Temporal Analysis of Adversarial Attacks in Federated Learning | Paper Citation Record

Observation 70912f07-897f-4ad9-baf2-89ded7c573ba · outbound

This paper cites Kulkarni, and H.

Temporal Analysis of Adversarial Attacks in Federated Learning Kulkarni, and H

Reference 1

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Observation 4873f4f4-f4b5-42ce-b15c-beaa2b6f53b5 · outbound

This paper cites Towards effective device-aware federated learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Towards effective device-aware federated learning

Reference 2

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Observation d948563f-3c6d-4bd8-9537-c684208d1481 · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

Temporal Analysis of Adversarial Attacks in Federated Learning Flower: A Friendly Federated Learning Research Framework

Reference 3

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Observation baa4c71e-e252-49f8-af64-69e7ec80c8af · outbound

This paper cites Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth.

Temporal Analysis of Adversarial Attacks in Federated Learning Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.948803Z

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Observation befbdd16-9733-4a5f-a8ae-58fcc2bcf356 · outbound

This paper cites Federated learning with autotuned communication-efficient secure aggregation.

Temporal Analysis of Adversarial Attacks in Federated Learning Federated learning with autotuned communication-efficient secure aggregation

Reference 5

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Observation 2595a5c0-8a49-4b5e-ad18-6fb86ff583bc · outbound

This paper cites Random forests.

Temporal Analysis of Adversarial Attacks in Federated Learning Random forests

Reference 6

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Observation 56adfba9-cc19-4997-9b8f-78b75be42c28 · outbound

This paper cites Breunig, Hans-Peter Kriegel, Raymond T.

Temporal Analysis of Adversarial Attacks in Federated Learning Breunig, Hans-Peter Kriegel, Raymond T

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.906593Z

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Observation f18a1986-119a-427b-993a-a7c9f7e4b099 · outbound

This paper cites MPAF: Model poisoning attacks to federated learning based on fake clients.

Temporal Analysis of Adversarial Attacks in Federated Learning MPAF: Model poisoning attacks to federated learning based on fake clients

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.889149Z

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Observation 00165767-8aa2-4a90-8bc2-9c5d366e4a50 · outbound

This paper cites XGBoost: A scalable tree boosting sys- tem.

Temporal Analysis of Adversarial Attacks in Federated Learning XGBoost: A scalable tree boosting sys- tem

Reference 9

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Observation 09a9e9b7-3161-4019-a9bd-d42e701a9ed9 · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

Temporal Analysis of Adversarial Attacks in Federated Learning Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 10

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Observation 26d617b6-6a40-40e5-b5c1-b40e62ef775e · outbound

This paper cites Communication-efficient fed- erated deep learning with layerwise asynchronous model update and tem- porally weighted aggregation.

Temporal Analysis of Adversarial Attacks in Federated Learning Communication-efficient fed- erated deep learning with layerwise asynchronous model update and tem- porally weighted aggregation

Reference 11

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Observation ca856c90-4146-4936-974b-b5dce0718760 · outbound

This paper cites Asyn- chronous online federated learning for edge devices with non-IID data.

Temporal Analysis of Adversarial Attacks in Federated Learning Asyn- chronous online federated learning for edge devices with non-IID data

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.841321Z

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Observation 4c36b0e1-fe7a-443c-8586-c019d06098f0 · outbound

This paper cites Federated learning with multichannel ALOHA.

Temporal Analysis of Adversarial Attacks in Federated Learning Federated learning with multichannel ALOHA

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.826384Z

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Observation 3707d78d-0c80-4004-865e-8b804d02e76d · outbound

This paper cites Support-vector networks.

Temporal Analysis of Adversarial Attacks in Federated Learning Support-vector networks

Reference 14

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Observation cd93f7b2-a4f5-4a5b-9745-5a20c2d518cc · outbound

This paper cites Heterofl: Computation and communication efficient federated learning for heterogeneous clients.

Temporal Analysis of Adversarial Attacks in Federated Learning Heterofl: Computation and communication efficient federated learning for heterogeneous clients

Reference 15

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Observation 3c93261d-a35a-4fa9-96b5-0dc1bd4c8930 · outbound

This paper cites Rawat, and Chunmei Liu.

Temporal Analysis of Adversarial Attacks in Federated Learning Rawat, and Chunmei Liu

Reference 16

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Observation 650cbccf-7266-4852-beaa-2d188799434e · outbound

This paper cites https://data.europa.eu/eli/reg/2016/679/oj, 2016.

Temporal Analysis of Adversarial Attacks in Federated Learning https://data.europa.eu/eli/reg/2016/679/oj, 2016

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.767687Z

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Observation 4bb5c136-58a2-4c5c-9468-71d982421583 · outbound

This paper cites https: //en.wikipedia.org/wiki/Federated_learning#/media/File: Federated_learning_(centralized_vs_decentralized).png, 2023.

