On Attacking Locking SIB based IJTAG Architecture

Abstract

The IEEE 1687 standard, which is commonly used for efficient access of on-chip instruments, could be exploited by an intruder and thus needs to be secured. One of the techniques to alleviate the vulnerability of 1687 network is to use a secure access protocol that is based on licensed access software, Chip ID and locking SIB. A licensed access software is generally used to gain control of the embedded instruments and use them as per requirement. In this paper, a successful attack using various machine learning algorithms has been instigated on secure access protocol scheme. It is demonstrated that machine learning algorithms have the potential of breaching the secure communication between the access software and the board and hence access the sensitive instruments. Furthermore, Random Forest significantly outperforms the other models in terms of breaking the security.