Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

The growing reliance on Low-Earth Orbit LEO satellite communication systems has increased the need for intelligent methods capable of detecting cyberattacks across complex and dynamic space environments. Unlike conventional network intrusion detection, satellite systems generate heterogeneous...

Benchmarking Cyberattack Detection in Electric Vehicle Charging Infrastructure with Benign User Updates

Cyberattack detection in electric vehicle charging infrastructure is complicated by legitimate post-activation revisions to requested energy and departure time. Charging manipulation attacks can exploit the same interface and variables; therefore, detecting a request change alone does not establi...

Tool Demo: Topology Analysis with GPML for Detection of Cyberattacks in Water Distribution Networks

Water distribution networks depends on industrial control systems to integrate the physical process with communication network, making them vulnerable to cyberattacks that alter the traffic pattern and network behavior. Traditional detection approaches that rely on raw traffic or protocol...

S3CDM: A Secret-Sharing-Scheme-Based Cyberattack Detection Model and Its Simulation Implementation

We design and develop a secret-sharing-scheme-based cyberattack detection modelS3CDMthat can detect unauthorized or illegal activities especially insider attacks and protect sensitive information within complex network infrastructures of large organizations. The model splits a secret among a grou...

Large Language Models for Detecting Cyberattacks on Smart Grid Protective Relays

This paper presents a large language model LLM-based framework for detecting cyberattacks on transformer current differential relays TCDRs, which, if undetected, may trigger false tripping of critical transformers. The proposed approach adapts and fine-tunes compact LLMs such as DistilBERT to...

Causal Graph Profiling Via Structural Divergence for Robust Anomaly Detection in Cyber-Physical Systems

With the growing complexity of cyberattacks targeting critical infrastructures such as water treatment networks, there is a pressing need for robust anomaly detection strategies that account for both system vulnerabilities and evolving attack patterns. Traditional methods -- statistical,...

Differential Privacy for Regulatory Compliance in Cyberattack Detection on Critical Infrastructure Systems

Industrial control systems are a fundamental component of critical infrastructure networks CIN such as gas, water and power. With the growing risk of cyberattacks, regulatory compliance requirements are also increasing for large scale critical infrastructure systems comprising multiple utility...

Explainable Machine Learning for Cyberattack Identification from Traffic Flows

The increasing automation of traffic management systems has made them prime targets for cyberattacks, disrupting urban mobility and public safety. Traditional network-layer defenses are often inaccessible to transportation agencies, necessitating a machine learning-based approach that relies sole...

Detection of ‘Leave Behinds’ From Nation-State Actors

Who left the backdoor open? By Trellix · March 28, 2022 In our recent report, In the Crosshairs: Companies and Nation-State Cyber Threats, over 800 IT decision makers from around the world were interviewed on their experiences with nation-state cyber attacks. One of the questions sought to...