The DOI matches its Crossref record; 187 of the 187 references it cites were found in a registry or an index.
Machine learning based solutions for security of Internet of Things (IoT): A survey
Open accessAbstract
Abstract Over the last decade, IoT platforms have been developed into a global giant that grabs every aspect of our daily lives by advancing human life with its unaccountable smart services. Because of easy accessibility and fast-growing demand for smart devices and network, IoT is now facing more security challenges than ever before. There are existing security measures that can be applied to protect IoT. However, traditional techniques are not as efficient with the advancement booms as well as different attack types and their severeness. Thus, a strong-dynamically enhanced and up to date security system is required for next-generation IoT system. A huge technological advancement has been noticed in Machine Learning (ML) which has opened many possible research windows to address ongoing and future challenges in IoT. In order to detect attacks and identify abnormal behaviors of smart devices and networks, ML is being utilized as a powerful technology to fulfill this purpose. In this survey paper, the architecture of IoT is discussed, following a comprehensive literature review on ML approaches the importance of security of IoT in terms of different types of possible attacks. Moreover, ML-based potential solutions for IoT security has been presented and future challenges are discussed.
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Cites
1 retracted
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Cited by
Abdullahi, M., Baashar, Y., Alhussian, H., Alwadain, A., Aziz, N., Capretz, L. F., & Abdulkadir, S. J. (2022) · Electronics · doi:10.3390/electronics11020198 · Cited by 361
Using the internet of things in smart energy systems and networks
Ahmad, T., & Zhang, D. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.102783 · Cited by 332
An efficient lightweight cryptographic algorithm for IoT security
Abdulraheem, M., Awotunde, J. B., Jimoh, R. G., & Oladipo, I. D. (2021) · Communications in Computer and Information Science · doi:10.1007/978-3-030-69143-1_34 · Cited by 32
A Comprehensive Survey on Generative AI Solutions in IoT Security
López Delgado, J. L., & López Ramos, J. A. (2024) · Electronics · doi:10.3390/electronics13244965 · Cited by 33
Hussain, B., Elmedany, W., & Sharif, M. S. (2022) · 2022 International Conference on Data Analytics for Business and Industry (ICDABI) · doi:10.1109/icdabi56818.2022.10041508 · Cited by 4
Metadata
- Authors
- Tahsien, S. M., Karimipour, H., & Spachos, P.
- Venue
- Journal of Network and Computer Applications
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 161
- Pages
- 102630
- ISSN
- 1084-8045 (ISSN-L)
- OpenAlex
- W3015246755
- Cited by
- 470
- References
- 187
- FWCI
- 37.25
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
