Foundations and Practice of Security
Description
This two-volume set constitutes the refereed proceedings of the 17th International Symposium on Foundations and Practice of Security, FPS 2024, held in Montréal, QC, Canada, during December 09-11, 2024.
The 28 full and 11 short papers presented in this book were carefully reviewed and selected from 75 submissions. The papers were organized in the following topical sections:
Part I: Critical issues of protecting systems against digital threats,considering financial, technological, and operational implications; Automating and enhancing security mechanisms in software systems and data management; Cybersecurity and AI when applied to emerging technologies; Cybersecurity and Ethics; Cybersecurity and privacy in connected and autonomous systems for IoT, smart environments, and critical
infrastructure; New trends in advanced cryptographic protocols. Part II: Preserving privacy and maintaining trust for end users in a complex and numeric cyberspace; Intersecting security, privacy, and machine learning techniques to detect, mitigate, and prevent threats; New trends of machine leaning and AI applied to cybersecurity.
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Content
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Preserving privacy and maintaining trust for end users in a complex and numeric cyberspace.
.- Another Walk for Monchi.
.- An Innovative DSSE Framework: Ensuring Data Privacy and Query Verification in Untrusted Cloud Environments.
.- Privacy-Preserving Machine Learning Inference for Intrusion Detection.
.- Priv-IoT: Privacy-preserving Machine Learning in IoT Utilizing TEE and Lightweight Ciphers.
.- Intersecting security, privacy, and machine learning techniques to detect, mitigate, and prevent threats.
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LocalIntel: Generating Organizational Threat Intelligence from Global and Local Cyber Knowledge.
.- Intelligent Green Efficiency for Intrusion Detection.
.- A Privacy-Preserving Behavioral Authentication System.
.- Automated Exploration of Optimal Neural Network Structures for Deepfake Detection.
.- An Empirical Study of Black-box based Membership Inference Attacks on a Real-World Dataset.
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New trends of machine leaning and AI applied to cybersecurity
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.- ModelForge: Using GenAI to Improve the Development of Security Protocols.
.- Detecting Energy Attacks in the Battery-less Internet of Things .
.- Is Expert-Labeled Data Worth the Cost? Exploring Active and Semi-Supervised Learning Across Imbalance Scenarios in Financial Crime Detection.
.- ExploitabilityBirthMark: An Early Predictor of the Likelihood of Exploitation.
