SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) | Paper Citation Record

Observation 424d776a-b5a0-49b5-b3f4-b7c64e99a77a · outbound

This paper cites https://www.govinfo.gov/content/pkg/PLAW-104publ191/pdf/ PLAW-104publ191.pdf.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) https://www.govinfo.gov/content/pkg/PLAW-104publ191/pdf/ PLAW-104publ191.pdf

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a94b5e5c-45e5-4dd8-874d-525644b74fba · outbound

This paper cites https://eur-lex.europa.eu/eli/ reg/2016/679/oj.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) https://eur-lex.europa.eu/eli/ reg/2016/679/oj

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.376154Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 136c5455-fbd7-4bab-9a0e-87567f4d2946 · outbound

This paper cites https://pytorch.org.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) https://pytorch.org

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.357860Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55554eaf-62ec-4ef5-9413-295e22c70b78 · outbound

This paper cites Discrete cosine transform.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Discrete cosine transform

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.335850Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f63041c7-b4e7-47f0-9424-0c256be2fcd7 · outbound

This paper cites How To Backdoor Federated Learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) How To Backdoor Federated Learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.319501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8f65bdac-27ab-48cd-8be1-eec261cd831d · outbound

This paper cites VILLAIN: Backdoor attacks against vertical split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) VILLAIN: Backdoor attacks against vertical split learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.303122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 95169507-4de8-412a-af39-09882f07677e · outbound

This paper cites Analyzing federated learning through an adversarial lens.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Analyzing federated learning through an adversarial lens

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.284961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dfebd9a9-0efa-4dc5-850f-9e41aaf29017 · outbound

This paper cites Machine Learning with Adversaries: Byzantine Tolerant Gradi- ent Descent.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Machine Learning with Adversaries: Byzantine Tolerant Gradi- ent Descent

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.263025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0bdd5c62-52d2-479b-9e92-acc14f51bcef · outbound

This paper cites Fltrust: Byzantine-robust federated learning via trust bootstrapping.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Fltrust: Byzantine-robust federated learning via trust bootstrapping

Reference 9

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Source-reported events for the cited work

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Observation c9e0f9b4-4398-4d21-80bf-a2c1ea8f3d99 · outbound

This paper cites Provably secure federated learning against malicious clients.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Provably secure federated learning against malicious clients

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.233163Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d12bb39d-aecf-460c-ad90-21b2936aeac0 · outbound

This paper cites Fledge: Ledger-based federated learning resilient to inference and backdoor attacks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Fledge: Ledger-based federated learning resilient to inference and backdoor attacks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.214025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 951d9f50-32d3-48bd-9221-8b2404afb4b8 · outbound

This paper cites Harrison Smith, and S.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Harrison Smith, and S

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.196899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5e3d836f-f107-4678-b4e8-b3605da08c94 · outbound

This paper cites Splitguard: Detecting and mitigating training-hijacking attacks in split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Splitguard: Detecting and mitigating training-hijacking attacks in split learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.177893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b4a5996f-a544-4b67-b1af-59231c2a1473 · outbound

This paper cites Freqfed: A frequency analysis- based approach for mitigating poisoning attacks in federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Freqfed: A frequency analysis- based approach for mitigating poisoning attacks in federated learning

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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This paper cites Label inference attacks against vertical federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Label inference attacks against vertical federated learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.132076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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This paper cites Focusing on pinocchio’s nose: A gradients scrutinizer to thwart split-learning hijacking attacks using intrinsic attributes.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Focusing on pinocchio’s nose: A gradients scrutinizer to thwart split-learning hijacking attacks using intrinsic attributes

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.108614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c87a1193-ff50-4db4-a472-b796fea585ea · outbound

This paper cites The limitations of federated learning in sybil settings.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) The limitations of federated learning in sybil settings

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.082587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a58f33c9-c762-450b-a3f5-92fc527eb0f4 · outbound

This paper cites PCAT: Functionality and data stealing from split learning by Pseudo-Client attack.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) PCAT: Functionality and data stealing from split learning by Pseudo-Client attack

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.064403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1f202d29-4ac3-4e4d-9384-ff44765fe133 · outbound

This paper cites End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

Reference 19

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Source-reported events for the cited work

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Observation 567836ec-3ba5-47f4-86db-d6184ccc2616 · outbound

This paper cites Distributed learning of deep neural network over multiple agents.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Distributed learning of deep neural network over multiple agents

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.045869Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4417f306-630b-4d95-9d7a-49cdc67aa176 · outbound

This paper cites Deep residual learning for image recognition.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Deep residual learning for image recognition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.025524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 021adbae-de3d-4a50-af43-97e74c3238a8 · outbound

