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Using machine learning to secure IoT systems
Abstract
The Internet of Things (IoT) is a massive group of devices containing sensors or actuators connected together over wired or wireless networks. With an estimate of over 25 billion devices connected together by 2020, IoT has been rapidly growing over the past decade. During the growth, security has been identified as one of the weakest areas in IoT. When implementing security within an IoT network, there are several challenges including heterogeneity within the system as well as the quantity of devices that need to be addressed. To approach the challenges in securing IoT devices, we propose using machine learning within an IoT gateway to help secure the system. We investigate using Artificial Neural Networks in a gateway to detect anomalies in the data sent from the edge devices. We are convinced that this approach can improve the security of IoT systems.
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Cited by
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988293 · Cited by 1,392
Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking
Restuccia, F., D'Oro, S., & Melodia, T. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2846040 · Cited by 286
A Machine Learning Security Framework for Iot Systems
Bagaa, M., Taleb, T., Bernabe, J. B., & Skarmeta, A. (2020) · IEEE Access · doi:10.1109/access.2020.2996214 · Cited by 271
Internet of Things: Evolution, Concerns and Security Challenges
Malhotra, P., Singh, Y., Anand, P., Bangotra, D. K., Singh, P. K., & Hong, W.-C. (2021) · Sensors · doi:10.3390/s21051809 · Cited by 260
Role of Artificial Intelligence in the Internet of Things (IoT) cybersecurity
Kuzlu, M., Fair, C., & Guler, O. (2021) · Discover Internet of Things · doi:10.1007/s43926-020-00001-4 · Cited by 259
Metadata
- Authors
- Canedo, J., & Skjellum, A.
- Venue
- 2016 14th Annual Conference on Privacy, Security and Trust (PST)
- Publisher
- IEEE
- Published
- 2016-12
- Pages
- 219-222
- OpenAlex
- W2608418534
- Cited by
- 202
- References
- 0
- FWCI
- 8.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Canedo, J., & Skjellum, A. (2016). Using machine learning to secure IoT systems. 2016 14th Annual Conference on Privacy, Security and Trust (PST). https://doi.org/10.1109/pst.2016.7906930
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
