Network Traffic Analysis and Anomaly Detection
Table Of Contents
- 1.Introduction
- 1.1Importance of Network Traffic Analysis
- 1.2Objectives of the Project
- 2.Fundamentals of Network Traffic Analysis
- 2.1Packet Inspection and Deep Packet Inspection (DPI)
- 2.2Flow Analysis and Traffic Profiling
- 2.3Network Protocol Analysis and Signatures
- 3.Anomaly Detection Techniques
- 3.1Statistical Approaches to Anomaly Detection
- 3.2Machine Learning-Based Anomaly Detection
- 3.3Behavior-Based Anomaly Detection
- 4.Real-Time Monitoring and Alerting Systems
- 4.1Intrusion Detection and Prevention Systems (IDPS)
- 4.2Security Information and Event Management (SIEM)
- 4.3Network Forensics and Incident Response
- 5.Case Studies and Practical Applications
- 5.1Detection of DDoS Attacks and Botnet Activity
- 5.2Insider Threat Detection and User Behavior Analysis
- 5.3Zero-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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