This paper cites Backdoor attack against split neural network-based vertical federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Backdoor attack against split neural network-based vertical federated learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:03.005464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 725c1645-078b-44c4-a308-27808c8ad118 · outbound

This paper cites Advances and open problems in federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Advances and open problems in federated learning

Reference 23

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Source-reported events for the cited work

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Observation ce70be66-bc02-4cfe-91a8-0d148fb12123 · outbound

This paper cites Exploit: Extracting private labels in split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Exploit: Extracting private labels in split learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.970371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6d94c1e6-1f3a-44b8-b1c6-94c8eb1dd07d · outbound

This paper cites Mesas: Poisoning defense for federated learning resilient against adaptive attackers.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Mesas: Poisoning defense for federated learning resilient against adaptive attackers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.950312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb9643f2-69c5-4ea7-8555-05ba257ec24e · outbound

This paper cites Learning multiple layers of features from tiny images.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Learning multiple layers of features from tiny images

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.922151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89f6bc36-4aac-40ac-9943-b0ce1e8f7128 · outbound

This paper cites Baybfed: Bayesian backdoor defense for federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Baybfed: Bayesian backdoor defense for federated learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.903791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation de299c0f-a8e6-42ae-b2f2-4f889dc949ba · outbound

This paper cites FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning

Reference 28

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fab6422d-cf7d-4448-9dbf-521753d817cf · outbound

This paper cites Label Leakage and Protection in Two-party Split Learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Label Leakage and Protection in Two-party Split Learning

Reference 29

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Source-reported events for the cited work

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Observation 79a65a39-eda1-45d0-a13e-a3ae4bf9aafc · outbound

This paper cites Federated learning: Challenges, methods, and future directions.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Federated learning: Challenges, methods, and future directions

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.883915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d9257f93-ad23-4ea4-a128-436b916d2920 · outbound

This paper cites Similarity-based Label Inference Attack against Training and Inference of Split Learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Similarity-based Label Inference Attack against Training and Inference of Split Learning

Reference 31

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6a194584-a44b-4d44-aa39-e99da08bc9cd · outbound

This paper cites Similarity-based label inference attack against training and inference of split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Similarity-based label inference attack against training and inference of split learning

Reference 32

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3cf95ee1-6350-4fb2-8b3e-608ab99ed562 · outbound

This paper cites Secure split learning against property inference, data reconstruction, and feature space hijacking attacks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Secure split learning against property inference, data reconstruction, and feature space hijacking attacks

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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This paper cites Federated learning: Collabora- tive Machine Learning without Centralized Training Data.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Federated learning: Collabora- tive Machine Learning without Centralized Training Data

Reference 34

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f21c3a65-4516-49ac-8ee4-cd59eb317fa9 · outbound

This paper cites Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang

Reference 35

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e8a345a-7903-411e-8ca1-24fc9a710214 · outbound

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

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 36

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Source-reported events for the cited work

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This paper cites Discrete cosine transform.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Discrete cosine transform

Reference 37

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4b010a3c-0b4a-419b-945a-c7f3f0f190f5 · outbound

This paper cites Unleashing the tiger: Inference attacks on split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Unleashing the tiger: Inference attacks on split learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.775355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 21da2765-42c9-46d8-8596-1b5872701838 · outbound

This paper cites Split Learning for collaborative deep learning in healthcare.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Split Learning for collaborative deep learning in healthcare

Reference 39

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Source-reported events for the cited work

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Observation 9a590c06-cd09-4744-87e5-0cb56f54f462 · outbound

This paper cites Hamprecht, Yoshua Bengio, and Aaron Courville.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Hamprecht, Yoshua Bengio, and Aaron Courville

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.755625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bdcd0995-6a06-43b9-b105-56423ef766a4 · outbound

This paper cites Crowdguard: Federated backdoor detection in federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Crowdguard: Federated backdoor detection in federated learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.738839Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 00c8bde6-c60e-4e3f-a463-cf9736c93c8a · outbound

This paper cites Safesplit: A novel defense against client-side backdoor attacks in split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Safesplit: A novel defense against client-side backdoor attacks in split learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.721339Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d6842b15-ac85-4c04-86f4-fa138184076c · outbound

This paper cites Hidden trigger backdoor attacks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Hidden trigger backdoor attacks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.704691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb88b232-0176-4160-89ee-78999fee6bae · outbound

This paper cites Auror: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Auror: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.687243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1d79611d-69be-4d3e-82c4-2742071b2f83 · outbound

This paper cites Manipulating sgd with data ordering attacks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Manipulating sgd with data ordering attacks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.669739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0a45b99a-4487-43b2-9dee-e7d8c0525345 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Very deep convolutional networks for large-scale image recognition

