TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data | Paper Citation Record

Observation d22d0e04-2c88-4a4e-bdf7-612561651546 · outbound

This paper cites How to backdoor federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data How to backdoor federated learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.459791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2092b041-6c8a-4d88-bd86-982cdb770af0 · outbound

This paper cites Analyzing federated learning through an adversarial lens.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Analyzing federated learning through an adversarial lens

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.597239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d55c49c3-bb35-4f0e-9890-cfb7aa6d17e1 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Machine learning with adversaries: Byzantine tolerant gradient descent

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.579208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3aa4edd7-4a71-47e3-b1e9-f2745b864bc8 · outbound

This paper cites FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.476723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac731cf3-7289-4a82-a794-6f660c97b88e · outbound

This paper cites Provably secure federated learning against malicious clients.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Provably secure federated learning against malicious clients

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.562577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 613c74a6-e057-46dd-aaf9-f3a49389f3a3 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.487468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5446ca54-1240-4516-acf5-7f1efefac517 · outbound

This paper cites Distributed statistical machine learning in adversarial settings: Byzantine gradient descent.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Distributed statistical machine learning in adversarial settings: Byzantine gradient descent

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.545934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7fa8a15d-e52c-455b-abb2-2ddd683487d2 · outbound

This paper cites Emnist: Extending mnist to handwritten letters.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Emnist: Extending mnist to handwritten letters

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.528875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c4c1a44-6c47-4b02-a6d5-4e6620808873 · outbound

This paper cites Chameleon: Adapting to peer images for planting durable backdoors in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Chameleon: Adapting to peer images for planting durable backdoors in federated learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.511329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1fd19817-738a-4512-89a1-51fb487d3e6d · outbound

This paper cites Exploiting linear structure within convolutional networks for efficient evaluation.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Exploiting linear structure within convolutional networks for efficient evaluation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.507763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3504f557-261d-420e-baf8-edbcbe6a8616 · outbound

This paper cites Local model poisoning attacks to byzantine-robust federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Local model poisoning attacks to byzantine-robust federated learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.483058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6319ed15-f272-415b-8c9b-55001ccbd08d · outbound

This paper cites On the vulnerability of backdoor defenses for federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data On the vulnerability of backdoor defenses for federated learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.466674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4068edc2-8d60-43c3-8397-05e47059a614 · outbound

This paper cites FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.522369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb29ee62-87d0-4f90-8da1-b6d2c336ed6e · outbound

This paper cites an unresolved cited work.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:24:38.449164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 76bd7adc-c6a3-4b9f-b143-cb6878fb7e3e · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data The limitations of federated learning in sybil settings

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.433516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ef273c3f-bfa9-48f9-b3fb-fde2aa23b5b4 · outbound

This paper cites Inverting gradients-how easy is it to break privacy in fed- erated learning? Advances in Neural Information Processing Systems , 33:16937–16947, 2020.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Inverting gradients-how easy is it to break privacy in fed- erated learning? Advances in Neural Information Processing Systems , 33:16937–16947, 2020

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.416947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cc58c6e-d065-4153-948f-05f09cc3c61f · outbound

This paper cites Atteq-nn: Attention-based qoe-aware evasive backdoor attacks.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Atteq-nn: Attention-based qoe-aware evasive backdoor attacks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.398739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eedf5426-c2e8-4ba3-9283-90aee0634844 · outbound

This paper cites Defense-resistant backdoor attacks against deep neural networks in outsourced cloud environment.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Defense-resistant backdoor attacks against deep neural networks in outsourced cloud environment

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.383025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e148c17-3741-4bb3-8561-358e6a438395 · outbound

This paper cites Badnets: Evaluating backdooring attacks on deep neural networks.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Badnets: Evaluating backdooring attacks on deep neural networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.549881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bcf65fb-3c9b-4f44-844f-40d6ef849264 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data The hidden vulnerability of distributed learning in byzantium

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.355974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 05d5b904-1e68-4557-a91c-31e0353905d6 · outbound

This paper cites Learning both weights and connections for efficient neural network.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Learning both weights and connections for efficient neural network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.340004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7e099b09-2ecf-4cdd-82b5-4b62654f7767 · outbound

This paper cites Deep residual learning for image recognition.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Deep residual learning for image recognition

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.563624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db9ae37c-6c95-4f6c-b271-d46d357f76cb · outbound

This paper cites Why relu networks yield high-confidence predictions far away from the training data and how to mitigate the problem.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Why relu networks yield high-confidence predictions far away from the training data and how to mitigate the problem

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.568254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16699898-3186-4736-ba6a-486435cf5082 · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.572913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fb2ad00-ac50-43af-824d-921e7a7011df · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.301153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 91d876b0-4ef4-42f1-80a6-a3ca6e6a1fe6 · outbound

This paper cites Communication-efficient distributed sgd with sketching.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Communication-efficient distributed sgd with sketching

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.285208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 629cf646-e971-45c4-8a9d-eb784198f2e4 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Mesas: Poisoning defense for federated learning resilient against adaptive attackers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.267695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa30bbb7-896b-4ea2-94b1-1974a9ba8581 · outbound

