A Holistic Approach to DDoS Mitigation: Leveraging NS-3 Simulation and Traceback for Enhanced Network Resilience

In the early stages of network development the security measures included for instance traffic filtering and firewalls which did not protect networks against new and sophisticated threats such as DDoS. Due to breakage of the nine layers of the Internet, these defenses served no purpose when facing mass raids. This paper therefore presents an effective means of detecting, isolating and managing DDoS attacks within large network systems using NS-3 based simulations. Next we develop a realistic 100-node networks with DDoS condition and by analyzing the traffic patterns, we isolate the malicious nodes. Our method uses Probabilistic Packet Marking (PPM) for traceback and a technique of identifying and removing compromised nodes, which improves network reliability. That is evident by the outcomes as traffic analysing and traceback techniques available in this research minimize disruptions and enhance service reliability.

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Publication Details

Published
2025-02-28
DOI
https://doi.org/10.1109/ice63309.2025.10983918
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

A Holistic Approach to DDoS Mitigation: Leveraging NS-3 Simulation and Traceback for Enhanced Network Resilience

Abhishek Jain, Nikhil Kumar, Jeyadev Meka
Network Security and Intrusion Detection
article

A Holistic Approach to DDoS Mitigation: Leveraging NS-3 Simulation and Traceback for Enhanced Network Resilience

Abhishek Jain, Nikhil Kumar, Jeyadev Meka
article en

Abstract

In the early stages of network development the security measures included for instance traffic filtering and firewalls which did not protect networks against new and sophisticated threats such as DDoS. Due to breakage of the nine layers of the Internet, these defenses served no purpose when facing mass raids. This paper therefore presents an effective means of detecting, isolating and managing DDoS attacks within large network systems using NS-3 based simulations. Next we develop a realistic 100-node networks with DDoS condition and by analyzing the traffic patterns, we isolate the malicious nodes. Our method uses Probabilistic Packet Marking (PPM) for traceback and a technique of identifying and removing compromised nodes, which improves network reliability. That is evident by the outcomes as traffic analysing and traceback techniques available in this research minimize disruptions and enhance service reliability.

BML Munjal University (IN)
Climate action
Openalex Percentile: Top 91%
Network Security and Intrusion Detection
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