Abstract Side-channel attacks have become a realistic threat to implementations of cryptographic algorithms, especially with the help deep-learning techniques. The majority recently demonstrated side-channel use single neural network classifier extract secret from algorithms. potential benefits combining multiple classifiers using ensemble learning method not been fully explored in attack’s con...

Side-channel analysis (SCA) is a class of attacks on the physical implementation cipher, which enables extraction confidential key information by exploiting unintended leaks generated device. In recent years, researchers have observed that neural networks (NNs) can be utilized to perform highly effective SCA profiling, even against countermeasure-hardened targets. This study investigates new ap...

SIMON is a block cipher developed to provide flexible security options for lightweight hardware applications such as the Internet-of-things (IoT). Safeguarding resource-constrained from side-channel attacks poses significant challenge. Adiabatic circuit operation has recently received attention due ultra-low power consumption. In this work, charge-based methodology mount correlation analysis (C...

Emerging Non-Volatile Memories (NVMs) such as Magnetic RAM (MRAM), Spin-Transfer Torque (STTRAM), Phase Change Memory (PCM) and Resistive (RRAM) are very promising due to their low (static) power operation, high scalability performance. However, these memories bring new threats data security. In this paper, we investigate vulnerability against Side Channel Attack (SCA). We assume that the adver...

In-memory computing (IMC) architectures provide a much needed solution to energy-efficiency barriers posed by Von-Neumann computing. The functions implemented in such in-memory are often proprietary and constitute confidential intellectual property (IP). Our studies indicate that IMC using resistive RAM (RRAM) susceptible side channel attack (SCA). Unlike the conventional SCAs aimed leak privat...