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Paper Citation Record · LEDGER

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation

As of 17 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2509.08449.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.08449 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:13:03.364743Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

  • verified exact4
  • verified fuzzy30
  • unresolved20
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1f3cca0-df82-4612-9c7a-627296a61ec3 · outbound

This paper cites Resolution on generative artificial intelligence systems,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Resolution on generative artificial intelligence systems,

Reference 1

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raw_fallback, observed 2026-08-15T16:13:04.513872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.032685Z digest=sha256:f28c8033f41f13667ae1ec30923db07a7373d8772882104ae07baed128af2924

Observation feba1996-7d03-4cfc-8daf-488f4745a411 · outbound

This paper cites Domain adaptation: Challenges, methods, datasets, and applications,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Domain adaptation: Challenges, methods, datasets, and applications,

Reference 2

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raw_fallback, observed 2026-08-15T16:13:04.494039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.045805Z digest=sha256:0ff9f0d33489f82b5db5b385c8f9e095d0a800dbcd919c22a4986ff5c178dea9

Observation e5d63847-7aa8-4396-9230-b2dd9ebafebf · outbound

This paper cites The challenges of data quality and data quality assessment in the big data era,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation The challenges of data quality and data quality assessment in the big data era,

Reference 3

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raw_fallback, observed 2026-08-15T16:13:04.477915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.056044Z digest=sha256:0d40501c13f307ffd14f8727abdefe4e31d8ab43edfccff2e030cc224bae7ce6

Observation 772b2ffd-95ec-48cb-8321-f6666abd61f4 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 4

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no resolver link, observed 2026-08-15T16:13:03.064550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.064550Z digest=sha256:4164ddd2b2f3aee23668c37a323b0af42ee1851e6b8529c3c0a2920e16bc4e9b

Observation 155b501c-4a7a-44ce-9aa3-c87fe7ca0560 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated Learning: Strategies for Improving Communication Efficiency

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.080353Z digest=sha256:c89ded552d7338378742e07c70e19ba944331186b72e555d2815469cfec96a26

Observation ff451a95-f1e3-4da7-8dae-5da4b1e99447 · outbound

This paper cites A review on traditional machine learning and deep learning models for wbcs classification in blood smear images,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A review on traditional machine learning and deep learning models for wbcs classification in blood smear images,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.460570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.085910Z digest=sha256:cb01a177fd6217b8297b8088b9ee59971c43087070912c69b19438df533d894e

Observation b5f5e30e-de6f-4865-afa0-514458971511 · outbound

This paper cites Federated vs. centralized machine learning under privacy-elastic users: A comparative analysis,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated vs. centralized machine learning under privacy-elastic users: A comparative analysis,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.092103Z digest=sha256:a284963c6e7364de296ef87d57fb6067cb18bcd99ad00f12cbf7544cccc8f2b4

Observation c1e1db95-8872-4dd0-bb42-6b927cce3a85 · outbound

This paper cites A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.097896Z digest=sha256:c6c3159cde9744ee04476e5e91834af8c3b01440e2314710631d1d869edf518a

Observation cf95aafb-33ec-4fe5-9eca-7b25380536c2 · outbound

This paper cites Federated benchmarking of medical artificial intelligence with medperf,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated benchmarking of medical artificial intelligence with medperf,

Reference 9

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no resolver link, observed 2026-08-15T16:13:03.103313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.103313Z digest=sha256:d72fc2e42e5554b0c6568f6d3cf7070e363083f94e55d51b02d4edc27c50ac44

Observation 14e9129c-d3df-46cb-afc8-fa3656457580 · outbound

This paper cites Feder- ated learning in autonomous vehicles using cross- border training,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Feder- ated learning in autonomous vehicles using cross- border training,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.109670Z digest=sha256:86c32db22f4652d082ff0e3921f79e942bb909ddd035933dfa44a080d088c9c0

Observation f38a0d9c-5d08-4526-aa48-92e60d9ef545 · outbound

This paper cites Securing secure aggregation: mitigating multi-round privacy leakage in federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Securing secure aggregation: mitigating multi-round privacy leakage in federated learning,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.115035Z digest=sha256:0fae1ac9b5e59fe255b776fc11e18d3445d583df0d49ffa30443bec3f16656d7

