Abstract: The primary intention of this research is to design and implement a real-time malware detection tool that utilizes YARA rules for effective identification and prevention of malicious activities within network traffic. The rise in sophisticated malware threats has highlighted the importance of effective detection mechanisms in cybersecurity. This project, titled "Malware Scanner Using YARA", aims to develop a robust tool for identifying malicious entities within real-time network traffic. YARA (Yet Another Recursive Acronym), a powerful tool for classifying and identifying malware using pattern-matching rules, forms the backbone of this solution.
The proposed scanner leverages YARA rules to analyze network packets for potential malicious payloads, offering a proactive approach to threat detection. By focusing on network traffic analysis, the system bypasses the limitations of static malware scanning, enabling real-time interception of threats before they infiltrate critical systems.
Key features include the integration of YARA’s rule-matching capabilities with Python for automated traffic analysis, seamless processing of packet data, and precise reporting mechanisms. The project also emphasizes user-defined YARA rules, providing flexibility in addressing emerging malware signatures.
Keywords: Malware Detection, YARA Rules, Network Traffic Analysis, Real-Time Detection, Cybersecurity, Pattern Matching, Malware Analysis, Threat Identification
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DOI:
10.17148/IJARCCE.2024.131222
