Network Traffic Analysis and Anomaly Detection
Table Of Contents
1. Introduction
1.1 Importance of Network Traffic Analysis
1.2 Objectives of the Project
2. Fundamentals of Network Traffic Analysis
2.1 Packet Inspection and Deep Packet Inspection (DPI)
2.2 Flow Analysis and Traffic Profiling
2.3 Network Protocol Analysis and Signatures
3. Anomaly Detection Techniques
3.1 Statistical Approaches to Anomaly Detection
3.2 Machine Learning-Based Anomaly Detection
3.3 Behavior-Based Anomaly Detection
4. Real-Time Monitoring and Alerting Systems
4.1 Intrusion Detection and Prevention Systems (IDPS)
4.2 Security Information and Event Management (SIEM)
4.3 Network Forensics and Incident Response
5. Case Studies and Practical Applications
5.1 Detection of DDoS Attacks and Botnet Activity
5.2 Insider Threat Detection and User Behavior Analysis
5.3 Zero-Day Exploit Detection and Response
Thesis Abstract
This project aims to explore network traffic analysis techniques and anomaly detection methods for identifying malicious activities and security threats in computer networks. The project will involve studying packet inspection, flow analysis, and machine learning-based anomaly detection algorithms to develop a comprehensive network security monitoring system.
Thesis Overview
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