Distributed Denial of Service (ddos) Attack Identification and Analysis Using Python for Tracefile Processing

Student: Ifeoluwapo Erioluwatosin Popoola (Project, 2025)
Department of Computer Engineering
Ekiti State University, Ado-Ekiti, Ekiti State

Abstract

Distributed Denial of Service (DDoS) attacks pose significant threats to network security by overwhelming a target system with malicious traffic, disrupting legitimate user access. This project focuses on the identification and analysis of DDoS attacks using Python-based tracefile processing techniques. A network simulation is conducted to generate normal and attack traffic, which is then logged into a tracefile. The collected data is analyze to identify traffic anomalies, packet loss, congestion patterns, and bandwidth utilization. Various performance metrics such as throughput, packet delivery ratio, and traffic distribution are examined to differentiate between legitimate and attack traffic. The findings from this study contribute to understanding DDoS attack characteristics and provide insights for enhancing network security through effective traffic analysis techniques.

Keywords
DDoS attack network security Python analysis tracefile processing traffic monitoring network congestion packet loss NS2
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