Toward Risk Thresholds for AI-Enabled Cyber Threats: Enhancing Decision-Making under Uncertainty with Bayesian Networks

Artificial intelligence AI is increasingly being used to augment and automate cyber operations, altering the scale, speed, and accessibility of malicious activity. These shifts raise urgent questions about when AI systems introduce unacceptable or intolerable cyber risk, and how risk thresholds...

Towards Reliable and Practical LLM Security Evaluations Via Bayesian Modelling

Before adopting a new large language model LLM architecture, it is critical to understand vulnerabilities accurately. Existing evaluations can be difficult to trust, often drawing conclusions from LLMs that are not meaningfully comparable, relying on heuristic inputs or employing metrics that fai...

Dynamic Causal Attack Graph Based Cyber-Security Risk Assessment Framework for CTCS System

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. However, the representation and assessment of the...

Ransomware Negotiation: Dynamics and Privacy-Preserving Mechanism Design

Ransomware attacks have become a pervasive and costly form of cybercrime, causing tens of millions of dollars in losses as organizations increasingly pay ransoms to mitigate operational disruptions and financial risks. While prior research has largely focused on proactive defenses, the...

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers

Ensemble-based attacks have been proven to be effective in enhancing adversarial transferability by aggregating the outputs of models with various architectures. However, existing research primarily focuses on refining ensemble weights or optimizing the ensemble path, overlooking the exploration ...

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,...

A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning

Federated learning FL enables collaborative model training across decentralized clients while preserving data privacy. However, its open-participation nature exposes it to data-poisoning attacks, in which malicious actors submit corrupted model updates to degrade the global model. Existing defens...

Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats

Protecting cyberspace requires not only advanced tools but also a shift in how we reason about threats, trust, and autonomy. Traditional cybersecurity methods rely on manual responses and brittle heuristics. To build proactive and intelligent defense systems, we need integrated theoretical...

Balancing Privacy and Utility in Correlated Data: a Study of Bayesian Differential Privacy

Privacy risks in differentially private DP systems increase significantly when data is correlated, as standard DP metrics often underestimate the resulting privacy leakage, leaving sensitive information vulnerable. Given the ubiquity of dependencies in real-world databases, this oversight poses a...

Vulnerability Assessment Combining CVSS Temporal Metrics and Bayesian Networks

Vulnerability assessment is a critical challenge in cybersecurity, particularly in industrial environments. This work presents an innovative approach by incorporating the temporal dimension into vulnerability assessment, an aspect neglected in existing literature. Specifically, this paper focuses...

Bayesian Perspective on Memorization and Reconstruction

We introduce a new Bayesian perspective on the concept of data reconstruction, and leverage this viewpoint to propose a new security definition that, in certain settings, provably prevents reconstruction attacks. We use our paradigm to shed new light on one of the most notorious attacks in the...

BSAGIoT: a Bayesian Security Aspect Graph for Internet of Things (IoT)

IoT is a dynamic network of interconnected things that communicate and exchange data, where security is a significant issue. Previous studies have mainly focused on attack classifications and open issues rather than presenting a comprehensive overview on the existing threats and vulnerabilities...

Modeling Interdependent Cybersecurity Threats Using Bayesian Networks: a Case Study on In-Vehicle Infotainment Systems

Cybersecurity threats are increasingly marked by interdependence, uncertainty, and evolving complexity challenges that traditional assessment methods such as CVSS, STRIDE, and attack trees fail to adequately capture. This paper reviews the application of Bayesian Networks BNs in cybersecurity ris...

Azure Sentinel uncovers the real threats hidden in billions of low fidelity signals

Cybercrime is as much a people problem as it is a technology problem. To respond effectively, the defender community must harness machine learning to compliment the strengths of people. This is the philosophy that undergirds Azure Sentinel. Azure Sentinel is a cloud-native SIEM that exploits...

SQL Injection Vulnerability in Bayesian Public Opinion Monitoring System

The Public Opinion Monitoring System is a product of Bayesian Beijing Information Consulting Co., Ltd. which is a market and Internet information research organization. A SQL injection vulnerability exists in the Bayesian Public Opinion Monitoring System. The vulnerability allows attackers to...

Debian Security Advisory DSA 2585-1 (bogofilter - buffer overflow)

A heap-based buffer overflow was discovered in bogofilter, a software package for classifying mail messages as spam or non-spam. Crafted mail messages with invalid base64 data could lead to heap corruption and, potentially, arbitrary code execution. OpenVAS Vulnerability Test $Id: deb25851.nasl...

[SECURITY] Fedora 18 Update: bogofilter-1.2.3-1.fc18

Bogofilter is a Bayesian spam filter. In its normal mode of operation, it takes an email message or other text on standard input, does a statistical check against lists of "good" and "bad" words, and returns a status code indicating whether or not the message is spam. Bogofilter is designed with...

USN-1667-1: bogofilter vulnerability

Julius Plenz discovered that bogofilter incorrectly handled certain invalid base64 code. By sending a specially crafted email, a remote attacker could exploit this and cause bogofilter to crash, resulting in a denial of service, or possibly execute arbitrary code...

Fedora Update for bogofilter FEDORA-2012-19705

Check for the Version of bogofilter OpenVAS Vulnerability Test Fedora Update for bogofilter FEDORA-2012-19705 Authors: System Generated Check Copyright: Copyright c 2012 Greenbone Networks GmbH, http://www.greenbone.net This program is free software; you can redistribute it and/or modify it under...

[SECURITY] Fedora 16 Update: bogofilter-1.2.3-1.fc16

Bogofilter is a Bayesian spam filter. In its normal mode of operation, it takes an email message or other text on standard input, does a statistical check against lists of "good" and "bad" words, and returns a status code indicating whether or not the message is spam. Bogofilter is designed with...