, and Izzatdin BA Aziz. A security scheme to minimize information loss during big data transmission over the internet. In2016 3rd International Conference on Computer and Information Sciences (ICCOINS), pages 215–220. IEEE, 2016

    work page 2016

  12. [12]

    A lossless compression technique to increase robustness in big 35 data transmission system.International Journal in Advances in Soft Computing and Its Application, 2015

    Shiladitya Bhattacharjee, Lukman Bin Ab Rahim, and Izzatdin Bin A Aziz. A lossless compression technique to increase robustness in big 35 data transmission system.International Journal in Advances in Soft Computing and Its Application, 2015

    work page 2015

  13. [13]

    Leveraging chaos for enhancing encryption and compression in large cloud data transfers: S

    Shiladitya Bhattacharjee, Himanshi Sharma, Tanupriya Choudhury, and Ahmed M Abdelmoniem. Leveraging chaos for enhancing encryption and compression in large cloud data transfers: S. bhattacharjee et al. The Journal of Supercomputing, 80(9):11923–11957, 2024

    work page 2024

  14. [14]

    Improved fractal coding and hyperchaotic system for lossless image compression and encryption.Nonlinear Dynamics, 113(10):12233–12262, 2025

    Bofeng Long, Zhong Chen, Tongzhe Liu, Ximei Wu, Chenchen He, Lujie Wang, and Can Cao. Improved fractal coding and hyperchaotic system for lossless image compression and encryption.Nonlinear Dynamics, 113(10):12233–12262, 2025

    work page 2025

  15. [15]

    Salman Ali and Faisal Anwer. A novel lightweight framework for se- cure and efficient iot communication using chaotic cryptography and adaptive steganography.IEEE Transactions on Dependable and Secure Computing, 2025

    work page 2025

  16. [16]

    Medical image com- pression and encryption using chaos based dna cryptography

    Prema T Akkasaligar and Sumangala Biradar. Medical image com- pression and encryption using chaos based dna cryptography. In2020 IEEE Bangalore humanitarian technology conference (B-HTC), pages 1–5. IEEE, 2020

    work page 2020

  17. [17]

    Bharti Ahuja and Rajesh Doriya. A novel hybrid compressive encryption cryptosystem based on block quarter compression via dct and fractional fourier transform with chaos.International Journal of Information Technology, 13(5):1837–1846, 2021

    work page 2021

  18. [18]

    Deyang Wu, Xinpeng Zhang, Jiayan Wang, Li Li, and Guorui Feng. Novel robust video watermarking scheme based on concentric ring subband and visual cryptography with piecewise linear chaotic mapping.IEEE Trans- actions on Circuits and Systems for Video Technology, 34(10):10281– 10298, 2024

    work page 2024

  19. [19]

    entropys based image encryption scheme to secure sensitive multimedia content in cloud storage.Expert Systems with Applications, 257:125050, 2024

    Talha Umar, Mohammad Nadeem, and Faisal Anwer. entropys based image encryption scheme to secure sensitive multimedia content in cloud storage.Expert Systems with Applications, 257:125050, 2024

    work page 2024

  20. [20]

    A lightweight encryption method for privacy protection in surveillance videos.IEEE Access, 6:18074–18087, 2018

    Xing Zhang, Seung-Hyun Seo, and Changda Wang. A lightweight encryption method for privacy protection in surveillance videos.IEEE Access, 6:18074–18087, 2018

    work page 2018

  21. [21]

    Simultaneous encryption and compression for securing large data transmission over a heteroge- neous network

    Shiladitya Bhattacharjee and Sulabh Bansal. Simultaneous encryption and compression for securing large data transmission over a heteroge- neous network. InApplied Intelligence in Human-Computer Interaction, pages 129–142. CRC Press, 2023

    work page 2023

  22. [22]

    An efficient commutative encryption and data hiding scheme for hevc video.IEEE Access, 8:60232–60245, 2020

    Bo Guan, Dawen Xu, and Qian Li. An efficient commutative encryption and data hiding scheme for hevc video.IEEE Access, 8:60232–60245, 2020

    work page 2020

  23. [23]

    An integrated technique to ensure confidentiality and integrity in data transmission through the strongest and authentic hotspot selection mechanism

