FDM: A Framework for Decision-Making to Build ML-Based Malware Detection Systems

Selecting appropriate machine learning ML configurations for malware detection is a complex, multi-criteria problem. Model choice, feature engineering, and update mechanisms must jointly satisfy operational constraints that vary across deployment contexts. This paper proposes the Framework for...

LITE-SOC: Lightweight Security Operations Center Simulator for Cybersecurity Education

This innovative practice WIP paper describes LITE-SOC, a lightweight web-based Security Operations Center SOC simulator designed for instructor-led cybersecurity education. SOC analysts must triage large volumes of alerts, separate genuine threats from false positives, and communicate decisions...

What Security and Privacy Transparency Users Need from Consumer-Facing Generative AI

Users increasingly rely on consumer-facing generative AI GenAI for tasks ranging from everyday needs to sensitive use cases. Yet, it remains unclear whether and how existing security and privacy S&P communications in GenAI tools shape users' adoption decisions and subsequent experiences...

NASimJax: GPU-Accelerated Policy Learning Framework for Penetration Testing

Penetration testing, the practice of simulating cyberattacks to identify vulnerabilities, is a complex sequential decision-making task that is inherently partially observable and features large action spaces. Training reinforcement learning RL policies for this domain faces a fundamental...

Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks

Due to the scalability and portability, low-altitude intelligent networks LAINs are essential in various fields such as surveillance and disaster rescue. However, in LAINs, unmanned aerial vehicles UAVs are characterized by the distributed topology and high mobility, thus vulnerable to security...

ROC vs. CTEM: How a Risk Operations Center Evolves Beyond Continuous Threat Exposure Management in 2026

Key Takeaways: The Essentials of ROC vs. CTEM What is a ROC? A risk operations center ROC is a centralized command hub that unifies cyber risk management across security, IT, and compliance. It uses agentic AI to provide a real-time view of business risk, prioritize what matters, and then automat...

AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection

Secure code review is critical at the pre-commit stage, where vulnerabilities must be caught early under tight latency and limited-context constraints. Existing SAST-based checks are noisy and often miss immature, context-dependent vulnerabilities, while standalone Large Language Models LLMs are...

Decision-Aware Trust Signal Alignment for SOC Alert Triage

Detection systems that utilize machine learning are progressively implemented at Security Operations Centers SOCs to help an analyst to filter through high volumes of security alerts. Practically, such systems tend to reveal probabilistic results or confidence scores which are ill-calibrated and...

Cyberscurity Threats and Defense Mechanisms in IoT Network

The rapid proliferation of Internet of Things IoT technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a comprehensive analysis of vulnerabilities, threats, and defense...

PentestEval: Benchmarking LLM-Based Penetration Testing with Modular and Stage-Level Design

Penetration testing is essential for assessing and strengthening system security against real-world threats, yet traditional workflows remain highly manual, expertise-intensive, and difficult to scale. Although recent advances in Large Language Models LLMs offer promising opportunities for...

When AI Becomes the Heart of Security: Powering a Future You Can Trust

Helping teams see clearly, decide wisely, and move safely...

From Misinformation to Climate Crisis: Navigating Vulnerabilities in the Cyber-Physical-Social Systems

Within the cyber-physical-social-climate nexus, all systems are deeply interdependent: cyber infrastructure facilitates communication, data processing, and automation across physical systems such as power grids and networks, while social infrastructure provides the human capital and societal norm...

CVE-2025-11034

A vulnerability was found in Dibo Data Decision Making System up to 2.7.0. The affected element is the function downloadImpTemplet of the file /common/dep/commondep.action.jsp. The manipulation of the argument filePath results in path traversal. It is possible to launch the attack remotely. The...

PT-2025-39672

Name of the Vulnerable Software and Affected Versions Dibo Data Decision Making System versions prior to 2.7.0 Description A path traversal issue exists in Dibo Data Decision Making System. The issue is related to the manipulation of the filePath argument within the downloadImpTemplet function...

[Extended] Ethics in Computer Security Research: a Data-Driven Assessment of the Past, the Present, and the Possible Future

Ethical questions are discussed regularly in computer security. Still, researchers in computer security lack clear guidance on how to make, document, and assess ethical decisions in research when what is morally right or acceptable is not clear-cut. In this work, we give an overview of the...

Maturing the cyber threat intelligence program

The Cyber Threat Intelligence Capability Maturity Model CTI-CMM helps organizations assess and improve their threat intelligence programs by outlining 11 key areas and specific missions where CTI can support decision-making. The model describes four levels of maturity, guiding teams from basic, a...

LLMs in Cybersecurity: Friend or Foe in the Human Decision Loop?

Large Language Models LLMs are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote over-reliance and homogenize decisions. In this paper, we investigate...

Adaptive Malware Detection Using Sequential Feature Selection: a Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification

Traditional malware detection methods exhibit computational inefficiency due to exhaustive feature extraction requirements, creating accuracy-efficiency trade-offs that limit real-time deployment. We formulate malware classification as a Markov Decision Process with episodic feature acquisition a...

Keeping Pace and Embracing Emerging Technologies

Trend Micro and the NEOM McLaren Formula E Team stay ahead of the curve by embracing new technologies, fostering a no-blame culture, and making split-second decisions in high-stakes environments...

CVE-2025-47292 Cap Collectif vulnerable to insecure deserialization leading to remote code execution

Cap Collectif is an online decision making platform that integrates several tools. Before commit 812f2a7d271b76deab1175bdaf2be0b8102dd198, the DebateAlternateArgumentsResolver deserializes a Cursor, allowing any classes and which can be controlled by unauthenticated user. Exploitation of this...