Observation e30e99f0-46e1-4ef5-acb8-1278c525ba99 · outbound

This paper cites Exploiting Unintended Feature Leakage in Collaborative Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Exploiting Unintended Feature Leakage in Collaborative Learning

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.120792Z digest=sha256:3d758b0f8f3c7e53d6a6485f938a4a5d9a3479207e8f3229eb3c9bd1f7fd3a91

Observation 23c01f31-b798-4cb7-9aef-f33d58b5f7d8 · outbound

This paper cites A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions,

Reference 13

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raw_fallback, observed 2026-08-15T16:13:04.384928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.129359Z digest=sha256:6fbed3f94fa9765ddd09dd3d7fc29698e4f6a57929216f07cd89d51b985db49b

Observation 9868d32a-2f64-4d47-9138-2d9f5200cb0b · outbound

This paper cites How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?

Reference 14

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source=pdf_text observed=2026-08-15T16:13:03.139836Z digest=sha256:5d3853115500b7a018dfbea434ff41fa15794c271e13033571b63bb4e303c0da

Observation 524b6a61-ed4b-44db-8cc4-20dd8003ad39 · outbound

This paper cites Federated learning minimal model replacement attack using optimal transport: An attacker perspective,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated learning minimal model replacement attack using optimal transport: An attacker perspective,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.145429Z digest=sha256:02b5ae624464ed3a089e172d99ee966535685ab8693a097160be40c4f5f8039a

Observation 6e4ad31a-d509-4e3d-be19-301bef8d193c · outbound

This paper cites How To Backdoor Federated Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation How To Backdoor Federated Learning

Reference 16

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source=pdf_text observed=2026-08-15T16:13:03.150497Z digest=sha256:693c83d99c7798acb4f93c4190b3579813234606237468d34ce473952aa77eb7

Observation a062cad9-8b5c-41ed-8aac-8cdeaa316778 · outbound

This paper cites Analyzing federated learning through an adversarial lens,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Analyzing federated learning through an adversarial lens,

Reference 17

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raw_fallback, observed 2026-08-15T16:13:04.347045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.157760Z digest=sha256:388d39f0a41db82ea04d793cca1bc27be795fb7b3c51e5224a93ddfe38ead2ff

Observation 0c6891a6-672b-4fb5-a7b6-6ca8c5ad2b27 · outbound

This paper cites Dual Model Replacement:invisible Multi-target Backdoor Attack based on Federal Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Dual Model Replacement:invisible Multi-target Backdoor Attack based on Federal Learning

Reference 18

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source=pdf_text observed=2026-08-15T16:13:03.162308Z digest=sha256:86ed7fb1d15381537e2f9c6a17bd49d0cdf54948c3381dac5efc0014ec0b0398

Observation 6e2fabbe-7a43-421f-ac62-793dc3098327 · outbound

This paper cites Dba: Distributed backdoor attacks against federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Dba: Distributed backdoor attacks against federated learning,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.168534Z digest=sha256:7a8b61cf7dea235d4c59b567c4553d1f7928c62f6a46172391ef5aa30218bf83

Observation b80eac43-57a8-48bf-87a0-9ce30ef92c5f · outbound

This paper cites Local model poisoning attacks to Byzantine-Robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Local model poisoning attacks to Byzantine-Robust federated learning,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.173925Z digest=sha256:9644f83b7f4ac06b82ec43ed1e462abdaa484fe108b1eba54926a96944687ea6

Observation a178e583-73fd-4f2c-b21b-11620640a8b9 · outbound

This paper cites A gan- based data poisoning attack against federated learning systems and its countermeasure,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A gan- based data poisoning attack against federated learning systems and its countermeasure,

Reference 21

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source=pdf_text observed=2026-08-15T16:13:03.184725Z digest=sha256:adc19443a51bf585ac2b76f13ab5bc58bb805be32ea143ad29659b277c7302e6

Observation edb434fb-bb20-4dfe-884a-54b3812c3449 · outbound

This paper cites Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Reference 22

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local_arxiv, observed 2026-08-15T16:13:03.854923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.190704Z digest=sha256:2486810268bbbeacc2fd8ece994ac3294c9ebb9d5280798c3f63632dcea66028

