In-Context Autonomous Network Incident Response: An End-To-End Large Language Model Agent Approach

Rapidly evolving cyberattacks demand incident response systems that can autonomously learn and adapt to changing threats. Prior work has extensively explored the reinforcement learning approach, which involves learning response strategies through extensive simulation of the incident. While this...

A Survey of Security Challenges and Solutions for UAS Traffic Management (UTM) and Small Unmanned Aerial Systems (SUAS)

The rapid growth of small Unmanned Aerial Systems sUAS for civil and commercial missions has intensified concerns about their resilience to cyber-security threats. Operating within the emerging UAS Traffic Management UTM framework, these lightweight and highly networked platforms depend on secure...

CVE-2005-1908

Perception LiteWeb allows remote attackers to bypass access controls for files via an extra leading / slash or leading \ backslash in the URL...

Failure Analysis of Safety Controllers in Autonomous Vehicles under Object-Based LiDAR Attacks

Autonomous vehicles rely on LiDAR based perception to support safety critical control functions such as adaptive cruise control and automatic emergency braking. While previous research has shown that LiDAR perception can be manipulated through object based spoofing and injection attacks, the impa...

Security Risks of Agentic Vehicles: A Systematic Analysis of Cognitive and Cross-Layer Threats

Agentic AI is increasingly being explored and introduced in both manually driven and autonomous vehicles, leading to the notion of Agentic Vehicles AgVs, with capabilities such as memory-based personalization, goal interpretation, strategic reasoning, and tool-mediated assistance. While framework...

A Visual Perception-Based Tunable Framework and Evaluation Benchmark for H.265/HEVC ROI Encryption

ROI selective encryption, as an efficient privacy protection technique, encrypts only the key regions in the video, thereby ensuring security while minimizing the impact on coding efficiency. However, existing ROI-based video encryption methods suffer from insufficient flexibility and lack of a...

Evaluation of Vision-LLMs in Surveillance Video

The widespread use of cameras in our society has created an overwhelming amount of video data, far exceeding the capacity for human monitoring. This presents a critical challenge for public safety and security, as the timely detection of anomalous or criminal events is crucial for effective...

The Cybersecurity Perception Gap: Why Executives and Practitioners See Risk Differently

Does your organization suffer from a cybersecurity perception gap? Findings from the Bitdefender 2025 Cybersecurity Assessment suggest the answer is probably "yes" — and many leaders may not even realize it. This disconnect matters. Small differences in perception today can evolve into major blin...

The Cybersecurity Perception Gap: Why Executives and Practitioners See Risk Differently

Does your organization suffer from a cybersecurity perception gap? Findings from the Bitdefender 2025 Cybersecurity Assessment suggest the answer is probably “yes” — and many leaders may not even realize it. This disconnect matters. Small differences in perception today can evolve into major blin...

Can You Trust What You See? Alpha Channel No-Box Attacks on Video Object Detection

As object detection models are increasingly deployed in cyber-physical systems such as autonomous vehicles AVs and surveillance platforms, ensuring their security against adversarial threats is essential. While prior work has explored adversarial attacks in the image domain, those attacks in the...

Future G Network'S New Reality: Opportunities and Security Challenges

Future G network's new reality is a widespread cyber-physical environment created by Integrated Sensing and Communication ISAC. It is a crucial technology that transforms wireless connections into ubiquitous sensors. ISAC unlocks transformative new capabilities, powering autonomous systems,...

EUVD-2002-2171

Malware in sbrugna...

EUVD-2002-1965

Malware in sbrugna...

EUVD-2005-1910

Malware in sbrugna...

EUVD-2024-35768

Malicious code in bioql PyPI...

EUVD-2024-45515

Malicious code in bioql PyPI...

SoK: Measuring What Matters for Closed-Loop Security Agents

Cybersecurity is a relentless arms race, with AI driven offensive systems evolving faster than traditional defenses can adapt. Research and tooling remain fragmented across isolated defensive functions, creating blind spots that adversaries exploit. Autonomous agents capable of integrating, explo...

Integrated Simulation Framework for Adversarial Attacks on Autonomous Vehicles

Autonomous vehicles AVs rely on complex perception and communication systems, making them vulnerable to adversarial attacks that can compromise safety. While simulation offers a scalable and safe environment for robustness testing, existing frameworks typically lack comprehensive supportfor...

Connected and Exposed: Cybersecurity Risks, Regulatory Gaps, and Public Perception in Internet-Connected Vehicles

The rapid advancement of Internet-connected vehicle technologies has introduced a new era of smart mobility, while simultaneously raising significant cybersecurity and privacy concerns. This paper explores the evolving threat landscape associated with connected vehicles, focusing on risks such as...

False Reality: Uncovering Sensor-Induced Human-VR Interaction Vulnerability

Virtual Reality VR techniques, serving as the bridge between the real and virtual worlds, have boomed and are widely used in manufacturing, remote healthcare, gaming, etc. Specifically, VR systems offer users immersive experiences that include both perceptions and actions. Various studies have...