Unveiling Malware Secrets Through Cutting-Edge Analysis

Unveiling Malware Secrets Through Cutting-Edge Analysis

연구 분야: Safety

학회: 2024 Second International Conference on Inventive Computing and Informatics (ICICI)

Malware can covertly damage computers, steal data, and cause various other issues. It includes ransomware, worms, trojan horses, viruses, and botnets, each with different motives and impacts. Malware can compromise private data, slow down or crash systems, and even demand ransom. To combat these threats, advanced security tools that detect ransomware through network traffic monitoring and behavior analysis are essential. This study proposes a multi-layered approach for malware detection, including the use of robust antivirus programs, rigorous anti-malware scans, and regular software updates. Effective malware analysis involves static and dynamic analysis, malware segregation in controlled environments, and signature creation. By reverse engineering the malware code, network monitoring and memory activities, and generating comprehensive reports with indicators of compromise, a deeper understanding of malware behavior and mitigation strategies can be achieved. This research study aims to enhance malware detection and evaluation by using machine learning techniques. The objective of this research study is to develop reliable models for thorough examination and real-time malware detection, thereby promoting proactive cybersecurity measures.