    Shiladitya Bhattacharjee, Divya Midhun Chakkaravarthy, Midhun Chakkaravarthy, and Lukman Bin Ab Rahim. An integrated technique to ensure confidentiality and integrity in data transmission through the strongest and authentic hotspot selection mechanism. InData Manage- ment, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 36 2, pages 459–474. S...

    work page 2019

  24. [24]

    A modified image selective encryption- compression technique based on 3d chaotic maps and arithmetic coding

    Saad Mohamed Darwish. A modified image selective encryption- compression technique based on 3d chaotic maps and arithmetic coding. Multimedia Tools and Applications, 78(14):19229–19252, 2019

    work page 2019

  25. [25]

    Survey on image encryption techniques using chaotic maps in spatial, transform and spatiotemporal domains: U

    Unsub Zia, Mark McCartney, Bryan Scotney, Jorge Martinez, Mamun AbuTair, Jamshed Memon, and Ali Sajjad. Survey on image encryption techniques using chaotic maps in spatial, transform and spatiotemporal domains: U. zia et al.International Journal of Information Security, 21(4):917–935, 2022

    work page 2022

  26. [26]

    Joint video compression and encryption using arithmetic coding and chaos

    Amit Pande, Joseph Zambreno, and Prasant Mohapatra. Joint video compression and encryption using arithmetic coding and chaos. In 2010 IEEE 4th international conference on internet multimedia services architecture and application, pages 1–6. IEEE, 2010

    work page 2010

  27. [27]

    Robust video encryption for h

    Hui Xu, Xiaojun Tong, Zhu Wang, Miao Zhang, Yang Liu, and Jing Ma. Robust video encryption for h. 264 compressed bitstream based on cross-coupled chaotic cipher.Multimedia Systems, 26(4):363–381, 2020

    work page 2020

  28. [28]

    Sparse representation based compressive video encryption using hyper-chaos and dna coding.Digital Signal Processing, 117:103143, 2021

    Jayashree Karmakar, Arghya Pathak, Debashis Nandi, and Mrinal Kanti Mandal. Sparse representation based compressive video encryption using hyper-chaos and dna coding.Digital Signal Processing, 117:103143, 2021

    work page 2021

  29. [29]

    Image compression- encryption algorithm based on chaos and compressive sensing.Multime- dia Tools and Applications, 82(14):22189–22212, 2023

    Jiao Cai, Shucui Xie, and Jianzhong Zhang. Image compression- encryption algorithm based on chaos and compressive sensing.Multime- dia Tools and Applications, 82(14):22189–22212, 2023

    work page 2023

  30. [30]

    Chaos-based simultaneous compression and encryption for hadoop.PloS one, 12(1):e0168207, 2017

    Muhammad Usama and Nordin Zakaria. Chaos-based simultaneous compression and encryption for hadoop.PloS one, 12(1):e0168207, 2017

    work page 2017

  31. [31]

    Heterogeneous parallel computing based real-time chaotic video encryption and its application to drone-oriented secure communication

    Fan-feng Shi, Tao Li, Hao-yu Hu, Yi-fei Li, Dan Shan, and Dong Jiang. Heterogeneous parallel computing based real-time chaotic video encryption and its application to drone-oriented secure communication. Chaos, Solitons & Fractals, 181:114681, 2024

    work page 2024

  32. [32]

    Symmetric encryption algorithms using chaotic and non-chaotic genera- tors: A review.Journal of advanced research, 7(2):193–208, 2016

    Ahmed G Radwan, Sherif H AbdElHaleem, and Salwa K Abd-El-Hafiz. Symmetric encryption algorithms using chaotic and non-chaotic genera- tors: A review.Journal of advanced research, 7(2):193–208, 2016

    work page 2016

  33. [33]

    Commutative encryption and data hiding in hevc video compression.IEEE access, 7:66028–66041, 2019

    Dawen Xu. Commutative encryption and data hiding in hevc video compression.IEEE access, 7:66028–66041, 2019

    work page 2019

  34. [34]

    Shiping Zhu, Chang Liu, and Ziyao Xu. High-definition video com- pression system based on perception guidance of salient information of a convolutional neural network and hevc compression domain.IEEE Transactions on Circuits and Systems for Video Technology, 30(7):1946– 1959, 2019

    work page 1946

  35. [35]

    Novel chroma sampling methods for cfa video compression in avc, hevc and vvc.IEEE Transactions on Circuits and Systems for Video Technology, 30(9):3167–3180, 2019

