In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

In recent past years, Deep Learning presented an excellent performance in different areas
like image recognition, pattern matching, and even in cybersecurity. The Deep Learning has …

The proliferation and application of machine learning-based Intrusion Detection Systems
(IDS) have allowed for more flexibility and efficiency in the automated detection of cyber …

Industrial control systems (ICSs) are widely used and vital to industry and society. Their
failure can have severe impact on both the economy and human life. Hence, these systems …

Abstract Machine learning based Intrusion Detection Systems (IDS) allow flexible and
efficient automated detection of cyberattacks in Internet of Things (IoT) networks. However …

The high energy costs of neural network training and inference led to the use of acceleration
hardware such as GPUs and TPUs. While such devices enable us to train large-scale neural …

Smart Grid (SG) is the revolutionised power network characterised by a bidirectional flow of
energy and information between customers and suppliers. The integration of power …

Recent research demonstrated that the superficially well-trained machine learning (ML)
models are highly vulnerable to adversarial examples. As ML techniques are becoming a …

Recently, neural network (NN)-based methods, including autoencoders, have been
proposed for the detection of cyber attacks targeting industrial control systems (ICSs). Such …

Simple Summary This paper introduces simple, faster and more efficient versions of the
known targeted and untargeted Jacobian-based Saliency Map Attacks (JSMA). Despite …