Description
Book Synopsis.- 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.
.- 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.
.- New trends of machine leaning and AI applied to cybersecurity.
.- 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.