    Ting-Lan Lin, Yi-Chieh Yu, Kun-Hu Jiang, Chi-Fu Liang, and Pei-Sin Liaw. Novel chroma sampling methods for cfa video compression in avc, hevc and vvc.IEEE Transactions on Circuits and Systems for Video Technology, 30(9):3167–3180, 2019

    work page 2019

  36. [36]

    Compcrypt–lightweight 37 ans-based compression and encryption.IEEE Transactions on Informa- tion Forensics and Security, 16:3859–3873, 2021

    Seyit Camtepe, Jarek Duda, Arash Mahboubi, Pawe l Morawiecki, Surya Nepal, Marcin Paw lowski, and Josef Pieprzyk. Compcrypt–lightweight 37 ans-based compression and encryption.IEEE Transactions on Informa- tion Forensics and Security, 16:3859–3873, 2021

    work page 2021

  37. [37]

    Xiuli Chai, Xianglong Fu, Zhihua Gan, Yushu Zhang, Yang Lu, and Yiran Chen. An efficient chaos-based image compression and encryp- tion scheme using block compressive sensing and elementary cellular automata.Neural Computing and Applications, 32(9):4961–4988, 2020

    work page 2020

  38. [38]

    Optimizing semantic- aware video compression using particle swarm optimization technique for automotive applications.IEEE Access, 2025

    Vadivel Shanmugam and B Uma Maheswari. Optimizing semantic- aware video compression using particle swarm optimization technique for automotive applications.IEEE Access, 2025

    work page 2025

  39. [39]

    A novel chaotic map and its application to secure transmission of multimodal images.IEEE Trans- actions on Computational Social Systems, 2025

    Parkala Vishnu Bharadwaj Bayari, Yashmita Sangwan, Gaurav Bhat- nagar, and Chiranjoy Chattopadhyay. A novel chaotic map and its application to secure transmission of multimodal images.IEEE Trans- actions on Computational Social Systems, 2025

    work page 2025

  40. [40]

    End-to-end neural video compression: A review.IEEE Open Journal of Circuits and Systems, 2025

    Jiovana S Gomes, Mateus Grellert, F´ abio LL Ramos, and Sergio Bampi. End-to-end neural video compression: A review.IEEE Open Journal of Circuits and Systems, 2025

    work page 2025

  41. [41]

    Yu Liu, Chun Luo, Wanglong Wan, Wenqiang Jin, and Zheng Qin. A secure medical image encryption scheme based on cross-ring josephus scrambling and two-dimensional cellular automata.IEEE Transactions on Circuits and Systems for Video Technology, 2025

    work page 2025

  42. [42]

    Quantum-inspired hyperchaotic bio-dna image encryption for real time medical security.IEEE Access, 2025

    Harshit Sharma and Simran Kaur. Quantum-inspired hyperchaotic bio-dna image encryption for real time medical security.IEEE Access, 2025

    work page 2025

  43. [43]

    Joint video compression and encryption using parallel compressive sensing and improved chaotic maps.Digital Signal Processing, 130:103746, 2022

    Jagannath Sethi, Jaydeb Bhaumik, and Ananda S Chowdhury. Joint video compression and encryption using parallel compressive sensing and improved chaotic maps.Digital Signal Processing, 130:103746, 2022

    work page 2022

  44. [44]

    Multi-view light field images compression and encryption using enhanced 3d chaotic system and pixel-bit-scrambling.IEEE Access, 12:156471–156491, 2024

    Jianrui Shao, Enjian Bai, Xueqin Jiang, and Yun Wu. Multi-view light field images compression and encryption using enhanced 3d chaotic system and pixel-bit-scrambling.IEEE Access, 12:156471–156491, 2024

    work page 2024

  45. [45]

    A systematic literature review on chaotic maps- based image security techniques.Computer Science Review, 54:100659, 2024

    Dilbag Singh, Sharanpreet Kaur, Mandeep Kaur, Surender Singh, Manjit Kaur, and Heung-No Lee. A systematic literature review on chaotic maps- based image security techniques.Computer Science Review, 54:100659, 2024

    work page 2024

  46. [46]

    Encryption for high efficiency video coding with video adaptation capabilities.IEEE Transactions on Consumer Electronics, 59(3):634–642, 2013

