Asadizanjani / Xi / Tehranipoor Materials for Electronics Security and Assurance

1. Auflage 2024
ISBN: 978-0-443-18543-4
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 400 Seiten

Materials for Electronics Security and Assurance reviews the properties of materials that could enable devices that are resistant to tampering and manipulation. The book discusses recent advances in materials synthesis and characterization techniques for security applications. Topics addressed include anti-reverse engineering, detection, prevention, track and trace, fingerprinting, obfuscation, and how materials could enable these security solutions. The book introduces opportunities and challenges and provides a clear direction of the requirements for material-based solutions to address electronics security challenges. It is suitable for materials scientists and engineers who seek to enable future research directions, current computer and hardware security engineers who want to enable materials selection, and as a way to inspire cross-collaboration between both communities. - Discusses materials as enablers to provide electronics assurance, counterfeit detection/protection, and fingerprinting - Provides an overview of benefits and challenges of materials-based security solutions to inspire future materials research directions - Includes an introduction to material perspectives on hardware security to enable cross collaboration between materials, design, and testing

Navid Asadi is an assistant professor in the department of electrical and computer engineering at university of Florida. His research is mainly focused on physical inspection of electronics from device to system level. He investigates novel techniques for integrated circuits counterfeit detection/prevention, system and chip level reverse engineering, anti-reverse engineering, invasive and semi-invasive physical attacks, integrity analysis, etc. using advanced inspection methods including but not limited to 3D X-ray microscopy, Optical imaging, scanning electron microscopy (SEM), focused ion beams (FIBs), THz imaging, etc. in combination with image processing and machine learning algorithms to make the inspection process intelligent and independent from human. He has received several best paper awards and is the co-founder of the IEEE-PAINE conference.

Autoren/Hrsg.

Asadizanjani, Navid

Xi, Chengjie

Tehranipoor, Mark M.