Cryptography and Embedded Systems Security

This textbook provides an all-in-one approach for learning about hardware security of cryptographic systems. It gives the necessary background on mathematics that is used for the construction of symmetric and public-key cryptosystems. Then, it introduces the most commonly used encryption algorithms that can be found on a wide variety of embedded devices to provide confidentiality, integrity, and authenticity of the messages/data. Finally, it provides theoretical and practical details on the two most common attack methods in hardware security - side-channel attacks, and fault injection attacks, together with the protection methods used against both.

• Starts from the basics and does not require prior knowledge of cryptography or mathematical background
• Enables readers to implement symmetric block ciphers and RSA with an emphasis on hardware security
• Covers the classical as well as state-of-the-art fault attacks and side-channel attacks

Auteur

Xiaolu Hou is currently an Assistant Professor at the Faculty of Informatics and Information Technologies, Slovak University of Technology, Slovakia. She received her Ph.D. degree in mathematics from Nanyang Technological University (NTU), Singapore, in 2017. Her research focus is on hardware security of both cryptographic and AI implementations. She designs and develops novel attacks and protection techniques on protocol, hardware and software levels.

Jakub Breier is currently a Senior Cyber Security Manager at TTControl, Vienna, Austria.. Before that, he worked at Silicon Austria Labs, Graz on deep learning security, Nanyang Technological University, Singapore on hardware security and at Underwriters Laboratories, Singapore on security evaluation of embedded devices. He received his Ph.D. in Applied Informatics from Slovak University of Technology (STU), Slovakia in 2013.

His research topics include fault and side-channel analysis methods and countermeasures, advanced fault injection techniques, design of cryptographic primitives, and deep learning security.