IT System Log Analyzer

Abstract The Log Analyzer was implemented using [insert your programming language, e. g. , Go/Python], and incorporates fundamental concepts such as regular expression-based parsing, keyword filtering, time-based segmentation, severity classification, and pattern detection. It possesses the ability to recognize common issues such as failed login attempts, service crashes, unauthorized access, and performance bottlenecks. Additional features include customizable rule sets, support for multiple log formats (e. g. , syslog, application logs), and output visualization options to enhance usability and interpretability. The tool was evaluated on actual log data to assess its effectiveness, scalability, and accuracy. The results indicated significant improvements in log analysis efficiency and anomaly detection when compared to manual techniques. The project ultimately contributes to the fields of system administration, cybersecurity, and IT operations by providing a practical solution for log management and threat monitoring Keywords: Log Analysis, Anomaly Detection, Real-Time Monitoring, Cybersecurity