Semantic Scholar Open Access 2019 305 sitasi

Deep Learning Models for Cyber Security in IoT Networks

Monika Roopak G. Tian J. Chambers

Abstrak

In this paper we propose deep learning models for the cyber security in IoT (Internet of Things) networks. IoT network is as a promising technology which connects the living and non-living things around the world. The implementation of IoT is growing fast but the cyber security is still a loophole, so it is susceptible to many cyber-attack and for the success of any network it most important that the network is completely secure, otherwise people could be reluctant to use this technology. DDoS (Distributed Denial of Service) attack has affected many IoT networks in recent past that has resulted in huge losses. We have proposed deep learning models and evaluated those using latest CICIDS2017 datasets for DDoS attack detection which has provided highest accuracy as 97.16% also proposed models are compared with machine learning algorithms. This paper also identifies open research challenges for usage of deep learning algorithm for IoT cyber security.

Topik & Kata Kunci

Computer Science

Penulis (3)

Monika Roopak

G. Tian

J. Chambers

Format Sitasi

APA MLA BibTeX

Roopak, M., Tian, G., Chambers, J. (2019). Deep Learning Models for Cyber Security in IoT Networks. https://doi.org/10.1109/CCWC.2019.8666588

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Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 305×
Sumber Database: Semantic Scholar
DOI: 10.1109/CCWC.2019.8666588
Akses: Open Access ✓