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All Journal bit-Tech Cyber Security and Network Management
Fandan Dwi Nugroho Wicaksono
Perbanas Institute
Computer Science & IT

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IoT Security Attacks on the Public Sector: Systematic Literature Review Fandan Dwi Nugroho Wicaksono; Winny Purbaratri; Moch Fajar Purnomo Alam; Agnes Novita Ida Safitri
bit-Tech Vol. 7 No. 1 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i1.1627

Abstract

The primary objective of this study is to examine security threats that specifically target the Internet of Things (IoT) used in the Public Sector. This sector is widely acknowledged as a crucial element of the fourth industrial revolution. The high volume of intelligent devices employed in the public sector, which are linked in the Internet of Things (IoT), and each of them transmits sensitive data in numerous instances, makes security of utmost importance. The objective of this study is to categorize various forms of security attacks and propose strategies to mitigate security breaches through many approaches. This study employed a systematic review, which is a methodical examination of current literature. The data synthesis methodology in this study consisted of comparing 15 literature sources that had been evaluated for quality and satisfied the specified criteria for inclusion and exclusion. The utilized database sources include renowned platforms such as Scopus, ACM, and IEEE. The present study employs a qualitative methodology, specifically utilizing the perspectives of two information security specialists to examine the existing literature. The findings of this study have made a meaningful contribution to the field of public sector. This study categorizes four types of assaults against Public Sector IoT: 37% Denial-of-Service (DoS) attacks, 31% Malware attacks, and 19% Phishing attacks. System attacks account for 13% of all system attacks. By contrast, 50% of the security attack mitigation strategies rely on authentication, 36% on Secure Communication, and 14% on Application Security.
Penentuan Metode Optimalisasi Pemakaian Bandwith Menggunakan Analytical Hierarchy Process (AHP) Gregorius Armando Malvin; Mardiana Purwaningsih; Fandan Dwi Nugroho Wicaksono
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1811

Abstract

Kecepatan internet yang stabil dan konstan merupakan sebuah kebutuhan yang sangat penting dalam sebuah perusahaan. Kecepatan ini sangat berpengaruh dalam proses upload (besaran data yang keluar) maupun proses download (besaran data yang masuk) oleh sebuah peralatan dalam suatu jaringan. Saat ini perusahaan belum menerapkan metode optimalisasi bandwith. Dengan jumlah pengguna sebesar 123 user pada jaringan lokal, maka ada saat-saat tertentu di mana pembagian bandwith ini menjadi masalah, ketika diakses secara bersamaan. Apalagi ada beberapa pengguna yang membutuhkan bandwith lebih besar berkenaan dengan pekerjaannya. Optimalisasi penggunaan bandwith ini dapat dibantu oleh beberapa metode, akan tetapi perusahaan pun menemui kesulitan dalam memilihnya. Metode optimalisasi bandwidth merupakan sebuah kegiatan yang dapat membantu mengatur bandwidth baik yang akan keluar maupun masuk. Tujuan optimalisasi ini agar lalu lintas dalam sebuah jaringan tidak berlebihan dan sesuai dengan yang sebenarnya, serta tidak terjadi tumpang tindih. Ada beberapa metode yang dapat membantu bandwidth bekerja secara optimal antara lain Simple Queue, Queue Tree, PCQ, dan HTB. Di mana masing-masing metode tersebut memiliki karateristik berbeda-beda, serta kelebihan dan kekurangannya. Akan tetapi seringkali perusahaan tidak memiliki pengetahuan yang cukup dalam memilih metode yang sesuai dengan kebutuhannya. Sistem pendukung keputusan dibentuk dan dibangun untuk membantu perusahaan menentukan metode optimalisasi bandwith yang sesuai. Metode Analytical Hierarchy Process (AHP) merupakan salah satu metode dalam sistem pendukung keputusan untuk membantu perusahaan memilih metode optimalisasi bandwith. Dari hasil perhitungan dengan AHP maka metode yang mendapat peringkat tertinggi adalah Simple Queue dengan nilat total 0.367. Dengan penggunaan metode optimalisasi bandwith ini maka ke depannya perusahaan dapat memilih metode yang paling sesuai dengan kebutuhan, sehingga pembagian bandwith akan sesuai juga dengan kapasitas pekerjaan masing-masing pengguna.
Risk Aware Cybersecurity Governance Model with Real Time Threat Intelligence Integration and Predictive Anomaly Detection for Enterprise Network Infrastructures Firman Pratama; Fandan Dwi Nugroho Wicaksono
Cyber Security and Network Management Vol. 1 No. 1 (2026): February: Cyber Security and Network Management
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/cybernet.v1i1.10

Abstract

The increasing sophistication of cyber threats has rendered traditional cybersecurity models insufficient in safeguarding enterprise networks. This study introduces a risk aware cybersecurity governance model that integrates real time threat intelligence with predictive anomaly detection to proactively mitigate potential threats. By leveraging advanced machine learning and AI techniques, the model enhances the ability to identify and address cyber threats before they can escalate into significant incidents. The model’s ability to predict anomalies, analyze real time threat intelligence feeds, and provide early warnings allows for faster response times and reduced risk exposure compared to traditional reactive models. Through simulations and real-world use cases, the proposed model demonstrated a 30% reduction in response time and a 25% decrease in overall risk exposure, showing its potential to improve security decision-making and resilience in dynamic threat environments. Unlike traditional models that rely on static rules and periodic policies, the proposed model uses predictive analytics to stay ahead of evolving threats, ensuring continuous monitoring and rapid adaptation. This proactive approach enhances organizational resilience, particularly in handling sophisticated cyber threats such as ransomware, malware, and phishing attacks. Despite its effectiveness, challenges such as data overload, scalability, and the need for interpretability in AI models remain. Future research will focus on refining predictive models, improving scalability for larger networks, and enhancing the explainability of machine learning models to foster greater trust in automated cybersecurity systems. This study contributes to the ongoing evolution of cybersecurity governance by demonstrating the value of integrating predictive and real time monitoring technologies for enhanced threat detection and mitigation.
Co-Authors Agnes Novita Ida Safitri Firman Pratama Gregorius Armando Malvin Mardiana Purwaningsih Moch Fajar Purnomo Alam Purbaratri, Winny