This paper cites Automatic adversarial adaption for stealthy poisoning attacks in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Automatic adversarial adaption for stealthy poisoning attacks in federated learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.248219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 33bee284-f616-465e-b592-4828408bc74d · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Learning multiple layers of features from tiny images

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.596737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 867f9a7b-236a-46fc-8a6b-9050115dd77d · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Baybfed: Bayesian backdoor defense for federated learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.220343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a6d75b58-d556-4c1a-891b-3398d5e69b87 · outbound

This paper cites BackdoorIndicator: Leveraging OOD data for proactive backdoor detection in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data BackdoorIndicator: Leveraging OOD data for proactive backdoor detection in federated learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.201093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d70c1dd1-cc13-400d-9b2e-7be00a601532 · outbound

This paper cites Poisoning with cerberus: Stealthy and colluded backdoor attack against federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Poisoning with cerberus: Stealthy and colluded backdoor attack against federated learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.182378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0f12a96a-e120-43af-ae63-5e7ac8682a01 · outbound

This paper cites Lurking in the shadows: Unveiling stealthy backdoor attacks against personalized fed- erated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Lurking in the shadows: Unveiling stealthy backdoor attacks against personalized fed- erated learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.166625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 50d3db90-6a1e-406d-a08d-0668d281dc88 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Communication-efficient learning of deep networks from decentralized data

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.150961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cd4d70d-7244-45bb-98f5-b9bf0f42e46d · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Learning Differentially Private Recurrent Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.624832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa7ef418-aa91-4328-ba15-3fb28a6833b5 · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.630148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbe21126-ed63-4175-935a-e46f83cba914 · outbound

This paper cites Local and central differential privacy for robustness and privacy in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Local and central differential privacy for robustness and privacy in federated learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.135188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4d80f975-baa6-47a7-bb98-de926f88a9db · outbound

This paper cites Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.639793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8969d9dd-129c-47f9-8278-d70dce71aa66 · outbound

This paper cites {FLAME}: Taming backdoors in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data {FLAME}: Taming backdoors in federated learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.108042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d4a9753-cfc6-4139-949e-c31ae71cdba2 · outbound

This paper cites Revisiting the assumption of latent separability for backdoor defenses.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Revisiting the assumption of latent separability for backdoor defenses

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.092023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bdea5e9b-a057-4615-a898-eb8998ceea00 · outbound

This paper cites CrowdGuard: Federated Backdoor Detection in Federated Learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data CrowdGuard: Federated Backdoor Detection in Federated Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.654130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 968e183a-894f-4114-95fe-8f67105767ad · outbound

This paper cites Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.658971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f385fedf-5cf6-462f-9567-42436bd92474 · outbound

This paper cites Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.663672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0603c75-3d45-4275-9e33-29eada42545d · outbound

This paper cites Auror: Defending against poisoning attacks in collaborative deep learning systems.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Auror: Defending against poisoning attacks in collaborative deep learning systems

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.051590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7da0d15-3489-49b9-acf9-4a05327da2d6 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.673024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d9ff912-7abf-4661-820c-affce994e3b5 · outbound

This paper cites Spar- sified sgd with memory.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Spar- sified sgd with memory

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.033817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c96bdf5f-7ef9-40df-af1a-fba2d57dfaca · outbound

This paper cites Can You Really Backdoor Federated Learning?.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Can You Really Backdoor Federated Learning?

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:37.682437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90db0bef-9ea0-4fe0-856f-a8257ba5a6c2 · outbound

This paper cites Demon in the variant: Statistical analysis of dnns for robust backdoor contam- ination detection.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Demon in the variant: Statistical analysis of dnns for robust backdoor contam- ination detection

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:38.018215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b36e3e1f-9364-4c20-b190-28f3017860cf · outbound

This paper cites Attack of the tails: Yes, you really can backdoor federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Attack of the tails: Yes, you really can backdoor federated learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:37.999902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9238f1a6-bfd4-4fde-a03f-3f666109bd4b · outbound

This paper cites Rflbat: A robust federated learning algorithm against backdoor attack, 2022.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Rflbat: A robust federated learning algorithm against backdoor attack, 2022

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:37.980843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation de9e0f10-b3b1-48e2-9809-1f9b7187110b · outbound

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

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Dba: Distributed backdoor attacks against federated learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:37.952922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aab262ac-1620-40fb-81b7-9b8ef1873026 · outbound

This paper cites Bartlett.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Bartlett

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:37.935807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e383d271-fb35-4a72-936f-8f625c6ba38b · outbound

This paper cites Neurotoxin: Durable backdoors in federated learning.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Neurotoxin: Durable backdoors in federated learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:24:37.919363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55990873-f97a-4269-b931-6edb0bc7543d · outbound

This paper cites Shielding collaborative learning: Mitigating poisoning attacks through client-side detection.

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data Shielding collaborative learning: Mitigating poisoning attacks through client-side detection

Reference 54

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T11:24:37.902215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers