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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Ahmed, Salman
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Electrical & Electronics Engineering

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Enhancing SDN security using ensemble-based machine learning approach for DDoS attack detection Hirsi, Abdinasir; Audah, Lukman; Salh, Adeb; Alhartomi, Mohammed A.; Ahmed, Salman
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1073-1085

Abstract

Software-defined networking (SDN) is a groundbreaking technology that transforms traditional network frameworks by separating the control plane from the data plane, thereby enabling flexible and efficient network management. Despite its advantages, SDN introduces vulnerabilities, particularly distributed denial of service (DDoS) attacks. Existing studies have used single, hybrid, and ensemble machine learning (ML) techniques to address attacks, often relying on generated datasets that cannot be tested because of accessibility issues. A major contribution of this study is the creation of a novel, publicly accessible dataset, and benchmarking the proposed approach against existing public datasets to demonstrate its effectiveness. This paper proposes a novel approach that combines ensemble learning models with principal component analysis (PCA) for feature selection. The integration of ensemble learning models enhances predictive performance by leveraging multiple algorithms to improve accuracy and robustness. The results showed that the ensemble of random forests (ENRF) model achieved the highest performance across all metrics with 100% accuracy, precision, recall, and F1-score. This study provides a comprehensive solution to the limitations of existing models by offering superior performance, as evidenced by the comparative analysis, establishing this approach as the best among the evaluated models.
A review of the hardware implementation of CRYSTALS-Kyber post-quantum cryptography algorithm Wijayanto, Ardhi; Ahmad, Nabihah; Ahmed, Salman
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10477

Abstract

The development of quantum computing is escalating the vulnerability of conventional cryptography algorithms. To answer this challenge, researchers develop the post-quantum cryptography (PQC) algorithms. The PQC algorithms are immune from attacks deployed by quantum computers. CRYSTALS-Kyber (abbreviated as Kyber) is a PQC algorithm, originally constructed as public key encryption (PKE), then extended as the key encapsulation mechanism (KEM) algorithm to securely transfer a shared key to other parties over unsecured communication channels. The implementation of Kyber algorithm in hardware ensures a better security standard for securing systems that prioritize performance. This study provides a literature review of the Kyber hardware implementations. The review is delivered by a systematic literature review method to discuss resource and performance optimization, key design constraints, performance trade-offs, and future research directions in hardware implementation of Kyber based on existing studies. Area utilization and energy efficiency are achieved through the optimization of memory and architecture. The trade-off between performance, flexibility, and utilization remains relevant in the deployment context. Future work should accommodate holistic solutions, security, and performance enhancements as well as fabrication for real-world solutions.
Co-Authors Ahmad, Nabihah Alhartomi, Mohammed A. Audah, Lukman Hirsi, Abdinasir Salh, Adeb Wijayanto, Ardhi