Temporal Analysis of Adversarial Attacks in Federated Learning https: //en.wikipedia.org/wiki/Federated_learning#/media/File: Federated_learning_(centralized_vs_decentralized).png, 2023

Reference 18

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Observation 13599ebc-4778-4c6e-a870-dcf6d29d1732 · outbound

This paper cites https://flower.ai/static/ images/blog/content/2023-11-29-xgboost-fl.jpg , 2023.

Temporal Analysis of Adversarial Attacks in Federated Learning https://flower.ai/static/ images/blog/content/2023-11-29-xgboost-fl.jpg , 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.735831Z

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Observation 6b2af9b3-9855-40d4-a594-260834bf78a5 · outbound

This paper cites https://flower.ai/docs/framework/tutorial-quickstart- xgboost.html#tree-based-bagging-aggregation, 2023.

Temporal Analysis of Adversarial Attacks in Federated Learning https://flower.ai/docs/framework/tutorial-quickstart- xgboost.html#tree-based-bagging-aggregation, 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.720282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 01070cb7-aef0-4d5a-b6d4-f0489cc0a9fc · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735–1780, 1997.

Temporal Analysis of Adversarial Attacks in Federated Learning Long short-term memory.Neural Computation, 9(8):1735–1780, 1997

Reference 21

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Observation 4e17d64d-5a1b-4da8-bf06-fae7a23c27b5 · outbound

This paper cites Model and feature aggre- gation based federated learning for multi-sensor time series trend following.

Temporal Analysis of Adversarial Attacks in Federated Learning Model and feature aggre- gation based federated learning for multi-sensor time series trend following

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.692940Z

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Observation 9552157e-7793-4c16-a887-fd179f818246 · outbound

This paper cites Incentive design for efficient federated learning in mobile networks: A contract theory approach.

Temporal Analysis of Adversarial Attacks in Federated Learning Incentive design for efficient federated learning in mobile networks: A contract theory approach

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.678583Z

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Observation c2c0420b-62e3-40f8-8b0a-5c1fd469184d · outbound

This paper cites Reliable federated learning for mobile networks.

Temporal Analysis of Adversarial Attacks in Federated Learning Reliable federated learning for mobile networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.663130Z

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Observation 076f5ac6-25be-4130-b2b4-552de1623b66 · outbound

This paper cites Blockchained on-device federated learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Blockchained on-device federated learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.647981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a0642392-22d6-45cb-b84d-c5d46f25cd42 · outbound

This paper cites Peer-to-peer federated learning on graphs.

Temporal Analysis of Adversarial Attacks in Federated Learning Peer-to-peer federated learning on graphs

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.631216Z

Source-reported events for the cited work

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Observation 76870c1b-440d-4f74-b22d-0bfc38e3b543 · outbound

This paper cites MNIST handwritten digit database.

Temporal Analysis of Adversarial Attacks in Federated Learning MNIST handwritten digit database

Reference 27

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Observation 6d5d1019-e2f2-4e69-b70f-3c8a5a7d49ae · outbound

This paper cites Backpropagation applied to handwritten zip code recog- nition.

Temporal Analysis of Adversarial Attacks in Federated Learning Backpropagation applied to handwritten zip code recog- nition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.605175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ac14a11a-ee63-4a1c-9d26-e69d9d608cb0 · outbound

This paper cites Fair Resource Allocation in Federated Learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Fair Resource Allocation in Federated Learning

Reference 29

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Observation 4937f759-9383-46c3-8e3c-ca52ce94eceb · outbound

This paper cites Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption , pages 154–179.

Temporal Analysis of Adversarial Attacks in Federated Learning Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption , pages 154–179

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.590513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5f844349-2211-428c-ae59-609d658496e7 · outbound

This paper cites Isolation forest.

Temporal Analysis of Adversarial Attacks in Federated Learning Isolation forest

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.575080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e6bcf8de-6caa-465d-8173-a9bf0984f79c · outbound

This paper cites H Deng, and Kui Ren.

Temporal Analysis of Adversarial Attacks in Federated Learning H Deng, and Kui Ren

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.559606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 074d9b3a-add1-4433-b3db-d62dfe106e16 · outbound

This paper cites Blockchain and federated learning for privacy-preserved data sharing in industrial iot.

Temporal Analysis of Adversarial Attacks in Federated Learning Blockchain and federated learning for privacy-preserved data sharing in industrial iot

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.543593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e64a69f8-ea6f-4d55-bedf-c84d8f93e84f · outbound

This paper cites FLchain: Federated learning via MEC-enabled blockchain network.

