6 papers · 1 filter
Evaluating Open-Weight LLMs for Generating Structured Threat Information for Autonomous Vehicle Vulnerabilities
Md Erfan, Ahmed Ryan, Md Kamal Hossain Chowdhury +1
Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and…
Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation
Abir Ashab Niloy, Ahmed Ryan, Imamul Hossain Rafi +2
Multi-stage cyberattacks span system, network, and browser logs. Detecting them requires correlating events across all three sources. Machine learning methods can learn these cross…
Evaluating Open-Source LLMs for Multi-Label ATT&CK Technique Classification on CTI Reports
Ahmed Ryan, Saad Sakib Noor, Md Erfan +3
Classifying Cyber Threat Intelligence (CTI) using MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) is essential for proactive defense, but historically required…
An Evaluation of Large Language Models for Detection of Malicious Python Packages
Ahmed Ryan, Ibrahim Khalil, Abdullah Al Jahid +4
Modern software development relies on open-source package repositories. Attackers use these to distribute malicious packages. Large Language Models (LLMs) can automatically detect…
Unveiling Malicious Logic: Towards a Statement-Level Taxonomy and Dataset for Securing Python Packages
Ahmed Ryan, Junaid Mansur Ifti, Md Erfan +2
The widespread adoption of open-source ecosystems enables developers to integrate third-party packages, but also exposes them to malicious packages crafted to execute harmful behav…
Security Vulnerabilities in Software Supply Chain for Autonomous Vehicles
Md Wasiul Haque, Md Erfan, Sagar Dasgupta +2
The interest in autonomous vehicles (AVs) for critical missions, including transportation, rescue, surveillance, reconnaissance, and mapping, is growing rapidly due to their signif…