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Journals / Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering / 2026 / Volume: 68 Issue: 1

Enhancing IDS Through Multi-Objective Optimization: A Focus on Attack Graph under Worst-Parent Attack

Ali Deveci(HACETTEPE ÜNİVERSİTESİ)0000-0002-4990-0785
Mehmet Ali Erkan(ORTA DOĞU TEKNİK ÜNİVERSİTESİ)0009-0007-5760-1914
İhsan Tolga Medeni(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ)0000-0002-0642-7908
Tunç Durmuş Medeni(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ)0000-0002-2964-3320
Ali Uzkafali(Uzkafalı Hukuk Bürosu)0009-0005-0940-5885
Ahmet Özkan(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ)0009-0008-9338-757X
Pages
—
Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This improvement signifies the effectiveness of integrating additional metrics in enhancing predictive accuracy and understanding network structure and resilience.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study focuses on the evolution of network security models for RPL based LLNs under worst-parent attack.
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Key Findings & Data:The multi-objective optimization approach integrates additional metrics: i) The amount of change in the maximum path length within the graph (∆L) and ii) the amount of change in the number of nodes connected to the attacker node(∆W) alongside the conventional accuracy criterion.
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Conclusion & Impact:This improvement signifies the effectiveness of integrating additional metrics in enhancing predictive accuracy and understanding network structure and resilience.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Attack graphs · eccentricity · multi-objective optimization

Abstract

This study focuses on the evolution of network security models for RPL based LLNs under worst-parent attack. The multi-objective optimization approach integrates additional metrics: i) The amount of change in the maximum path length within the graph (∆L) and ii) the amount of change in the number of nodes connected to the attacker node(∆W) alongside the conventional accuracy criterion. The analysis of these metrics plays a crucial role in the development of Intrusion Detection Systems (IDS), particularly through the examination of attack graphs. Attack graphs are small, distinct network substructures used to model potential attacks on the network. Analyzing these graphs is considered essential for identifying security vulnerabilities in the network and determining the spread and impact of attacks. The findings of the study demonstrate a progressive improvement in model performance across tasks, starting from a single-objective task and advancing towards multi-objective tasks. This improvement signifies the effectiveness of integrating additional metrics in enhancing predictive accuracy and understanding network structure and resilience.

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Cite This Article

Deveci, A., Erkan, M. A., Medeni, İ. T., Medeni, T. D., Uzkafali, A., Özkan, A. (2026). Enhancing IDS Through Multi-Objective Optimization: A Focus on Attack Graph under Worst-Parent Attack. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Volume: 68 Issue: 1. https://doi.org/10.33769/aupse.1907258

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