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All Journal JISTECH: Journal of Information Science and Technology Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization INOVTEK Polbeng - Seri Informatika Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) TANJAK : Jurnal Pengabdian Kepada Masyarakat INOVTEK Polbeng - Seri Informatika
Ratnawati, Fajar
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Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media

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Journal : JOIV : International Journal on Informatics Visualization

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Optimizing Pigeon-Inspired Algorithm to Enhance Intrusion Detection System Performance Internet of Things Environments Ratnawati, Fajar; Siswanto, Apri; Jaroji, -; Effendy, Akmar; Tedyyana, Agus
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1724

Abstract

Intrusion Detection Systems (IDS) are crucial in maintaining network security and safeguarding sensitive information against external and internal threats. This study proposes a novel approach by utilizing a Pigeon-Inspired Algorithm optimized with the Hyperbolic Tangent Function (Tanh) function to enhance the performance of IDS in threat detection specifically tailored for Internet of Things (IoT) environments. We aim to create a more robust solution for optimizing intrusion detection systems by integrating the efficient and effective Tanh function into the Pigeon-Inspired Algorithm. The proposed method is evaluated on three widely-used datasets in the field of IDS: NSL-KDD, CICIDS2017, and CSE-CIC-IDS2018. Experimental results demonstrate that integrating the Tanh function into the Pigeon-Inspired Algorithm significantly improves the performance of the intrusion detection system. Our method achieves higher accuracy, True Positive Rate (TPR), and F1-score while reducing the False Positive Rate (FPR) compared to traditional Pigeon-Inspired Algorithms and several other optimization algorithms. The Pigeon-Inspired Algorithm optimized with the Tanh function offers an efficient and effective solution for enhancing intrusion detection system performance, specifically in Internet of Things environments. This method holds great potential for application in diverse network environments, bolstering information security and safeguarding systems from evolving cybersecurity threats. By extending the applicability and effectiveness of the Pigeon-Inspired Algorithm optimized with the Tanh function, researchers can contribute to developing more comprehensive and robust security solutions, addressing the ever-evolving landscape of IoT-based cybersecurity threats.
Co-Authors Afridon, M Agus Tedyyana, Agus Apri Siswanto Budhi Santoso Danuri Danuri, Danuri Depandi Enda Effendy, Akmar Elgamar Syam Fitri Fitri Jaroji Jaroji, Jaroji Jaroji, - Muhammad Asep Subandri Muhammad Fauzi Muhammad Luthfi Nazirah, Reza Suci Niky Hardinata Putra, Fajri Profesio Raff, Hafizah Wadji Subandri, M. Asep Supendi, Supendi Umila, Izatul Yumami, Eva