Temporal Analysis of Adversarial Attacks in Federated Learning FLchain: Federated learning via MEC-enabled blockchain network

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.526391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2c26f0fc-413a-42a7-8629-611ae7fdd54c · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

Temporal Analysis of Adversarial Attacks in Federated Learning Communication-efficient learning of deep networks from decentralized data

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.511029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c8b9021d-aae0-4e33-8d54-6f9e6ec31c3d · outbound

This paper cites https://numpy.org/.

Temporal Analysis of Adversarial Attacks in Federated Learning https://numpy.org/

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.495787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9404087a-f398-493b-a294-e3d67677b3e4 · outbound

This paper cites https://pandas.pydata.org/.

Temporal Analysis of Adversarial Attacks in Federated Learning https://pandas.pydata.org/

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.480870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 93a12088-f2e9-4f40-9d24-f15661792bac · outbound

This paper cites https://pytorch.org/.

Temporal Analysis of Adversarial Attacks in Federated Learning https://pytorch.org/

Reference 38

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Observation 903d0a26-b4c7-499f-b958-ed1148ef8b0f · outbound

This paper cites Fedpaq: A communication-efficient federated learn- ing method with periodic averaging and quantization.

Temporal Analysis of Adversarial Attacks in Federated Learning Fedpaq: A communication-efficient federated learn- ing method with periodic averaging and quantization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.453149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 937349c6-55b3-4160-9efa-59e37711fb7a · outbound

This paper cites A fast algorithm for the minimum covariance determinant estimator.

Temporal Analysis of Adversarial Attacks in Federated Learning A fast algorithm for the minimum covariance determinant estimator

Reference 40

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Observation 371f51e6-cb02-4205-bc3a-0b93f728b1e8 · outbound

This paper cites BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning.

Temporal Analysis of Adversarial Attacks in Federated Learning BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning

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Resolution: unresolved; no resolver link, observed 2026-08-10T18:43:48.955766Z

Source-reported events for the cited work

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Observation babcddcc-6206-4368-be67-aa762090ea44 · outbound

This paper cites Rumelhart, Geoffrey E.

Temporal Analysis of Adversarial Attacks in Federated Learning Rumelhart, Geoffrey E

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.426700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 57017db1-bce0-4194-875a-18847d0f1489 · outbound

This paper cites Samy and Sarunas Girdzijauskas.

Temporal Analysis of Adversarial Attacks in Federated Learning Samy and Sarunas Girdzijauskas

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.411486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 631d8340-aa30-43a2-bf85-596f69718039 · outbound

This paper cites Platt, John Shawe-Taylor, Alex J.

Temporal Analysis of Adversarial Attacks in Federated Learning Platt, John Shawe-Taylor, Alex J

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.395694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e68b48d1-6f5f-494b-9090-db19725836e1 · outbound

This paper cites https://scikit-learn.org/ stable/.

Temporal Analysis of Adversarial Attacks in Federated Learning https://scikit-learn.org/ stable/

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.379461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1d93f90f-2786-44cb-a11f-ae15b8cd9293 · outbound

This paper cites Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks.

Temporal Analysis of Adversarial Attacks in Federated Learning Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T18:43:48.984357Z

Source-reported events for the cited work

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This paper cites Measure contribution of participants in federated learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Measure contribution of participants in federated learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.362953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 66822dab-129f-4da4-b321-0ff0e0fbeaef · outbound

This paper cites https://xgboost.

Temporal Analysis of Adversarial Attacks in Federated Learning https://xgboost

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.348124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 38c7438d-7485-4dbd-a4d5-ad3b56d2882a · outbound

This paper cites Hybridalpha: An efficient approach for privacy-preserving federated learn- ing.

Temporal Analysis of Adversarial Attacks in Federated Learning Hybridalpha: An efficient approach for privacy-preserving federated learn- ing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.330994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 262784b8-f442-4d3a-9b96-8ebb25c259ec · outbound

This paper cites Fed- erated learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Fed- erated learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.314343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 89c26ec8-de5e-4621-b369-65ac187a22fb · outbound

This paper cites Experience-driven computational resource allocation of federated learning by deep reinforcement learning.

Temporal Analysis of Adversarial Attacks in Federated Learning Experience-driven computational resource allocation of federated learning by deep reinforcement learning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:43:49.298730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9bc16758-82af-49c1-bbc5-95c77bfdfa23 · outbound

This paper cites Liu, and Yang Xiang.

Temporal Analysis of Adversarial Attacks in Federated Learning Liu, and Yang Xiang

Reference 53

Resolution: verified exact; raw_fallback, observed 2026-08-10T18:43:49.192407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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