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All Journal International Journal of Science Education and Cultural Studies Jurnal Komputer dan Elektro Sains
Luqman Hafiz
Department of Informatics Engineering, Institut Teknologi Budi Utomo, Jakarta, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Other

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Deep Learning in Wazuh Intrusion Detection System to Identify Advanced Persistent Threat (APT) Attacks Budi Wibowo; Aji Nurrohman; Luqman Hafiz
International Journal of Science Education and Cultural Studies Vol. 4 No. 1 (2025): IJSECS
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i1.311

Abstract

Advanced Persistent Threats (APTs) pose a significant challenge in modern cybersecurity by leveraging persistent and sophisticated methods to compromise organizations. These threats employ advanced techniques such as encrypted communication, polymorphic malware, and log tampering, to evade detection, exfiltrate sensitive data, and disrupt critical infrastructure. Such characteristics often render conventional security measures ineffective in mitigating or preventing such attacks. This study adopted an experimental approach to assess the application of Wazuh, an advanced open-source security platform, in countering APT attacks. By simulating attack scenarios and analyzing real-time logs from diverse sources, Wazuh demonstrated strong intrusion detection capabilities, identifying attack patterns such as brute force attempts and unauthorized directory access. The findings underscore Wazuh’s effectiveness in enhancing organizational resilience by enabling rapid detection and response to suspicious activities. This research highlights how integrated log analysis can address the stealthy nature of APTs. Future studies should explore the integration of machine learning with platforms like Wazuh to further enhance automated and predictive threat detection capabilities, thereby strengthening defenses against evolving strategies of APTs.
Risk Analysis of Bruteforce Attacks on Webserver with Telegram Notifications Budi Wibowo; Luqman Hafiz
Jurnal Komputer dan Elektro Sains Vol. 3 No. 1 (2025): komets
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/komets.v3i1.305

Abstract

In today's digital era, server security is a top priority for many organizations. Intrusion Detection Systems (IDS) such as Fail2ban, have proven effective in protecting servers from threats by monitoring logs and blocking suspicious IP addresses. This paper discusses the implementation of Fail2ban integrated with Telegram notifications, how it works, testing, and results showing improvements in detecting and responding to attacks. Server ssh brute force attacks pose considerable risks to web servers and have potentially severe consequences. Implementing strong preventive measures, continuous monitoring, and leveraging Telegram notifications for real-time alerts significantly improved the organization’s security posture. These combined efforts ensure robust and responsive detection of brute force attacks. Fail2ban was able to quickly discover the IP address from which the attacker performed the brute force attack and took preventive action by blocking the attacker's Ip for 3 failed login attempts within a specified time limit of 3600 s.
Co-Authors Aji Nurrohman Budi Wibowo