Semantic Scholar Open Access 2016 474 sitasi

Threat analysis of IoT networks using artificial neural network intrusion detection system

Elike Hodo X. Bellekens Andrew W. Hamilton Pierre-Louis Dubouilh E. Iorkyase +2 lainnya

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Abstrak

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

Topik & Kata Kunci

Computer Science

Penulis (7)

Elike Hodo

X. Bellekens

Andrew W. Hamilton

Pierre-Louis Dubouilh

E. Iorkyase

C. Tachtatzis

Robert C. Atkinson

Format Sitasi

APA MLA BibTeX

Hodo, E., Bellekens, X., Hamilton, A.W., Dubouilh, P., Iorkyase, E., Tachtatzis, C. et al. (2016). Threat analysis of IoT networks using artificial neural network intrusion detection system. https://doi.org/10.1109/ISNCC.2016.7746067

Akses Cepat

Lihat di Sumber doi.org/10.1109/ISNCC.2016.7746067

Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Total Sitasi: 474×
Sumber Database: Semantic Scholar
DOI: 10.1109/ISNCC.2016.7746067
Akses: Open Access ✓