İkili Gri Kurt Optimizasyonu (BGWO) ve Naive Bayes (NB) Kullanılarak Yeni Bir Hibrit IoT Tabanlı IDS

Yıl 2020, Ejosat Özel Sayı 2020 (ICCEES), 279 - 286, 05.10.2020

Ismail Mohamed Nur Erkan Ülker

https://doi.org/10.31590/ejosat.804113

Öz

Akıllı ortamların temel amaçlarından biri, verimlilik ve konfor açısından insan yaşam standardının kalitesini yükseltmektir. Nesnelerin İnterneti (IoT) modeli, akıllı ortamlar oluşturmak için yeni teknolojiye dönüşmüştür. IoT, diğer cihazlarla bilgi alışverişi yapabilen fiziksel eşyalar veya cihazları ifade etmektedir. Akıllı ev, akıllı şehir, endüstriyel kontrolu, otomobil endüstrisi, tarım, akıllı ulaşım, ev otomasyonu ve aletleri, sağlık gibi çeşitli alanlarda ve daha birçok alanda kullanılmaktadır. Dahası, yenilikçi iş paradigmalarını ve gelişmiş kullanıcı deneyimini garanti etmektedir. Gizlilik ve güvenlik, IoT paradigmasına dayalı herhangi bir gerçek dünya akıllı ortamında temel sorunlar olarak kabul edilmektedir. Bu nedenle, IoT sistemlerinin güvenliğini uygulamak, IoT ağlarının başarılı dağıtımında birinci öncelik ve büyük ilgi alanı haline gelmektedir. IoT ile ilgili sistemlerdeki açık güvenlik delikleri, akıllı uygulamaları etkileyen güvenlik riskleri oluşturur. Mirai botnet son zamanlarda başlatılan yeni saldırılardan bir örnektir. IoT ağı, kimlik doğrulama ve şifreleme ile korunmaktadır. ancak kötü niyetli ve zararlı saldırılara karşı hafifletemez. Bu nedenle saldırıları tespit etmek için IoT tabanlı Saldırı Tespit Sistemi (IDS) gerekmektedir. Bu makalede, IoT ağındaki saldırıları savunmak ve güvenlemek için ikili Gri Kurt Optimizasyonu (BGWO) ve Naive Bayes (NB) kullanılarak yeni bir hibrit IoT tabanlı IDS sunulmuştur. BGWO, özellik seçimi olarak ve NB de sınıflandırma yöntemi olarak kullanılmıştır. Sonuçlar diğer optimizasyon algoritmalarıyla karşılaştırılmıştır. IoT-botnet veri kümesi, deneysel bir veri kümesi olarak kullanılmıştır.

Anahtar Kelimeler

Nesnelerin İnterneti (IoT), Akıllı Ortamlar, Saldırı Tespit Sistemi, Mirai Botnet, Güvenlik

A Novel Hybrid IoT Based IDS Using Binary Grey Wolf Optimizer (BGWO) and Naive Bayes (NB)

Öz

One of the main objectives of intelligent environments is to enhance the quality of human life standard in terms of efficiency and comfort. The Internet of Things (IoT) model has newly evolved into the technology for establishing smart environments. IoT refers to physical things or devices which are able to exchange information with other devices. It is used in various fields such as smart home, smart city, industrial control, automobile industry, agriculture, intelligent transportation, home automation and appliances, healthcare, and many other fields. Moreover, it assures innovative business paradigms and advanced user experience. Privacy and security are counted as the key problems in any real-world intelligent environment for the IoT paradigm. Therefore, to implement the security of the IoT systems is becoming the first priority and big area of interest in the successful distribution of IoT networks. The open holes of security in IoT related systems create security risks that impact the smart applications. Mirai botnet is an example of one of the novel attacks that launched recently. The network of IoT is protected with authentication and encryption, but it can’t be mitigated against malicious and harmful attacks. Thus, IoT based Intrusion Detection System (IDS) is required to detect the attacks. In this paper, a novel hybrid IoT based IDS using Binary Grey wolf optimizer (BGWO) and Naive Bayes (NB) is presented to defend and secure intrusions on the IoT network. BGWO is used as feature selection and NB as a classification method. The results are compared with other optimization algorithms. The BoT-IoT data set is used as an experimental data set.

Anahtar Kelimeler

Internet of Things(IoT), Intelligent Environments, Intrusion Detection System, Mirai botnet, Security

Kaynakça

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