Magaia_2020_DP-IIoT-SC_IoTJ.pdf (946.42 kB)
Industrial Internet-of-Things security enhanced with deep learning approaches for smart cities
journal contribution
posted on 2023-06-10, 02:44 authored by Naercio Magaia, Ramon Fonseca, Khan Muhammad, Afonso H Fontes N Segundo, Aloísio Vieira Lira Neto, Victor Hugo C De AlbuquerqueThe significant evolution of the Internet of Things (IoT) enabled the development of numerous devices able to improve many aspects in various fields in the industry for smart cities where machines have replaced humans. With the reduction in manual work and the adoption of automation, cities are getting more efficient and smarter. However, this evolution also made data even more sensitive, especially in the industrial segment. The latter has caught the attention of many hackers targeting Industrial IoT (IIoT) devices or networks, hence the number of malicious software, i.e., malware, has increased as well. In this article, we present the IIoT concept and applications for smart cities, besides also presenting the security challenges faced by this emerging area. We survey currently available deep learning (DL) techniques for IIoT in smart cities, mainly deep reinforcement learning, recurrent neural networks, and convolutional neural networks, and highlight the advantages and disadvantages of security-related methods. We also present insights, open issues, and future trends applying DL techniques to enhance IIoT security.
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE Internet of Things JournalISSN
2327-4662Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Issue
8Volume
8Page range
6393-6405Department affiliated with
- Informatics Publications
Notes
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksFull text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2022-02-28First Open Access (FOA) Date
2022-02-28First Compliant Deposit (FCD) Date
2022-02-25Usage metrics
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