2 citations · 7 across the 28 of their papers we have counts for
12 papers · 1 filter
FedEP: Tailoring Attention to Heterogeneous Data Distribution with Entropy Pooling for Decentralized Federated Learning
Chao Feng, Hongjie Guan, Alberto Huertas Celdrán +3
Non-Independent and Identically Distributed (non-IID) data in Federated Learning (FL) causes client drift issues, leading to slower convergence and reduced model performance. While…
De-VertiFL: A Solution for Decentralized Vertical Federated Learning
Alberto Huertas Celdrán, Chao Feng, Sabyasachi Banik +3
Federated Learning (FL), introduced in 2016, was designed to enhance data privacy in collaborative model training environments. Among the FL paradigm, horizontal FL, where clients…
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…
Towards Threat Modelling of IoT Context-Sharing Platforms
Mohammad Goudarzi, Arash Shaghaghi, Simon Finn +2
The Internet of Things (IoT) involves complex, interconnected systems and devices that depend on context-sharing platforms for interoperability and information exchange. These plat…
PACCOR4ESP: Embedded Device Security Attestation using Platform Attribute Certificates
Thomas Grübl, Jan von der Assen, Markus Knecht +1
Verifying the integrity of embedded device characteristics is required to ensure secure operation of a device. One central challenge is to securely extract and store device-specifi…
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis
Chao Feng, Alberto Huertas Celdrán, Jan von der Assen +3
Federated Learning (FL) has emerged as a promising approach to address privacy concerns inherent in Machine Learning (ML) practices. However, conventional FL methods, particularly…
The Danger Within: Insider Threat Modeling Using Business Process Models
Jan von der Assen, Jasmin Hochuli, Thomas Grübl +1
Threat modeling has been successfully applied to model technical threats within information systems. However, a lack of methods focusing on non-technical assets and their represent…
Performance Analysis of Decentralized Physical Infrastructure Networks and Centralized Clouds
Jan von der Assen, Christian Killer, Alessandro De Carli +1
The advent of Decentralized Physical Infrastructure Networks (DePIN) represents a shift in the digital infrastructure of today's Internet. While Centralized Service Providers (CSP)…
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…
QuantTM: Business-Centric Threat Quantification for Risk Management and Cyber Resilience
Jan von der Assen, Muriel F. Franco, Muyao Dong +1
Threat modeling has emerged as a key process for understanding relevant threats within businesses. However, understanding the importance of threat events is rarely driven by the bu…
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…
Empirical and Theoretical Analysis of Liquid Staking Protocols
Krzysztof Gogol, Benjamin Kraner, Malte Schlosser +3
Liquid staking has become the largest category of decentralized finance protocols in terms of total value locked. However, few studies exist on its implementation designs or underl…