machine learning

Self-Configurable Cyber-Physical Intrusion Detection for Smart Homes Using Reinforcement Learning

The modern Internet of Things (IoT)-based smart home is a challenging environment to secure: devices change, new vulnerabilities are discovered and often remain unpatched, and different users interact with their devices differently and have different …

ARIES: A Novel Multivariate Intrusion Detection System for Smart Grid

The advent of the Smart Grid (SG) raises severe cybersecurity risks that can lead to devastating consequences. In this paper, we present a novel anomaly-based Intrusion Detection System (IDS), called ARIES (smArt gRid Intrusion dEtection System), …

A Taxonomy and Survey of Attacks Against Machine Learning

The majority of machine learning methodologies operate with the assumption that their environment is benign. However, this assumption does not always hold, as it is often advantageous to adversaries to maliciously modify the training (poisoning …

A Taxonomy and Survey of Cyber-Physical Intrusion Detection Approaches for Vehicles

With the growing threat of cyber and cyber-physical attacks against automobiles, drones, ships, driverless pods and other vehicles, there is also a growing need for intrusion detection approaches that can facilitate defence against such threats. …

Unsupervised Learning for Trustworthy IoT