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Developed a log analysis system to detect security incidents, reconstruct attack timelines, and identify malicious activity using Linux and Windows logs, demonstrating blue-team threat detection and incident response skills.
An AI-powered security system designed to enhance threat detection and system protection using machine learning techniques. Developed as part of an academic minor project.
A Security Operations Center (SOC) Home Lab showcasing endpoint telemetry collection, detection engineering, threat hunting and incident investigation using ELK Stack, Sysmon and Winlogbeat.
SOC-style network monitoring platform built with Python, Flask, SQLite and Scapy for device discovery, trust management, security event logging and network security monitoring.
An advanced cybersecurity system designed to monitor network traffic and system logs in real time, detect potential threats, and provide actionable insights. The project combines machine learning–based anomaly detection with rule-based techniques to identify suspicious activities such as unauthorized access and network attacks.