Tags → #data analysis

VulSifter Enhances Vulnerability Detection in Code Commits

VulSifter is a large language model designed to improve the detection of software vulnerabilities by accurately identifying genuine vulnerability-fixing code changes and reducing false positives in reporting.
Study Examines Machine Learning for Malware Detection on Windows

Recent research highlights the importance of machine learning and feature engineering in improving malware detection, with techniques like XGBoost and support vector machines showing significant promise in predicting threats.
Automatic Framework for Protocol State Machine Inference

A recent tutorial has introduced a new Automatic Protocol State Machine Inference Framework aimed at enhancing the analysis of network traffic in mixed protocol environments.
Study Analyzes Machine Learning Models for Phishing Detection

Phishing remains a significant cybersecurity threat, with recent studies highlighting the effectiveness of machine learning models in detecting phishing URLs while also raising concerns about the generalizability of their features across different datasets.
New Threat Intelligence Platform Enhances Cybersecurity Measures

A new Threat Intelligence Platform (TIP) has been launched to enhance cybersecurity for organizations by integrating various data sources and employing advanced technologies to monitor and mitigate diverse threats.