13 papers
Chained Attacks on Drone-Based Federated Learning: From Network Disruption to Device Impersonation
Suleiman Muhammad Sabo, Hamed Alkharsh, Peilin Li +4
Edge Intelligence (EI) has emerged as a transformative model for mission-critical unmanned platforms, such as drone swarms, by enabling collaborative model training at the network…
Exploring Blockchain Interoperability: Frameworks, Use Cases, and Future Challenges
Stanly Wilson, Kwabena Adu-Duodu, Yinhao Li +3
Trust between entities in any scenario without a trusted third party is very difficult, and trust is exactly what blockchain aims to bring into the digital world with its basic fea…
Dataset Distillation-based Hybrid Federated Learning on Non-IID Data
Xiufang Shi, Wei Zhang, Yuheng Li +5
In federated learning, the heterogeneity of client data has a great impact on the performance of model training. Many heterogeneity issues in this process are raised by non-indepen…
Benchmarking of CPU-intensive Stream Data Processing in The Edge Computing Systems
Tomasz Szydlo, Viacheslav Horbanov, Devki Nandan Jha +3
Edge computing has emerged as a pivotal technology, offering significant advantages such as low latency, enhanced data security, and reduced reliance on centralized cloud infrastru…
EVECTOR: An orchestrator for analysing attacks in electric vehicles charging system
Devki Nandan Jha, Tomasz Szydlo, Nima Valizadeh +9
Electric Vehicle (EV) charging infrastructure is critical for the widespread adoption of EVs, ensuring efficient and secure charging processes. Evaluating the security and performa…
TinyAC: Bringing Autonomic Computing Principles to Resource-Constrained Systems
Wojciech Kalka, Ruitao Xue, Kamil Faber +4
Autonomic Computing (AC) is a promising approach for developing intelligent and adaptive self-management systems at the deep network edge. In this paper, we present the problems an…