相关论文: Model-based Cybersecurity Analysis: Past Work and …

Joint safety and security analysis of cyber-physical systems is a necessary step to correctly capture inter-dependencies between these properties. Attack-Fault Trees represent a combination of dynamic Fault Trees and Attack Trees and can be…

As cybersecurity threats continue to evolve, the need for advanced tools to analyze and understand complex cyber environments has become increasingly critical. Graph theory offers a powerful framework for modeling relationships within cyber…

The increase in scale of cyber networks and the rise in sophistication of cyber-attacks have introduced several challenges in intrusion detection. The primary challenge is the requirement to detect complex multi-stage attacks in realtime by…

Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essential for ensuring system resilience. Graph-based approaches have become increasingly important for…

Identification of cyber threats is one of the essential tasks for security teams. Currently, cyber threats can be identified using knowledge organized into various formats, enumerations, and knowledge bases. This paper studies the current…

Cyber threats affect all kinds of organisations. Risk analysis is an essential methodology for cybersecurity as it allows organisations to deal with the cyber threats potentially affecting them, prioritise the defence of their assets and…

Evolving cybersecurity threats in complex cyber-physical systems pose significant risks to system functionality and safety. This experience report introduces ACTISM (Automotive Consequence-Driven and Threat-Informed Security Modelling), an…

In order to improve the resilience of computer infrastructure against cyber attacks and finding ways to mitigate their impact we need to understand their structure and dynamics. Here we propose a novel network-based influence spreading…

As cyber threats grow increasingly sophisticated, reinforcement learning (RL) is emerging as a promising technique to create intelligent and adaptive cyber defense systems. However, most existing autonomous defensive agents have overlooked…

APT (Advanced Persistent Threat) with the characteristics of persistence, stealth, and diversity is one of the greatest threats against cyber-infrastructure. As a countermeasure, existing studies leverage provenance graphs to capture the…

Graph-based classification methods are widely used for security and privacy analytics. Roughly speaking, graph-based classification methods include collective classification and graph neural network. Evading a graph-based classification…

The escalating complexity and volume of cyberattacks demand proactive detection strategies that go beyond traditional rule-based systems. This paper presents a phase-aware, multi-model machine learning framework that emulates adversarial…

In this paper, we present CrimeGAT, a novel application of Graph Attention Networks (GATs) for predictive policing in criminal networks. Criminal networks pose unique challenges for predictive analytics due to their complex structure,…

According to the World Economic Forum, cyber attacks are considered as one of the most important sources of risk to companies and institutions worldwide. Attacks can target the network, software, and/or hardware. During the past years, much…

A cyber-attack is a malicious attempt by experienced hackers to breach the target information system. Usually, the cyber-attacks are characterized as hybrid TTPs (Tactics, Techniques, and Procedures) and long-term adversarial behaviors,…

The document provides an in-depth analysis of the main attack chain models used in cybersecurity, including the Lockheed Martin Cyber Kill Chain framework, the MITER ATT&CK framework, the Diamond model, and the IoTKC, focusing on their…

Protecting the security of the train control system is a critical issue to ensure the safe and reliable operation of high-speed trains. Scientific modeling and analysis for the security risk is a promising way to guarantee system security.…

The advancement of graph-based malware analysis is critically limited by the absence of large-scale datasets that capture the inherent hierarchical structure of software. Existing methods often oversimplify programs into single level…

Deep-learning based computer vision models have proved themselves to be ground-breaking approaches to human activity recognition (HAR). However, most existing works are dedicated to improve the prediction accuracy through either creating…

The rise of advanced persistent threats (APTs) has marked a significant cybersecurity challenge, characterized by sophisticated orchestration, stealthy execution, extended persistence, and targeting valuable assets across diverse sectors.…