5 papers
Optimizing Code Embeddings and ML Classifiers for Python Source Code Vulnerability Detection
Talaya Farasat, Joachim Posegga
In recent years, the growing complexity and scale of source code have rendered manual software vulnerability detection increasingly impractical. To address this challenge, automate…
SafePyScript: A Web-Based Solution for Machine Learning-Driven Vulnerability Detection in Python
Talaya Farasat, Atiqullah Ahmadzai, Aleena Elsa George +3
Software vulnerabilities are a fundamental cause of cyber attacks. Effectively identifying these vulnerabilities is essential for robust cybersecurity, yet it remains a complex and…
SmartX Intelligent Sec: A Security Framework Based on Machine Learning and eBPF/XDP
Talaya Farasat, JongWon Kim, Joachim Posegga
Information and Communication Technologies (ICT) infrastructures are becoming increasingly complex day by day, facing numerous challenges to support the latest networking paradigms…
Advancing Network Security: A Comprehensive Testbed and Dataset for Machine Learning-Based Intrusion Detection
Talaya Farasat, JongWon Kim, Joachim Posegga
This paper introduces a Testbed designed for generating network traffic, leveraging the capabilities of containers, Kubernetes, and eBPF/XDP technologies. Our Testbed serves as an…
Machine Learning Techniques for Python Source Code Vulnerability Detection
Talaya Farasat, Joachim Posegga
Software vulnerabilities are a fundamental reason for the prevalence of cyber attacks and their identification is a crucial yet challenging problem in cyber security. In this paper…