Neuro-memristive Circuits for Edge Computing: A review

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks and open problems in the field of neuro-memristive circuits for edge computing

HARDWARE ATTACK DETECTION AND PREVENTION FOR CHIP SECURITY

Hardware security is a serious emerging concern in chip designs and applications. Due to the globalization of the semiconductor design and fabrication process, integrated circuits (ICs, a.k.a. chips) are becoming increasingly vulnerable to passive and active hardware attacks. Passive attacks on chips result in secret information leaking while active attacks cause IC malfunction and catastrophic system failures. This thesis focuses on detection and prevention methods against active attacks, in particular, hardware Trojan (HT). Existing HT detection methods have limited capability to detect small-scale HTs and are further challenged by the increased process variation. We propose to use differential Cascade Voltage Switch Logic (DCVSL) method to detect small HTs and achieve a success rate of 66% to 98%. This work also presents different fault tolerant methods to handle the active attacks on symmetric-key cipher SIMON, which is a recent lightweight cipher. Simulation results show that our Even Parity Code SIMON consumes less area and power than double modular redundancy SIMON and Reversed-SIMON, but yields a higher fault -detection-failure rate as the number of concurrent faults increases. In addition, the emerging technology, memristor, is explored to protect SIMON from passive attacks. Simulation results indicate that the memristor-based SIMON has a unique power characteristic that adds new challenges on secrete key extraction