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All Journal Journal Research of Social Science, Economics, and Management Blockchain Frontier Technology (BFRONT)
Fikri, Muhamad Al
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Computer Science & IT Control & Systems Engineering Education Environmental Science Library & Information Science

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Learning Cyber ​​Security and Machine Engineering at the University Karuniawan, Rickho Rizky; Santoso, Sugeng; Fikri, Muhamad Al; Argadilah, M.; Pamungkas, Wisnu Ardi
Blockchain Frontier Technology Vol. 3 No. 1 (2023): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v3i1.242

Abstract

In this review, key literature reviews on network analysis and intrusion detection using machine learning (ML) and deep learning (DL) approaches are explained. It also provides a brief lesson description for each ML/DL procedure. This paper covers the datasets used in machine learning techniques, which are the main instruments for evaluating network traffic and detecting irregularities. Data holds a key role in ML/DL approaches. We also go into further detail about the problems with using ML/DL to cybersecurity and make suggestions for future research.
The Role of National Computer Security Incident Response Team (Nat-CSIRT) in Threat Intelligence Sharing Through National Cyber Threat Intelligence System and Cyber Incident Database Center Yusuf, Andi; Setiyadi, Basuki Erwin; Amanda, Claudia Dwi; Fikri, Muhamad Al
Journal Research of Social Science, Economics, and Management Vol. 4 No. 10 (2025): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v4i10.843

Abstract

In 2021 and 2022, the stakeholder response rate to notifications sent by BSSN was only 9% of the total notifications delivered. In establishing the Nat-CSIRT, BSSN needs to implement breakthroughs to increase the number of responses and follow-ups to these notifications, thereby enhancing situational awareness and strengthening the national cybersecurity posture. Therefore, the role of Nat-CSIRT is crucial in optimizing threat intelligence sharing at the national level. The implementation of threat intelligence sharing has been mandated by various national and organizational policies, which underscores the urgency of executing the established policy directions. This paper focuses on strategies for the role of Nat-CSIRT in the implementation of national-level threat intelligence sharing by delving into the root causes of the suboptimal sharing using a problem tree analysis. Furthermore, the paper determines the strategic optimization of Nat-CSIRT’s role through a SWOT analysis, resulting in a strategy that leverages strengths to seize opportunities (S-O Strategy). This strategy is carried out through a three-phase action plan—short-term, medium-term, and long-term—targeting the development of human resources, governance, and technology. In addition, the paper presents a model for a national-level threat intelligence sharing scheme for the National Cyber Threat Intelligence System and National Cyber Incident Database Center, enabling stakeholders to automatically implement standardized information exchange in a secure, swift, and accurate manner, while applying the Traffic Light Protocol. This approach is expected to lead to more effective cyber threat response and mitigation.
Co-Authors Amanda, Claudia Dwi Argadilah, M. Karuniawan, Rickho Rizky Pamungkas, Wisnu Ardi Setiyadi, Basuki Erwin Sugeng Santoso Yusuf, Andi