Observation 05e0b10d-586c-4145-bdc1-6d2a6c7ad8be · outbound

This paper cites Exploiting defenses against gan-based feature inference attacks in federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Exploiting defenses against gan-based feature inference attacks in federated learning,

Reference 23

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doi, observed 2026-08-15T16:13:03.452949Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.195769Z digest=sha256:c70d0e742603b4e100a88325ec79278ae4f5ef1455c350644dd91f7dce8cb78a

Observation 8c911b94-3d48-456d-b734-e0e87d18057b · outbound

This paper cites Localmodelpoisoning attacks to byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Localmodelpoisoning attacks to byzantine-robust federated learning,

Reference 24

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raw_fallback, observed 2026-08-15T16:13:04.289085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.201336Z digest=sha256:c1dc318b3140343be90c6a45962f1737eda54879ab58ece0991959b15fe68d28

Observation 0f26761b-6917-4cce-a586-26f48c4123e8 · outbound

This paper cites Data Poisoning Attacks Against Federated Learning Systems.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Data Poisoning Attacks Against Federated Learning Systems

Reference 25

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source=pdf_text observed=2026-08-15T16:13:03.206351Z digest=sha256:06d6b92e27583d8e8a92c304d2d363c1b4d3dd7ab042cb7055151da6ca24f828

Observation 224c9607-ea27-4cf2-ae66-ae474b48c14c · outbound

This paper cites Manipulating machine learning: Poisoning attacks and countermeasures for regression learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Manipulating machine learning: Poisoning attacks and countermeasures for regression learning,

Reference 26

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raw_fallback, observed 2026-08-15T16:13:04.273808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.212012Z digest=sha256:ead89ef2be294b3437d9e2b162849b85741ea171268430190c3de23a2dd7d919

Observation 1ceef9b5-31d5-407c-ae7f-496cca465903 · outbound

This paper cites Machine learning with adversaries: Byzantine tolerant gradient descent,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Machine learning with adversaries: Byzantine tolerant gradient descent,

Reference 27

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raw_fallback, observed 2026-08-15T16:13:04.256030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.216313Z digest=sha256:1018ed631414e61c94795448daa554530ed1694db057910a8d2df5c687e803cb

Observation fdf4ec20-a2c2-4578-aafa-3d7118c6a711 · outbound

This paper cites The hidden vulnerability of distributed learning in byzantium,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation The hidden vulnerability of distributed learning in byzantium,

Reference 28

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raw_fallback, observed 2026-08-15T16:13:04.241075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.222969Z digest=sha256:5b6715c6cdccacb71dcb0cc2f0dc1ba6b4ee9678e814129e1c90dc4115652cdc

Observation 28ec73ce-7cbf-4e5e-ac02-23025f785766 · outbound

This paper cites Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 30

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T16:13:03.233359Z digest=sha256:5df84232cfd1352a407bca17127fe6d43967f743b7512d7bb2f4e6188d702bf5

Observation d9e1742c-b303-449a-b65d-15bcbef005e2 · outbound

This paper cites Practical secure aggregation for privacy-preserving machine learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Practical secure aggregation for privacy-preserving machine learning,

Reference 31

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source=pdf_text observed=2026-08-15T16:13:03.238256Z digest=sha256:c55cbfa243f7740b54a60ed27262a6238b56f684a3a8b908ebdc7a98de6c3024

Observation c6cf9ca1-accf-4ba0-b7d5-52c50c04300c · outbound

This paper cites Privacy-preserving deep learning via additively homomorphic encryption,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy-preserving deep learning via additively homomorphic encryption,

Reference 32

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T16:13:03.242697Z digest=sha256:34f1ce7d16b05f20f0ffaa2675025f7214e5731b8b389d31b5325844541ec57f

Observation 3a10635c-11a2-4d52-8585-a6ecf5fd07d5 · outbound

This paper cites Homomorphic encryption for arithmetic of approximate numbers,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Homomorphic encryption for arithmetic of approximate numbers,

Reference 33

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T16:13:03.248119Z digest=sha256:52021ac7806347b9709e84ac0caf30e043fe2874fe3fc8198295743c49980941

