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20232025
most citedFedstellar: A Platform for Decentralized Federated Learning

82 citations · 111 across the 18 of their papers we have counts for

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7 papers · 1 filter

cs.CR2025

A Crowdsensing Intrusion Detection Dataset For Decentralized Federated Learning Models

Chao Feng, Alberto Huertas Celdran, Jing Han +6

This paper introduces a dataset and an experimental study on Decentralized Federated Learning (DFL) for Internet of Things (IoT) crowdsensing malware detection. The dataset compris…

cs.CR2024

Leveraging MTD to Mitigate Poisoning Attacks in Decentralized FL with Non-IID Data

Chao Feng, Alberto Huertas Celdrán, Zien Zeng +4

Decentralized Federated Learning (DFL), a paradigm for managing big data in a privacy-preserved manner, is still vulnerable to poisoning attacks where malicious clients tamper with…

cs.CR2024★ 1 cited

Asset-centric Threat Modeling for AI-based Systems

Jan von der Assen, Jamo Sharif, Chao Feng +3

Threat modeling is a popular method to securely develop systems by achieving awareness of potential areas of future damage caused by adversaries. However, threat modeling for syste…

cs.CR2024★ 1 cited

GuardFS: a File System for Integrated Detection and Mitigation of Linux-based Ransomware

Jan von der Assen, Chao Feng, Alberto Huertas Celdrán +3

Although ransomware has received broad attention in media and research, this evolving threat vector still poses a systematic threat. Related literature has explored their detection…

cs.CR2023

Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks on DFL

Chao Feng, Alberto Huertas Celdran, Michael Vuong +2

The growing concern over malicious attacks targeting the robustness of both Centralized and Decentralized Federated Learning (FL) necessitates novel defensive strategies. In contra…

cs.CR2023★ 2 cited

CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation

Chao Feng, Alberto Huertas Celdran, Pedro Miguel Sanchez Sanchez +5

Recent research has shown that the integration of Reinforcement Learning (RL) with Moving Target Defense (MTD) can enhance cybersecurity in Internet-of-Things (IoT) devices. Nevert…

cs.CR2023★ 24 cited

RCVaR: an Economic Approach to Estimate Cyberattacks Costs using Data from Industry Reports

Muriel Figueredo Franco, Fabian Künzler, Jan von der Assen +2

Digitization increases business opportunities and the risk of companies being victims of devastating cyberattacks. Therefore, managing risk exposure and cybersecurity strategies is…