    Glenn Van Wallendael, Andras Boho, Jan De Cock, Adrian Munteanu, and Rik Van de Walle. Encryption for high efficiency video coding with video adaptation capabilities.IEEE Transactions on Consumer Electronics, 59(3):634–642, 2013

    work page 2013

  47. [47]

    Beta and logistic function driven encryption for compressed images

    Sharad Salunke, M Venkatadri, and Md Farukh Hashmi. Beta and logistic function driven encryption for compressed images. In2021 Sixth International Conference on Image Information Processing (ICIIP), volume 6, pages 13–18. IEEE, 2021

    work page 2021

  48. [48]

    Analysis of linear feedback shift registers and chaos- based techniques for image encryption.Journal of Cyber Security Tech- nology, 9(2):79–87, 2025

    Daniel Okunbor. Analysis of linear feedback shift registers and chaos- based techniques for image encryption.Journal of Cyber Security Tech- nology, 9(2):79–87, 2025. 38

    work page 2025

  49. [49]

    A visual security multi-key selection image encryption algorithm based on a new four-dimensional chaos and compressed sensing.Scientific Reports, 14(1):15496, 2024

    Shuqin Zhu and Congxu Zhu. A visual security multi-key selection image encryption algorithm based on a new four-dimensional chaos and compressed sensing.Scientific Reports, 14(1):15496, 2024

    work page 2024

  50. [50]

    An enhanced hybrid chaotic system and its application in image encryption.Journal of King Saud University Computer and Information Sciences, 37(9):295, 2025

    Junxia Gao, Yulin Shen, Shouliang Li, and Jilong Zhang. An enhanced hybrid chaotic system and its application in image encryption.Journal of King Saud University Computer and Information Sciences, 37(9):295, 2025

    work page 2025

  51. [51]

    Enhancing image security with a novel chaotic system: A focus on multi-face image encryption in smart applications.IEEE Internet of Things Journal, 2025

    Pengbo Liu, Lin Teng, Huipeng Liu, Herbert Ho-Ching Iu, Mingxu Wang, Xiaopeng Yan, and Xianping Fu. Enhancing image security with a novel chaotic system: A focus on multi-face image encryption in smart applications.IEEE Internet of Things Journal, 2025

    work page 2025

  52. [52]

    Error transmission of chaos-based image encryption: Application to smart grid.IEEE Transactions on Industrial Informatics, 2025

    Haoyu Li, Leimin Wang, Xiongbo Wan, and Chuan-Ke Zhang. Error transmission of chaos-based image encryption: Application to smart grid.IEEE Transactions on Industrial Informatics, 2025

    work page 2025

  53. [53]

    Comprehensive review and analysis of image encryption techniques.IEEE Access, 2025

    K Mahalakshmi and Sivakumar Nagarajan. Comprehensive review and analysis of image encryption techniques.IEEE Access, 2025

    work page 2025

  54. [54]

    A study on seismic big data handling at seismic exploration industry

    Shiladitya Bhattacharjee, Lukman Bin Ab Rahim, Ade Wahyu Ramad- hani, Midhunchakkaravarthy, and Divya Midhunchakkravarthy. A study on seismic big data handling at seismic exploration industry. InIn- telligent Computing and Innovation on Data Science: Proceedings of ICTIDS 2019, pages 421–429. Springer, 2021

    work page 2019

  55. [55]

    Adaptive video encoding for different video codecs.IEEE Access, 9:68720–68736, 2021

    Gangadharan Esakki, Andreas S Panayides, V Jalta, and Marios S Pattichis. Adaptive video encoding for different video codecs.IEEE Access, 9:68720–68736, 2021

    work page 2021

  56. [56]

    On the security of selectively encrypted hevc video bitstreams.ACM Transactions on Multimedia Computing, Communications and Applications, 20(9):1–27, 2025

    Chen Chen, Lingfeng Qu, Hadi Amirpour, Xingjun Wang, Christian Timmerer, and Zhihong Tian. On the security of selectively encrypted hevc video bitstreams.ACM Transactions on Multimedia Computing, Communications and Applications, 20(9):1–27, 2025

    work page 2025

  57. [57]

    Start code-based encryption and decryption framework for hevc.IEEE Access, 8:202910–202918, 2020

    Min Ku Lee and Euee Seon Jang. Start code-based encryption and decryption framework for hevc.IEEE Access, 8:202910–202918, 2020

    work page 2020

  58. [58]

