Zorlu Ortamlarda RPL Saldırılarının Etkisinin Değerlendirilmesi: Evrim Destekli Bir Çalışma

Year 2024, EARLY VIEW, 1 - 1

Özlem Ceviz , Selim Yilmaz

Abstract

IoT destekli akıllı teknolojilerin günlük yaşamımıza entegrasyonu birçok açıdan sayısız fayda sağlasa da bu teknolojiyi mümkün kılan IoT ağları için tasarlanan protokollerin günümüzde çok sayıda güvenlik açığı sergilemesi, beraberinde güvenlik endişelerini de getirmiştir. Bu protokollerden biri, heterojen cihazlar arasında yönlendirmeyi sağlamak için IoT ağlarda sıklıkla kullanılan RPL (IPv6 Routing Protocol for Low Power Lossy Networks) protokolüdür. RPL bugüne kadar önemli eksiklikler sergilemiş ve çeşitli saldırıların hedefi haline gelmiştir. RPL saldırılarının performansını değerlendirmek, IoT ağının etkili bir şekilde güvenliğini sağlamak önemli bir görevdir. Performans analizi literatürde çok sayıda çalışılmasına rağmen tamamı 'insan yapımı' saldırı ortamlarına dayanmaktadır. Buna karşılık, bu çalışma performans değerlendirmesi için ulaşılabilecek en güçlü saldırı ortamlarını dikkate almaktadır. Bu tür ortamları elde etmek için genetik algoritmanın kullanımı bu çalışmada araştırılmıştır. Bulgular, saldırının etkisinin, saldırganların ağdaki konumundan ve yoğunluğundan büyük ölçüde etkilendiğini ortaya koymaktadır.

Keywords

IoT, RPL saldırıları, genetik algoritma, performans değerlendirme

Ethical Statement

Bu makalenin yazarları çalışmalarında kullandıkları materyal ve yöntemlerin etik kurul izni ve/veya yasal-özel bir izin gerektirmediğini beyan ederler.

Supporting Institution

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

Project Number

122E331

Thanks

Bu çalışma Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK-122E331) tarafından finanse edilmektedir. Desteğinden dolayı TÜBİTAK'a teşekkür ederiz.

Assessing the Impact of RPL Attacks in Challenging Environments: An Evolution-assisted Study

Abstract

The integration of IoT-enabled smart technologies into our daily lives offers numerous benefits in many ways; however, it has also given rise well-founded security concerns since the protocols designed for IoT networks, enabling this technology, exhibit numerous vulnerabilities today. One such protocol is the IPv6 Routing Protocol for Low Power Lossy Networks (RPL) which is frequently used in IoT networks to enable routing between the heterogeneous devices. RPL has exhibited significant shortcomings and has become a target for various attacks up to now. Evaluating the performance of RPL attacks is a non-trivial task for securing IoT network effectively. Although performance analysis studies are numerous in literature, all of them rely on ‘human-crafted’ attack environments. In contrast, this study considers the most challenging malicious environments achievable for performance evaluation. To achieve such environments, the use of genetic algorithm is explored in this study. The findings reveal that the impact of the attack is greatly influenced by the position as well as the density of the attackers in the network.

Keywords

IoT, RPL attacks, genetic algorithm, performance assessment

Ethical Statement

The authors of this article declare that the materials and methods used in this study do not require ethical committee permission and/or legal-special permission

Supporting Institution

Scientific and Technological Research Council of Turkey (TUBITAK)

Project Number

122E331

Thanks

This study is funded by the Scientific and Technological Research Council of Turkey (TUBITAK-122E331). We would like to thank TUBITAK for its support.

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