Paper Citation Record · LEDGER

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL

As of 17 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 2 inbound Pith citation observations for arXiv:2506.19892.

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

pith.paper-citation-record.v1
2506.19892 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:11:54.710922Z

measured 22 of 22 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T20:08:21.578954Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T20:10:10.959898Z

Reference resolution

20 of 20 outbound references displayed

verified exact2
verified fuzzy17
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e1c339b-5e38-4127-ba70-2b22dd09b550 · outbound

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

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Communication-efficient learning of deep networks from decentralized data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:55.033660Z

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.

Observation 5394aa5e-6d40-4e87-90e5-b8af0291cff6 · outbound

This paper cites Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:55.022172Z

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.

Observation 239b1d0b-70a5-47cf-9f2b-b77ef3c6c266 · outbound

This paper cites Detection of false data injection attacks in smart grid: A secure federated deep learning approach,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Detection of false data injection attacks in smart grid: A secure federated deep learning approach,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:55.010832Z

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.

Observation d5adafbd-9b16-4eaa-b7d0-4c9d76feeb4c · outbound

This paper cites Delay- aware hierarchical federated learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Delay- aware hierarchical federated learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.999858Z

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.

Observation 7ed53c1d-1fc8-42fc-b57d-82290888eeec · outbound

This paper cites FLEAM: A federated learning empowered architecture to mitigate DDoS in industrial IoT,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL FLEAM: A federated learning empowered architecture to mitigate DDoS in industrial IoT,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.988793Z

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.

Observation 5b52c1ac-9896-4c84-b54e-7a93e3e5127f · outbound

This paper cites HybridChain: Fast, accurate, and secure transaction processing with distributed learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL HybridChain: Fast, accurate, and secure transaction processing with distributed learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.975886Z

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.

Observation ec92dcca-2644-40d8-988f-86b6e0ff3f7c · outbound

This paper cites Protecting federated learning from extreme model poisoning attacks via multidimensional time series anomaly detection,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Protecting federated learning from extreme model poisoning attacks via multidimensional time series anomaly detection,

Reference 8

Resolution: verified exact; doi, observed 2026-08-06T23:11:54.824554Z

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.

Observation df83e136-1926-478f-9d18-393226024236 · outbound

This paper cites Sok: Secure aggregation based on cryptographic schemes for federated learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Sok: Secure aggregation based on cryptographic schemes for federated learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.953109Z

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.

Observation 30275999-7df5-4188-92f7-10e863e75742 · outbound

This paper cites Nebula: A platform for decentralized federated learn- ing,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Nebula: A platform for decentralized federated learn- ing,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.942606Z

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.

Observation 6bb8e6be-128b-4d68-b976-2f46251ac6db · outbound

This paper cites Reputation-based federated learning for secure wireless networks,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Reputation-based federated learning for secure wireless networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.932042Z

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.

Observation 7b3648bc-6d77-4103-81c3-cc490f0849b0 · outbound

This paper cites Incentive mech- anism for reliable federated learning: A joint optimization approach to combining reputation and contract theory,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Incentive mech- anism for reliable federated learning: A joint optimization approach to combining reputation and contract theory,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:54.673566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7055230-a2a8-498e-8904-ef06fbc04a3b · outbound

This paper cites Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:11:54.748050Z

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.

Observation cd70d432-1306-43ce-a212-3452262353f5 · outbound

This paper cites Secure and privacy-preserving federated learning via co-utility,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Secure and privacy-preserving federated learning via co-utility,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.914026Z

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.

Observation 2cc502ea-893a-403e-a970-5f858e7b47b0 · outbound

This paper cites A reputation-aware hierar- chical aggregation framework for federated learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL A reputation-aware hierar- chical aggregation framework for federated learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.964445Z

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.

Observation 3ecad229-66ec-4c84-8547-0c6806a79c31 · outbound

This paper cites FGFL: A blockchain-based fair incentive governor for federated learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL FGFL: A blockchain-based fair incentive governor for federated learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.901078Z

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.

Observation 6a4882f5-38ef-4402-a68b-7a4420ef1683 · outbound

This paper cites Poisoning attacks on federated learning-based IoT intrusion detection system,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Poisoning attacks on federated learning-based IoT intrusion detection system,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.888417Z

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.

Observation 0b5d44bd-52db-45be-9504-a05a4f674d9f · outbound

This paper cites Fed- erated learning-based in-network traffic analysis on IoT edge,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Fed- erated learning-based in-network traffic analysis on IoT edge,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.875596Z

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.

Observation ffe97e8e-8cd2-417a-a5cc-58a25877b232 · outbound

This paper cites Decentralized federated learning: A survey on security and privacy,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Decentralized federated learning: A survey on security and privacy,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.862427Z

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.

Observation 6c371c9a-0200-4cce-8c5f-a6c8c3d5593e · outbound

This paper cites Secure and efficient federated learning through layering and sharding blockchain,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Secure and efficient federated learning through layering and sharding blockchain,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.849947Z

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.

Observation 5e5198be-210e-4a43-b711-6ce81aa592b5 · outbound

This paper cites Fedeval: Defending against lazybone attack via multi-dimension evaluation in federated learning,.

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL Fedeval: Defending against lazybone attack via multi-dimension evaluation in federated learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:54.837788Z

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.

Pith citing papers

Observation b71c2cb7-adf2-4b2f-8021-50c8755cb4e5 · inbound

FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning cites this paper.

FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning RepuNet: A Reputation System for Mitigating Malicious Clients in DFL

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:10:10.962361Z

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.

Observation d2c25729-6224-4967-94df-ad68972384a5 · inbound

\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments cites this paper.

\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments RepuNet: A Reputation System for Mitigating Malicious Clients in DFL

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:30:55.250480Z

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.