    Chaos-based block permutation and dynamic sequence multiplexing for video encryption

    Heping Wen, Yiting Lin, Zhiyu Xie, and Tengyu Liu. Chaos-based block permutation and dynamic sequence multiplexing for video encryption. Scientific Reports, 13(1):14721, 2023

    work page 2023

  59. [59]

    Wiley Online Library, 1988

    Heinz Georg Schuster and Wolfram Just.Deterministic chaos: an introduction, volume 2. Wiley Online Library, 1988

    work page 1988

  60. [60]

    A novel cosine-cosine chaotic map-based video encryption scheme.Journal of Engineering and Applied Science, 71(1):36, 2024

    Sweta Kumari, Mohit Dua, Shelza Dua, and Deepti Dhingra. A novel cosine-cosine chaotic map-based video encryption scheme.Journal of Engineering and Applied Science, 71(1):36, 2024

    work page 2024

  61. [61]

    Review of chaos detection techniques performed on chaotic maps and systems in image encryption.SN Computer Science, 2(5):392, 2021

    Joan S Muthu and P Murali. Review of chaos detection techniques performed on chaotic maps and systems in image encryption.SN Computer Science, 2(5):392, 2021

    work page 2021

  62. [62]

    Fast colored video encryption using block scrambling and multi-key generation.The Visual Computer, 39(12):6041–6072, 2023

    Khalid M Hosny, Mohamed A Zaki, Nabil A Lashin, and Hanaa M Hamza. Fast colored video encryption using block scrambling and multi-key generation.The Visual Computer, 39(12):6041–6072, 2023. 39

    work page 2023

  63. [63]

    A new compression method using a chaotic symbolic approach

    Mihai Bogdan Luca, Alexandru Serbanescu, St´ ephane Azou, and Gilles Burel. A new compression method using a chaotic symbolic approach. InIEEE Communications, 2004

    work page 2004

  64. [64]

    An image encryption approach based on chaotic maps.Chaos, Solitons & Fractals, 24(3):759– 765, 2005

    Linhua Zhang, Xiaofeng Liao, and Xuebing Wang. An image encryption approach based on chaotic maps.Chaos, Solitons & Fractals, 24(3):759– 765, 2005

    work page 2005

  65. [65]

    Joint compression and encryption using chaotically mutated huffman trees.Communications in nonlinear science and numerical simulation, 15(10):2987–2999, 2010

    Houcemeddine Hermassi, Rhouma Rhouma, and Safya Belghith. Joint compression and encryption using chaotically mutated huffman trees.Communications in nonlinear science and numerical simulation, 15(10):2987–2999, 2010

    work page 2010

  66. [66]

    An efficient secure data compression technique based on chaos and adaptive huffman coding.Peer-to-Peer Networking and Applications, 14(5):2651–2664, 2021

    Muhammad Usama, Qutaibah M Malluhi, Nordin Zakaria, Imran Raz- zak, and Waheed Iqbal. An efficient secure data compression technique based on chaos and adaptive huffman coding.Peer-to-Peer Networking and Applications, 14(5):2651–2664, 2021

    work page 2021

  67. [67]

    Mulvis: Multi-level encryption based security system for surveillance videos.Ieee Access, 8:177131–177155, 2020

    Amna Shifa, Mamoona N Asghar, Martin Fleury, Nadia Kanwal, Mo- hammad S Ansari, Brian Lee, Marco Herbst, and Yuansong Qiao. Mulvis: Multi-level encryption based security system for surveillance videos.Ieee Access, 8:177131–177155, 2020

    work page 2020

  68. [68]

    An image encryption scheme using present-rc4, chaos and secure key gener- ation.Scientific Reports, 15(1):42775, 2025

    Krishna Kumar, Satyabrata Roy, Dev Puri, and Ravinder Kumar. An image encryption scheme using present-rc4, chaos and secure key gener- ation.Scientific Reports, 15(1):42775, 2025

    work page 2025

  69. [69]

    Even symmetric chaotic and skewed maps as a technique in video encryption

    Bassant Mohey El-den, Walid A Raslan, and Ahmed A Abdullah. Even symmetric chaotic and skewed maps as a technique in video encryption. EURASIP Journal on Advances in Signal Processing, 2023(1):40, 2023

    work page 2023

  70. [70]