Observation 0c2bbe87-d381-45b3-a8ae-44a0178c7d8a · outbound

This paper cites Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.216023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.255225Z digest=sha256:ae633a0e29f56831bd2a23e8ef226ef05f9a89f35aed1f93c3195628e593cf66

Observation 14ca0219-e515-4c31-bbea-149e1e0c404a · outbound

This paper cites Lsfl: A lightweight and secure federated learning scheme for edge computing,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Lsfl: A lightweight and secure federated learning scheme for edge computing,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.202108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.259854Z digest=sha256:0415fe119e138f5b9158b92a6f3f459e007058e84337ead8bee9762b7d0e177d

Observation 9b4122ee-e596-4ef5-9d56-f6f6ff072238 · outbound

This paper cites FLOD: Oblivious defender for private byzantine-robust federated learning with dishonest-majority,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation FLOD: Oblivious defender for private byzantine-robust federated learning with dishonest-majority,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.188602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.264792Z digest=sha256:10dbcb8b46e0b63bad509786cfde4908a6af37e5cde2c3d6674e81e734ddf226

Observation 1fb81c51-47de-4a06-854b-5ce9c2eb352f · outbound

This paper cites Differentially private byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Differentially private byzantine-robust federated learning,

Reference 37

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unresolved
no resolver link, observed 2026-08-15T16:13:03.269804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.269804Z digest=sha256:898968c3a34f7ce3715f8b884048d69020d2d43cae8bbdfc5550e8deb703ca07

Observation be2ae0b7-464b-4e62-a931-492936dc95ed · outbound

This paper cites ELSA: secure aggregation for federated learning with malicious actors,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation ELSA: secure aggregation for federated learning with malicious actors,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.171284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.275209Z digest=sha256:0571613df767bf353a49117104799cf48ad9d50755d85dde6c94742d52dd040d

Observation 44596d24-6935-43be-8b63-7c71598fafc7 · outbound

This paper cites Byzantine-Tolerant Machine Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Tolerant Machine Learning

Reference 39

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unresolved
no resolver link, observed 2026-08-15T16:13:03.279569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.279569Z digest=sha256:947da43bb0544cc803d436bd5916e2c9c763e749da6d3d2581eaba9d01cf9a81

Observation 79fe45ac-5e59-4031-801d-665f57eadc9e · outbound

This paper cites Batchcrypt: efficient homomorphic encryption for cross-silo federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Batchcrypt: efficient homomorphic encryption for cross-silo federated learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.155852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.284470Z digest=sha256:5dd994219559e8311618d06cd6e58f7f91fa186bff4302a63d32e2b02040d0e7

Observation 582722e1-93f8-4c59-be3c-39ed52eddbe2 · outbound

This paper cites Verifynet: Secure and verifiable federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Verifynet: Secure and verifiable federated learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.138216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.289400Z digest=sha256:99e4b4ea376fabd799f4ded2e07376d479d7f7fc317b08f7ada469e246f0a921

Observation 8d382a30-9796-4d4f-84a5-1115e89c43ad · outbound

This paper cites Sear: Secure and efficient aggregation for byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Sear: Secure and efficient aggregation for byzantine-robust federated learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.119894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.293830Z digest=sha256:ca19e4e0388cb7a8835b281be7781209693da39be85f2dafaf65ae45f4476cb4

Observation da3947c3-a54e-4fc1-b146-7f57a6e7e12d · outbound

This paper cites Pvd-fl: A privacy-preserving and verifiable decentralized federated learn- ing framework,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Pvd-fl: A privacy-preserving and verifiable decentralized federated learn- ing framework,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.102138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.298401Z digest=sha256:16d6dfcf1540e9f7c3e49b1f8b898fb7dd4bb1c408b8b1c88b2b9a5d52d550ca

Observation a17c0b48-59d7-49af-aee4-c564db33ae11 · outbound

This paper cites A Secure and Efficient Federated Learning Framework for NLP.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A Secure and Efficient Federated Learning Framework for NLP

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T16:13:03.302442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.302442Z digest=sha256:1642de06796f2b7d949b826ecdbb514c35ac70056cf933582ecfc0e19d180362

Observation 78dd327e-c025-4abf-a2cb-cca5f6de353e · outbound

This paper cites Prio+: Privacy preserving aggregate statistics,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Prio+: Privacy preserving aggregate statistics,

