IMPLEMENTASI INTRUSION DETECTION SYSTEM MENGGUNAKAN SNORT BERBASIS PARALLEL COMPUTING DENGAN METODE LOG DISTRIBUTION

GIMNASTIAR, AHMAD and Heryanto, Ahmad (2025) IMPLEMENTASI INTRUSION DETECTION SYSTEM MENGGUNAKAN SNORT BERBASIS PARALLEL COMPUTING DENGAN METODE LOG DISTRIBUTION. Undergraduate thesis, Sriwijaya University.

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Abstract

This research develops an Intrusion Detection System (IDS) based on Snort, optimized using parallel computing with the Message Passing Interface (MPI). The system is built with an architecture consisting of one master and two workers running Snort in parallel to detect ICMP traffic. Detection logs are collected through a shared folder and monitored by the master using a Python script, which also sends automatic email notifications when critical threats are detected. Testing was carried out in four scenarios: without a worker, with 1 worker, 2 workers, and 1 worker with configuration tuning. The results show significant improvements in CPU, memory, and energy efficiency. The 2-worker configuration delivered the best performance, while tuning on the 1-worker setup resulted in the lowest energy consumption. These findings demonstrate that the parallel computing approach can effectively improve IDS performance and is suitable for deployment in small to medium-scale networks.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Intrusion Detection System, Snort, MPI, Parallel Computing, ICMP.
Subjects:	T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T10.5 General works Information centers T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T10.7 Technical literature
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Ahmad Gimnastiar
Date Deposited:	17 Sep 2025 01:37
Last Modified:	17 Sep 2025 01:37
URI:	http://repository.unsri.ac.id/id/eprint/184058

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