@inproceedings{ed4e25936a0b414fa446f3331ae7b614,
title = "A heuristic intrusion detection system for Internet-of-Things (IoT)",
abstract = "Today, digitally connected devices are involved in every aspect of life due to the advancements in Internet-of-Things (IoT) paradigm. Recently, it has been a driving force for a major technological revolution towards the development of advanced modern computer networks connecting physical objects around us. The emergence of IPv6 and installation of open access public networks is attracting cyber-criminals to compromise the user specific security information. This is why the security breaches in IoT devices are dominating the headlines lately. In this research we have developed a random neural network based heuristic intrusion detection system (RNN-IDS) for IoTs. Upon feature selection, the neurons are trained and further tested at different learning rates with NSL-KDD dataset. Two methods are adopted to analyse the proposed scheme where the accuracy of RNN-IDS increased from 85.5% to 95.25%. Results also suggest that upon comparison with other machine learning algorithms, the proposed intelligent intrusion detection has higher accuracy in recognition of anomalous traffic from normal patterns.",
keywords = "cyber-Security, intrusion detection systems, IoT security, machine learning, NSL-KDD, random neural networks",
author = "Ayyaz-Ul-Haq Qureshi and Hadi Larijani and Jawad Ahmad and Nhamoinesu Mtetwa",
note = "AAM and acceptance email req'd x 2 (17/04/19 DC, 11/6/19 ET) Not possible to validate until 1 of these sources. ^Now published, part of book series. ",
year = "2019",
month = jun,
day = "23",
doi = "10.1007/978-3-030-22871-2_7",
language = "English",
isbn = "9783030228705",
series = "Advances in Intelligent Systems and Computing book series",
publisher = "Springer",
pages = "86--98",
booktitle = "Intelligent Computing - Proceedings of the Computing Conference CompCom 2019: Intelligent Computing",
}