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Beskrivning
AI has become an emerging technology to assess security and privacy, with many challenges and potential solutions at the algorithm, architecture, and implementation levels.
AI for Cryptography.- Artificial Intelligence for the Design of Symmetric Cryptographic Primitives.- Traditional Machine Learning Methods for Side-Channel Analysis.- Deep Learning on Side-Channel Analysis.- Artificial Neural Networks and Fault Injection Attacks.- Physically Unclonable Functions and AI: Two Decades of Marriage.- AI for Authentication and Privacy.- Privacy-Preserving Machine Learning using Cryptography.- Machine Learning Meets Data Modification: the Potential of Pre-processing for Privacy Enhancement.- AI for Biometric Authentication Systems.- Machine Learning and Deep Learning for Hardware Fingerprinting. - AI for Intrusion Detection.- Intelligent Malware Defenses.- Open-World Network Intrusion Detection.- Security of AI.- Adversarial Machine Learning.- Deep Learning Backdoors. - On Implementation-level Security of Edge-based Machine Learning Models.
Jianying Zhou, Lejla Batina, Zengpeng Li, Jingqiang Lin, Eleonora Losiouk, Suryadipta Majumdar, Daisuke Mashima, Weizhi Meng, Stjepan Picek, Mohammad Ashiqur Rahman, Jun Shao, Masaki Shimaoka, Ezekiel Soremekun, Chunhua Su, Je Sen Teh, Aleksei Udovenko, Cong Wang, Leo Zhang, Yury Zhauniarovich