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.652358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e0212708-52dd-4754-87dd-f30d768580e2 · outbound

This paper cites Detailed comparison of communication efficiency of split learning and federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Detailed comparison of communication efficiency of split learning and federated learning

Reference 47

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Source-reported events for the cited work

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This paper cites The german traffic sign recognition benchmark: a multi-class classifica- tion competition.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) The german traffic sign recognition benchmark: a multi-class classifica- tion competition

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.635073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ca561a1-ef27-4eca-a563-9d031210b64a · outbound

This paper cites Going deeper with convolutions.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Going deeper with convolutions

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.617439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b6231cfa-f9d2-4838-a072-768291a8be94 · outbound

This paper cites On feasibility of server-side backdoor attacks on split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) On feasibility of server-side backdoor attacks on split learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.598595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 13b94cfb-39b7-4da8-a6e9-6445b0d335a4 · outbound

This paper cites Advancements of federated learning towards privacy preser- vation: from federated learning to split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Advancements of federated learning towards privacy preser- vation: from federated learning to split learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.579587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2670401f-ba99-424b-9c95-ce17b2e86f57 · outbound

This paper cites How to prove it: A structured approach.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) How to prove it: A structured approach

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.560930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1f08548f-009d-44f5-b8ff-822415e8e432 · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Split learning for health: Distributed deep learning without sharing raw patient data

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:01.955217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fbc5f11-caa8-4f53-9135-c5348e105c95 · outbound

This paper cites Flare: defending federated learning against model poisoning attacks via latent space representations.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Flare: defending federated learning against model poisoning attacks via latent space representations

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.542263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ea6989f1-5165-43fd-a3e5-038fa91fcb5c · outbound

This paper cites Fast algorithms for the discrete w transform and for the discrete fourier transform.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Fast algorithms for the discrete w transform and for the discrete fourier transform

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.521897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a39b8ef1-55f0-4f27-8355-c823b62c5b97 · outbound

This paper cites Backdoor attacks against deep learning systems in the physical world.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Backdoor attacks against deep learning systems in the physical world

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.502318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c6e6d713-a34f-413e-9ccb-88f68b07dbc4 · outbound

This paper cites Micronnet: A highly compact deep convolutional neural network archi- tecture for real-time embedded traffic sign classification.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Micronnet: A highly compact deep convolutional neural network archi- tecture for real-time embedded traffic sign classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.482032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72678e54-d474-4271-9a65-93c400a43791 · outbound

This paper cites A study on quantization effects of dct based compression.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) A study on quantization effects of dct based compression

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.463336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 50083cf8-2ef6-4b99-935e-d2c6b818516e · outbound

This paper cites Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:01.986185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14a03f00-5843-461d-9e7d-70961a41f3d5 · outbound

This paper cites DBA: Distributed backdoor attacks against federated learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) DBA: Distributed backdoor attacks against federated learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.431838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9921cd6f-bc6b-406d-be45-7fea8903c32d · outbound

This paper cites Training behavior of deep neural network in frequency domain.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Training behavior of deep neural network in frequency domain

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.414089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c2ec2967-31cf-4eab-bbee-f36700fcc1d4 · outbound

This paper cites Differentially Private Label Protection in Split Learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Differentially Private Label Protection in Split Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:02.001136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4edbf0e8-112b-40e1-9dc5-333267d50aee · outbound

This paper cites Robust Split Federated Learning for U-shaped Medical Image Networks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Robust Split Federated Learning for U-shaped Medical Image Networks

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:02.006971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a68c80cd-ef38-42d3-8cb8-9a2c5357cb51 · outbound

This paper cites How to backdoor split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) How to backdoor split learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.393779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 26a07cc2-3d1e-4265-a802-ca10d29acec9 · outbound

This paper cites Chronic poisoning: Backdoor attack against split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Chronic poisoning: Backdoor attack against split learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.363391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 27658d13-4622-4556-a9ad-b6bd07a66771 · outbound

This paper cites Wide Residual Networks.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Wide Residual Networks

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:02.023901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4ac39a2-9145-4388-86d9-359fed84d820 · outbound

This paper cites Label inference attack based on soft label towards two-party split learning.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Label inference attack based on soft label towards two-party split learning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:02:02.345738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ecab5552-3e3d-4407-868e-52358e6bd9e8 · outbound

This paper cites Passive Inference Attacks on Split Learning via Adversarial Regularization.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Passive Inference Attacks on Split Learning via Adversarial Regularization

Reference 68

Resolution: malformed identifier; no resolver link, observed 2026-08-10T21:02:02.035875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers