Security and Privacy in Communication Networks: 17th EAI International Conference, SecureComm 2021, Virtual Event, September 69, 2021, Proceedings, P [Paperback]

This two-volume set LNICST 398 and 399 constitutes the post-conference proceedings of the 17^th International Conference on Security and Privacy in Communication Networks, SecureComm 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually.

The 56 full papers were carefully reviewed and selected from 143 submissions. The papers focus on the latest scientific research results in security and privacy in wired, mobile, hybrid and ad hoc networks, in IoT technologies, in cyber-physical systems, in next-generation communication systems in web and systems security and in pervasive and ubiquitous computing.

Cyber Threats and Defence.- DeepHunter: A Graph Neural Network Based Approach for Robust Cyber Threat Hunting.- SIEMA: Bringing Advanced Analytics to Legacy Security Information and Event Management.- Automatic Generation of Malware Threat Intelligence from Unstructured Malware Traces.- Towards Automated Assessment of Vulnerability Exposures in Security Operations.- Repeatable Experimentation for Cybersecurity Moving Target Defense.- MPD: Moving Target Defense through Communication Protocol Dialects.- Blockchain and P2P Security 7 GuardedGossip: Secure and Anonymous Node Discovery in Untrustworthy Networks.- n Extensive Security Analysis on Ethereum Smart Contracts.- A Distributed Ledger for Non-Attributable Cyber Threat Intelligence Exchange.- AI and Security/Privacy 10 Understanding ff for Differential Privacy in Differencing Attack Scenarios.- ToFi: An Algorithm to Defend against Byzantine Attacks in Federated Learning.- TESLAC: Accelerating Lattice-based Cryptography with AI Accelerator.- Research of CPA Attack Methods based on Ant Colony Algorithm.- Local Model Privacy-preserving Study for Federated Learning.- Applied Cryptography 16 Cryptonite: A Framework for Flexible Time-Series Secure Aggregation with Non-interactive Fault Recovery.- Cryptonomial: A Framework for Private Time-Series Polynolƒ)