Show simple item record

AuthorAli, Yasir
AuthorKhan, Habib Ullah
AuthorKhalid, Muhammad
Available date2024-05-12T07:08:48Z
Publication Date2023
Publication NameJournal of Big Data
ResourceScopus
Identifierhttp://dx.doi.org/10.1186/s40537-023-00805-5
ISSN21961115
URIhttp://hdl.handle.net/10576/54809
AbstractInternet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of service (DDoS) attacks, intrusions, malwares, authentication problems or other fatal attacks. The impacts of these security threats can be diminished by providing protection towards the different IoT security features. Different technological solutions have been presented to cope with the vulnerabilities and providing overall security towards IoT systems operating in numerous environments. In order to attain the full-pledged security of any IoT-driven system the significant contribution presented by artificial neural networks (ANNs) is worthy to be highlighted. Therefore, a systematic approach is presented to unfold the efforts and approaches of ANNs towards the security challenges of IoT. This systematic literature review (SLR) is composed of three (3) research questions (RQs) such that in RQ1, the major focus is to identify security requirements or criteria that defines a full-pledge IoT system. This question also focusses on pinpointing the different types of ANNs approaches that are contributing towards IoT security. In RQ2, we highlighted and discussed the contributions of ANNs approaches for individual security requirement/feature in comprehensive and detailed fashion. In this question, we also determined the various models, frameworks, techniques and algorithms suggested by ANNs for the security advancements of IoT. In RQ3, different security mechanisms presented by ANNs especially towards intrusion detection system (IDS) in IoT along with their performances are comparatively discussed. In this research, 143 research papers have been used for analysis which are providing security solutions towards IoT security issues. A comprehensive and in-depth analysis of selected studies have been made to understand the current research gaps and future research works in this domain.
SponsorQatar National Library, QNL: IR CC 2021-001
Languageen
PublisherSpringer Science and Business Media Deutschland GmbH
SubjectArtificial neural network
Internet of Things
Internet security
Network
Security requirements
TitleEngineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review
TypeArticle Review
Issue Number1
Volume Number10
dc.accessType Open Access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record