Automatic characterization of exploitable faults : a machine learning approach

• Main Authors: Dasgupta, Pallab, Saha, Sayandeep, Jap, Dirmanto, Patranabis, Sikhar, Mukhopadhyay, Debdeep, Bhasin, Shivam
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Electrical and electronic engineering; Security; Block Cipher
• Online Access: https://hdl.handle.net/10356/104642; http://hdl.handle.net/10220/48070
• Institution: Nanyang Technological University

Characterizing the fault space of a cipher to filter out a set of faults potentially exploitable for fault attacks (FA), is a problem with immense practical value. A quantitative knowledge of the exploitable fault space is desirable in several applications, like security evaluation, cipher construct...