The massive increase in actuators, industrial devices, health care devices, and sensors, has
led to the implementation of the Internet of Things (IoT), fast and flexible information …

Currently, machine learning (ML) techniques are at the heart of smart cyber-physical
systems (CPSs) and Internet-of-Things (loT). This article discusses various challenges and …

The ever-increasing demand for sophisticated cyber-physical systems (CPS), combined with
the fabless model, led to vulnerability exploits in the IC supply chain, especially the insertion …

Due to their proven efficiency, machine-learning systems are deployed in a wide range of
complex real-life problems. More specifically, Spiking Neural Networks (SNNs) emerged as …

Traditional learning-based approaches for runtime hardware Trojan (HT) detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …

Malicious alteration in an IC design is generally referred to as hardware Trojans (HTs). The
involvement of multiple entities in the VLSI design cycle has made the process of HT …

Performance of the compute-intensive multichip platforms such as micro-servers and
embedded systems are limited by the latency and power hungry chip-to-chip …

Static or leakage power, which is especially prominent in advanced technology nodes,
enables so-called static power side-channel attacks (S-PSCA). While countermeasures …

This paper proposes an on-the-fly encryption system that consists of a lightweight encryption
architecture and a key-exchange algorithm for secure on-chip communications. The …

Compute-intensive platforms such as micro-servers and embedded systems have already
undergone a shift from a single-chip to multichip architecture to achieve better yield and …