Cybersecurity incidents require swift and accurate forensic analysis, but traditional methods rely heavily on manual processes. These methods are often time-consuming, labor-intensive, and prone to human error, delaying effective incident response. DedsecAI leverages artificial intelligence to automate and enhance post-incident cybersecurity forensic analysis, ensuring faster, more accurate investigations.
- Demo Video: [Insert Video Link]
- Deployed Project: [Insert Deployment Link]
- Automated Breach Detection: AI-driven analysis to identify anomalies and unauthorized access.
- Timeline Reconstruction: Tracks events leading up to and following a breach for clear incident visualization.
- Attack Vector Identification: Determines the specific methods used by attackers.
- Impacted Systems Analysis: Identifies compromised assets and prioritizes response efforts.
- AI Algorithm Integration: Uses machine learning for faster and more accurate forensic analysis.
- Data Visualization: Provides easy-to-interpret visual reports of the investigation results.
- Predictive Analytics: Utilizes historical data to anticipate potential cybersecurity threats.
- Frontend: React, D3.js
- Backend: Flask
- Database: MongoDB, Pandas
- AI/ML: PyTorch
- Other Technologies: Natural Language Processing (NLP), Predictive Analytics, SIEM Tool Integration
DedsecAI enhances cybersecurity forensic analysis by automating data collection, breach detection, and impact assessment using AI. By leveraging advanced technologies, it reduces human error, accelerates investigations, and strengthens security responses. The integration of predictive analytics and real-time threat detection ensures proactive risk management, making it a vital tool for modern cybersecurity.