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Dr. Basel Halak is the director of the embedded systems and IoT program at the University of Southampton, a visiting scholar at the Technical University of Kaiserslautern, a visiting professor at the Kazakh-British Technical University, an industrial fellow of the royal academy of engineering, and a national teaching fellow of the Advance Higher Education(HE) Academy. Dr. Halak's publications include over 80-refereed conference and journal papers and authored four books, including the first textbook on Physically Unclonable Functions. His research expertise includes evaluation of the security of hardware devices, development of countermeasures, mathematical formalism of reliability issues in CMOS circuits (e.g. crosstalk, radiation, aging), and the use of fault tolerance techniques to improve the robustness of electronics systems against such issues. Dr. Halak lectures on digital design, Secure Hardware, and Cryptography. Dr. Halak serves on several technical program committees such as HOST, IEEE DATE, IVSW, and DAC. He is an associate editor of IEEE access and an editor of the IET circuit devices and system journal. He is also a member of the hardware security-working group of the World Wide Web Consortium (W3C).
Discusses emerging technologies used to develop intelligent tamper detection techniques, using machine learning
Includes a comprehensive summary of how machine learning is used to combat IC counterfeit and to detect Trojans
Describes how machine learning algorithms are used to enhance the security of physically unclonable functions (PUFs)
Introduction.- Machine Learning for Tamper Detection.- Machine Learning for IC Counterfeit Detection and Prevention.- Machine Learning for Secure PUF Design.- Machine Learning for Malware Analysis.- Machine Learning for Detection of Software Attacks.- Conclusions and Future Opportunities.
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Nachrichtentechnik |
Genre: | Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xv
160 S. 27 s/w Illustr. 39 farbige Illustr. 160 p. 66 illus. 39 illus. in color. |
ISBN-13: | 9783030941772 |
ISBN-10: | 3030941779 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Redaktion: | Halak, Basel |
Herausgeber: | Basel Halak |
Auflage: | 1st ed. 2022 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 241 x 160 x 16 mm |
Von/Mit: | Basel Halak |
Erscheinungsdatum: | 23.04.2022 |
Gewicht: | 0,436 kg |
Dr. Basel Halak is the director of the embedded systems and IoT program at the University of Southampton, a visiting scholar at the Technical University of Kaiserslautern, a visiting professor at the Kazakh-British Technical University, an industrial fellow of the royal academy of engineering, and a national teaching fellow of the Advance Higher Education(HE) Academy. Dr. Halak's publications include over 80-refereed conference and journal papers and authored four books, including the first textbook on Physically Unclonable Functions. His research expertise includes evaluation of the security of hardware devices, development of countermeasures, mathematical formalism of reliability issues in CMOS circuits (e.g. crosstalk, radiation, aging), and the use of fault tolerance techniques to improve the robustness of electronics systems against such issues. Dr. Halak lectures on digital design, Secure Hardware, and Cryptography. Dr. Halak serves on several technical program committees such as HOST, IEEE DATE, IVSW, and DAC. He is an associate editor of IEEE access and an editor of the IET circuit devices and system journal. He is also a member of the hardware security-working group of the World Wide Web Consortium (W3C).
Discusses emerging technologies used to develop intelligent tamper detection techniques, using machine learning
Includes a comprehensive summary of how machine learning is used to combat IC counterfeit and to detect Trojans
Describes how machine learning algorithms are used to enhance the security of physically unclonable functions (PUFs)
Introduction.- Machine Learning for Tamper Detection.- Machine Learning for IC Counterfeit Detection and Prevention.- Machine Learning for Secure PUF Design.- Machine Learning for Malware Analysis.- Machine Learning for Detection of Software Attacks.- Conclusions and Future Opportunities.
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Nachrichtentechnik |
Genre: | Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xv
160 S. 27 s/w Illustr. 39 farbige Illustr. 160 p. 66 illus. 39 illus. in color. |
ISBN-13: | 9783030941772 |
ISBN-10: | 3030941779 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Redaktion: | Halak, Basel |
Herausgeber: | Basel Halak |
Auflage: | 1st ed. 2022 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 241 x 160 x 16 mm |
Von/Mit: | Basel Halak |
Erscheinungsdatum: | 23.04.2022 |
Gewicht: | 0,436 kg |