    A new chaotic complex map for robust video watermarking.Artificial Intelligence Review, 54(2):1237–1280, 2021

    Peyman Ayubi, Milad Jafari Barani, Milad Yousefi Valandar, Behzad Yosefnezhad Irani, and Reza Sedagheh Maskan Sadigh. A new chaotic complex map for robust video watermarking.Artificial Intelligence Review, 54(2):1237–1280, 2021

    work page 2021

  71. [71]

    A compressed image encryption algorithm leveraging optimized 3d chaotic maps for secure image communication.Scientific Reports, 15(1):14151, 2025

    Akshat Tiwari, Prachi Diwan, Tarun Dhar Diwan, Mahdal Miroslav, and SP Samal. A compressed image encryption algorithm leveraging optimized 3d chaotic maps for secure image communication.Scientific Reports, 15(1):14151, 2025

    work page 2025

  72. [72]

    Wanru Lu, Chunhua Jin, Jiahao Wang, Xinying Liu, Junyi Liu, and Zhonghao Zhai. A novel image encryption scheme using 3d chaotic maps with josephus permutation and dynamic diffusion.Journal of King Saud University Computer and Information Sciences, 37(8):254, 2025

    work page 2025

  73. [73]

    Optical video encryption using iterative phase retrieval and multimodal chaotic maps.Optics Communications, page 132960, 2026

    Gaurav Verma and Wenqi He. Optical video encryption using iterative phase retrieval and multimodal chaotic maps.Optics Communications, page 132960, 2026

    work page 2026

  74. [74]

    A fast multi-image encryption scheme using hyperchaotic map and parallel algorithm for vehicle detection applications.IEEE Internet of Things Journal, 2026

    Qiang Lai and Baowen Miao. A fast multi-image encryption scheme using hyperchaotic map and parallel algorithm for vehicle detection applications.IEEE Internet of Things Journal, 2026

    work page 2026

  75. [75]

    4d chaotic system-based secure data hiding method to improve robustness and embedding capacity of videos.Journal of Information Security and 40 Applications, 71:103369, 2022

    Sezgin Ka¸ car, Mehmet Zeki Konyar, and¨Unal C ¸avu¸ so˘ glu. 4d chaotic system-based secure data hiding method to improve robustness and embedding capacity of videos.Journal of Information Security and 40 Applications, 71:103369, 2022

    work page 2022

  76. [76]

    Bi-fidelity adaptive sparse reconstruction of polynomial chaos using bayesian compressive sensing.Engineering with Computers, 41(4):2461– 2481, 2025

    Mohamad Sadeq Karimi, Ramin Mohammadi, and Mehrdad Raisee. Bi-fidelity adaptive sparse reconstruction of polynomial chaos using bayesian compressive sensing.Engineering with Computers, 41(4):2461– 2481, 2025

    work page 2025

  77. [77]

    Chaos-based video encryption techniques: A review.Computer Science Review, 58:100816, 2025

    Suo Gao, Rui Wu, Herbert Ho-Ching Iu, Ugur Erkan, Yinghong Cao, Qi Li, Abdurrahim Toktas, and Jun Mou. Chaos-based video encryption techniques: A review.Computer Science Review, 58:100816, 2025

    work page 2025

  78. [78]

    Anna Guo, Chengbin Xu, and Chunlei Fan. A novel conservative vortex- like chaotic system with tunable parameters and its application in audio encryption.Journal of King Saud University Computer and Information Sciences, 37(9):287, 2025

    work page 2025

  79. [79]

    Design and analysis of parameter-controlled multiscroll memristive chaotic system with application to secure communication.IEEE Internet of Things Journal, 2026

    Qiang Lai, Daxun Huang, Xiaoyue Chen, and Xiang Sun. Design and analysis of parameter-controlled multiscroll memristive chaotic system with application to secure communication.IEEE Internet of Things Journal, 2026

    work page 2026

  80. [80]

    A survey on security challenges in cloud computing: issues, threats, and solutions.The journal of supercomputing, 76(12):9493–9532, 2020

    Hamed Tabrizchi and Marjan Kuchaki Rafsanjani. A survey on security challenges in cloud computing: issues, threats, and solutions.The journal of supercomputing, 76(12):9493–9532, 2020

    work page 2020

Showing first 80 references.