Foundations and Practice of Security -
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Présentation Foundations And Practice Of Security Format Broché
- Livre Informatique
Résumé : .- 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.
Biographie: Sommaire:
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:
.- 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....
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