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ITERATIVE LOG ANALYSIS TOOL FOR VISUAL REPRESENTATION IN DETECTING MALICIOUS ACTIVITIES
ITERATIVE LOG ANALYSIS TOOL FOR VISUAL REPRESENTATION IN DETECTING MALICIOUS ACTIVITIES
S.Saravana Kumar, Department of CSE (Cyber Security), Dr.Mahalihngam College of Engineering and Technology, Coimbatore, India
saravanacs84@gmail.com
P.Harishini, Department of CSE (Cyber Security), Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
harishiniraj2020@gmail.com
Sathya Shalini, Department of CSE (Cyber Security), Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
vijayakumart@drmcet.ac.in
Dr. P. Vivekanandan, Department of CSE (Cyber Security), Dr.Mahalingam College of Engineering and Technology, Coimbatore, India
Abstract
Log analysis is the process of converting raw or unstructured log files into structured data and making intelligent decisions on that structured data. In every field like software testing, the analysis of log files is designed to monitor and check application performance. Logs are unstructured text lines containing systematic information regarding application work and actions such as IP Address, date, time, viewed sites, potential domains, status code, components, levels, nodes, query information, loading-time, user-agent, and port-number. Logs include several types such as INFO, WARNING, FATAL, SEVERE, and ERROR. The Log Analyzer Tool is a Python-based application designed to analyze log files for suspicious activities including malware, unauthorized access, phishing attempts, file tampering, security breaches, and more. The tool works across macOS, Windows, and Linux, offering a user-friendly graphical interface for log file selection and scan initiation. This project represents an industry-level, production-grade solution that strengthens cybersecurity infrastructure, reduces manual monitoring efforts, improves incident response time, enhances system reliability, and protects sensitive digital assets.
Keywords System Monitoring, Log File Analytics, Performance Analysis, Security Event Detection, Visual Representation
