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Foundations and Practice of Security: 17th International Symposium, FPS 2024, Montréal, QC, Canada, December 911, 2024, Revised Selected Papers, Part II [Pehme köide]

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  • Formaat: Paperback / softback, 202 pages, kõrgus x laius: 235x155 mm, 48 Illustrations, color; 4 Illustrations, black and white; XV, 202 p. 52 illus., 48 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15533
  • Ilmumisaeg: 20-Jun-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031874951
  • ISBN-13: 9783031874956
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  • Formaat: Paperback / softback, 202 pages, kõrgus x laius: 235x155 mm, 48 Illustrations, color; 4 Illustrations, black and white; XV, 202 p. 52 illus., 48 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15533
  • Ilmumisaeg: 20-Jun-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031874951
  • ISBN-13: 9783031874956
Teised raamatud teemal:
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 0911, 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.
.- 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.