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Journal : Proceeding Applied Business and Engineering Conference

Intrusion Detection System (Ids) Menggunakan Raspberry Pi 4 dengan Snort Studi Kasus : Laboratorium Jaringan Komputer Politeknik Negeri Bengkalis wahyat, Wahyat; Ryci Rahmatil Fiska; Dedi Hermawan
ABEC Indonesia Vol. 11 (2023): 11th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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Abstract

Server security on a computer network is very important, maintaining computer network security in order to maintain information, data and maintain infrastructure so that it can work and function properly and provide access rights to registered users, this study aims to build an Intrusion Detection System (IDS) on networks and servers using Raspberry Pi 4 with SNORT which is useful for monitoring Server activities when an attempted attack occurs by sending notifications to BOT Telegram via the administrator's cellphone in realtime, this system is tested with three attack scenarios namely, PING Attack, Port Scanning, and DOS / DDoS Attack. From the results of testing attacks, Snort can detect and provide alerts that will be stored in the Snort Log and forwarded to the Telegram BOT notification in real time.   Keywords: Raspberry pi, Server, IDS, Snort, Bot Telegram
Machine Learning-Based Intrusion Detection System (IDS) for Classifying Types of Attacks on Computer Networks Fiska, Ryci Rahmatil; Wahyat, Wahyat; Hermawan, Dedi; Laurenz, Via; Fateha, Izatul
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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Abstract

Server security on a computer network is very important, maintaining the security of a computer network inorder to maintain information, data and maintain infrastructure so that it can work and function properly and provideaccess rights to registered users, this research, aims to build an IDS (Intrusion Detection System) on the network andServer using Raspberry Pi with SNORT which is useful for monitoring Server activity when an attempted attack occurs.With the increasing complexity of network attacks carried out by attackers, intelligent and adaptive approaches areneeded to detect and overcome these threats. Traditional methods such as rule-based or signatures are often not effectiveenough in the face of evolving attacks. The large amount of network traffic data makes it difficult to manually analyzeand detect attacks. Naive Bayes has a very important role in the classification and detection of network attacks, bothconsidered malicious and highly malicious, By using Naive Bayes, network security systems can become more proactiveand adaptive to attacks. This technology not only helps in detecting familiar attacks but also enables identification andresponse to new or unknown attack techniques. Through proper classification, the system can provide better protectionand reduce the impact of attacks.