Related papers: Intuitive visualization of the intelligence for th…

In this work we present a prototype for simulating computer network attacks. Our objective is to simulate large networks (thousands of hosts, with applications and vulnerabilities) while remaining realistic from the attacker's point of…

It is an increasingly common practice in several natural and social sciences to rely on network visualisations both as heuristic tools to get a first overview of relational datasets and as a way to offer an illustration of network analysis…

Complexity science affords a number of novel tools for examining terrorism, particularly network analysis and NK-Boolean fitness landscapes. The following paper explores various aspects of terrorist networks which can be illuminated through…

Cyber security attacks have become increasingly complex over time, with various phases of their kill chain, involving binaries, scripts, documents, executed commands, vulnerabilities, or network traffic. We propose a tool, GView, that is…

This article considers a short survey of basic methods of social networks analysis, which are used for detecting cyber threats. The main types of social network threats are presented. Basic methods of graph theory and data mining, that…

Characterizing attacker behavior with respect to Cyber-Physical Systems is important to assuring the security posture and resilience of these systems. Classical cyber vulnerability assessment approaches rely on the knowledge and experience…

Visualization has long been seen as a dependable and trustworthy tool for carrying out analysis and communication tasks -- a view reinforced by the growing interest in applying it to socially positive ends. However, despite the benign light…

Cyber criminality activities are changing and becoming more and more professional. With the growth of financial flows through the Internet and the Information System (IS), new kinds of thread arise involving complex scenarios spread within…

Political astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Common approaches examining these phenomena focus on broad campaigns rather than the small groups responsible. To reveal…

The rate of terror attacks has surged over the past decade, resulting in the tragic and senseless loss or alteration of numerous lives. Offenders behind mass shootings, bombings, or other domestic terrorism incidents have historically…

Network defenders face a steady stream of attacks, observed as raw Intrusion Detection System (IDS) alerts. The sheer volume of alerts demands prioritization, typically based on high-level risk classifications. This work expands the scope…

Political misinformation, astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Many previous approaches examining these phenomena have focused on broad campaigns rather than the small…

Social Media platforms (e.g., Twitter, Facebook, etc.) are used heavily by public to provide news, opinions, and reactions towards events or topics. Integrating such data with the event or topic factual data could provide a more…

The definition of similarity is a key prerequisite when analyzing complex data types in data mining, information retrieval, or machine learning. However, the meaningful definition is often hampered by the complexity of data objects and…

In temporal ( event-based ) networks, time is a continuous axis, with real-valued time coordinates for each node and edge. Computing a layout for such graphs means embedding the node trajectories and edge surfaces over time in a 2D+t space,…

Most of the intrusion detection methods in computer networks are based on traffic flow characteristics. However, this approach may not fully exploit the potential of deep learning algorithms to directly extract features and patterns from…

This paper addresses the challenge of viewing and navigating Bayesian networks as their structural size and complexity grow. Starting with a review of the state of the art of visualizing Bayesian networks, an area which has largely been…

Hands-on training sessions become a standard way to develop and increase knowledge in cybersecurity. As practical cybersecurity exercises are strongly process-oriented with knowledge-intensive processes, process mining techniques and models…

Analysis of criminal networks is inherently difficult because of the nature of the topic. Criminal networks are covert and most of the information is not publicly available. This leads to small datasets available for analysis. The available…

Social media platforms, particularly Twitter, have become pivotal arenas for influence campaigns, often orchestrated by state-sponsored information operations (IOs). This paper delves into the detection of key players driving IOs by…