1408 - IT System log analyzer

Ministry of Home Affairs

Software

Blockchain & Cybersecurity

This website aims to address the need for a centralized system to analyze IT system logs across different locations of the Central Reserve Police Force (CRPF). Currently, there is no central platform for experts to assess threats and security breaches systematically. The proposed solution is to develop a centralized system for analyzing the IT systems deployed at various CRPF locations across the country.

• Meghna Malasi - 2022UCS1611
• Krish Gupta - 2022UIC3507
• Tanish Saxena - 2022UIC3511
• Manas Madan - 2022UIC3533
• Ayush Arora - 2022UIC3538
• Devansh Behl - 2022UIC3582

• Next JS
• Tailwind CSS
• NextUI
• Recharts
• Truffle
• Solidity and Blockchain
• Ganache
• Node JS
• Express JS
• Moralis IPFS
• Luxon
• Python

• Real-time Analysis: The system provides real-time log analysis capabilities, allowing experts to monitor IT system activities as they happen.

• Threat Detection: Advanced algorithms and machine learning techniques are employed to detect potential threats, anomalies, and security breaches within the IT systems.

• Customizable Alerts: Experts can configure customizable alerts and notifications based on specific log patterns or security events, ensuring prompt response to potential issues.

• Data Visualization: The system offers interactive data visualization tools, including graphs and charts, to help experts gain insights from log data more effectively.

• Detailed Reports: Comprehensive reports are generated, summarizing log analysis findings, security incidents.

• Role-based Access: User roles and permissions are defined to ensure that only authorized personnel can access and modify log data and analysis settings.

• Log Data Storage: Log data from various CRPF units and offices is collected, securely stored, and organized in a structured database for efficient retrieval.

• Data Ingestion: The backend provides mechanisms for ingesting log data from diverse sources, ensuring compatibility and data integrity.

• Data Retention: Define data retention policies to manage the storage of log data, ensuring compliance with data protection regulations.

• Threat Detection Engine: Implement advanced algorithms and machine learning models to detect security threats, anomalies, and breaches in real-time.

• Alerting System: Create an alerting system that triggers notifications and alerts when potential security incidents are detected.

• RESTful APIs: Provide RESTful APIs for the frontend to access log data, analysis results, and configuration settings securely.

• User Authentication: Implement secure user authentication and authorization mechanisms for API access.

• Data Visualization: Offer APIs for data visualization tools to fetch real-time insights and generate reports.

• Blocks IP Address: Based on the ML Model predictions the system blocks suspicious IP address
• Block Actions: Based on the ML Model predictions the system restricts certain actions like downloading Malware, chaging Firewall rules etc.

• Machine Learning to Predict Threat Level of a log