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

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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

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Series Title

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Call Number

T1840582025

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 76 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

005.13

Content Type

Text

Media Type

-

Carrier Type

-

Edition

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Subject(s)

Sistem Pemograman
Prodi Sistem Komputer, Fakultas Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

NO

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