Deakin University
Browse

Averaged dependence estimators for DoS attack detection in IoT networks

Version 2 2024-06-05, 11:51
Version 1 2019-08-13, 23:09
journal contribution
posted on 2024-06-05, 11:51 authored by Zubair BaigZubair Baig, S Sanguanpong, SN Firdous, VN Vo, TG Nguyen, C So-In
Wireless sensor networks (WSNs) have evolved to become an integral part of the contemporary Internet of Things (IoT) paradigm. The sensor node activities of both sensing phenomena in their immediate environments and reporting their findings to a centralized base station (BS) have remained a core platform to sustain heterogeneous service-centric applications. However, the adversarial threat to the sensors of the IoT paradigm remains significant. Denial of service (DoS) attacks, comprising a large volume of network packets, targeting a given sensor node(s) of the network, may cripple routine operations and cause catastrophic losses to emergency services. This paper presents an intelligent DoS detection framework comprising modules for data generation, feature ranking and generation, and training and testing. The proposed framework is experimentally tested under actual IoT attack scenarios, and the accuracy of the results is greater than that of traditional classification techniques.

History

Journal

Future Generation Computer Systems

Volume

102

Pagination

198-209

Location

Amsterdam, The Netherlands

ISSN

0167-739X

eISSN

1872-7115

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2019, Elsevier B.V.

Publisher

ELSEVIER