Near-Field Microwave Sensing for Chip-Level Tamper Detection. [PDF]
Sensors (Basel)Saadat Safa M, Tajik S.
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Quantum adversarial machine learning: from classical adaptations to quantum-native methods. [PDF]
Artif Intell RevRazavi-Far R +8 more
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ChipletQuake: On-Die Digital Impedance Sensing for Chiplet and Interposer Verification. [PDF]
Sensors (Basel)Khalaj Monfared S +2 more
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Intelligent Electromagnetic Sensors for Non-Invasive Trojan Detection. [PDF]
Sensors (Basel), 2021 Chen E, Kan J, Yang BY, Zhu J, Chen V.
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Three-Basis Loop-Back QKD: A Passive Architecture for Secure and Scalable Quantum Mobile Networks. [PDF]
Entropy (Basel)Lizama-Pérez LA, Morales-Calvo P.
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Encryption chain based on measurement result and its applications on semi-quantum key distribution protocol. [PDF]
Sci Rep, 2022 Yang CW.
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Systematic Evaluation of Machine Learning and Deep Learning Models for IoT Malware Detection Across Ransomware, Rootkit, Spyware, Trojan, Botnet, Worm, Virus, and Keylogger. [PDF]
Sensors (Basel)Maghanaki M +3 more
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Hardware reverse engineering and its implications for hardware protections and hardware trojans
Mikrochips bilden das Rückgrat der digitalen Gesellschaft, doch globale, komplexe Lieferketten erhöhen das Risiko böswilliger Hardware-Manipulationen. Hardware-Reverse-Engineering (HRE) kann Angriffe wie Hardware-Trojaner aufdecken, ermöglicht jedoch zugleich IP-Diebstahl und Angriffsvorbereitungen.
openaire +2 more sources
Cyber-physical security of biochips: A perspective. [PDF]
BiomicrofluidicsBaban NS +4 more
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TCF-CBM: a three-stage collaborative poisoned sample filtering method based on composite backdoor mechanism. [PDF]
Sci RepHuang W +5 more
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