Reference 45

Resolution
verified exact
doi, observed 2026-08-15T16:13:03.414483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.307059Z digest=sha256:84cc0e860c563854c831229d7824443ff1c85f801db75487ef45694fe2ed1922

Observation 91cebfd1-5696-44eb-967a-f30c40c5ed01 · outbound

This paper cites Secure Byzantine-Robust Machine Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Secure Byzantine-Robust Machine Learning

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:13:03.612389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.311514Z digest=sha256:b9246e087e79bdc9c988b0647ff631df58a98740dd31e0fc314184ae1d9505aa

Observation bef10875-d850-4915-8853-684541bd2afb · outbound

This paper cites Privacy- enhanced federated learning against poisoning adversaries,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy- enhanced federated learning against poisoning adversaries,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.086884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.317262Z digest=sha256:6732e1258c0d016f54db536b5047821e49c82981c847ff8a3b1e37673e5dfaae

Observation f4b1e374-886a-4d9e-8677-1b3c2a32bdf3 · outbound

This paper cites A differentially private federated learning model against poisoning attacks in edge computing,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A differentially private federated learning model against poisoning attacks in edge computing,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.072665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.321543Z digest=sha256:b5e4b4b820b637beb6f481326595a2cbdfcfca17bfbf838df7e583e09ddeacb3

Observation 8d1a3cb4-b5dd-427b-b893-ead9ee84b133 · outbound

This paper cites Privacy-preserving and byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy-preserving and byzantine-robust federated learning,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.057223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.326603Z digest=sha256:1490521efb6c52fafae0337e742d6ec0bdbaa64a16434c4b404cf5fd5aabd116

Observation 3eef01fa-94ad-4fb7-a755-96c1bfd5d4d5 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 50

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unresolved
no resolver link, observed 2026-08-15T16:13:03.332580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.332580Z digest=sha256:889e962ce4089a63aa1e864a69e8b420743b82a7a89b703cec9b6b5055cb4935

Observation dd8d7893-4477-4785-a586-9600eb2cad1d · outbound

This paper cites Accurate diabetes risk stratification using machine learning: Role of missing value and outliers.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Accurate diabetes risk stratification using machine learning: Role of missing value and outliers

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.039924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.338137Z digest=sha256:fc80fd98c3a1299ac5413c105559f70c830e270b33fe9c3db1b8426fe9310081

Observation 08b2d566-9178-478b-81f6-400021e60f0e · outbound

This paper cites Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Reference 52

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unresolved
no resolver link, observed 2026-08-15T16:13:03.344172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.344172Z digest=sha256:76a4474f34eedbb3e4ee025aea07e060d9654e975b8fb6108abb7cc8de4ec0f3

Observation e38a652a-f218-4b2c-8f77-237241a56772 · outbound

This paper cites Federated learning with differential privacy: Algorithms and performance analysis,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated learning with differential privacy: Algorithms and performance analysis,

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T16:13:03.348973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.348973Z digest=sha256:244444426d527a12d8bd80ea27995c4fdbc1f21244e296e43d21eab9749209cb

Observation 344b022f-9570-4ac2-a898-d7836829bd98 · outbound

This paper cites Local SGD converges fast and communicates little,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Local SGD converges fast and communicates little,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.023373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.364743Z digest=sha256:04e9633641d3b9b65e9306985dcc2d78e645385cdc739f0cd39e0e4404a683cd

Observation 31682073-9a24-4004-a907-1fdd268a1ba8 · outbound

This paper cites Available:https://www.usenix.org/conference/ usenixsecurity20/presentation/fang.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Available:https://www.usenix.org/conference/ usenixsecurity20/presentation/fang

Reference 1622

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:13:04.301664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T16:13:03.179574Z digest=sha256:fc39a0b3e4353baf414bc4ca767d3703bd0e3c19cd34f43899df9ec3cd05d234

Observation 6e5910f5-0d55-4cbc-a759-57ec0d9ff0b7 · outbound

This paper cites SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-15T16:13:03.360478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.360478Z digest=sha256:8812c379dec63b7b4809f4c25bed31aa56d6ff4ce48d34d0eab5ae258e134090

Pith citing papers

No inbound Pith citation observations are available.