The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks
Open accessAbstract
With increasing reliance on Internet of Things (IoT) devices and services, the capability to detect intrusions and malicious activities within IoT networks is critical for resilience of the network infrastructure. In this paper, we present a novel model for intrusion detection based on two-layer dimension reduction and two-tier classification module, designed to detect malicious activities such as User to Root (U2R) and Remote to Local (R2L) attacks. The proposed model is using component analysis and linear discriminate analysis of dimension reduction module to spate the high dimensional dataset to a lower one with lesser features. We then apply a two-tier classification module utilizing Naïve Bayes and Certainty Factor version of K-Nearest Neighbor to identify suspicious behaviors. The experiment results using NSL-KDD dataset shows that our model outperforms previous models designed to detect U2R and R2L attacks.
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Cites
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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
Network Intrusion Detection for IoT Security Based on Learning Techniques
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Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches
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Internet of Things security and forensics: Challenges and opportunities
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Self-citation
Metadata
- Authors
- Pajouh, H. H., Javidan, R., Khayami, R., Dehghantanha, A., & Choo, K.-K. R.
- Venue
- IEEE Transactions on Emerging Topics in Computing
- Published
- 2019-04-01
- Volume
- 7
- Issue
- 2
- Pages
- 314-323
- ISSN
- 2168-6750 (ISSN-L)
- 2376-4562
- OpenAlex
- W2557450880
- Cited by
- 503
- References
- 54
- FWCI
- 24.00
- Type
- journal article
- Language
- en
- Open access
- green
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- Pajouh, H. H., Javidan, R., Khayami, R., Dehghantanha, A., & Choo, K.-K. R. (2019). A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks. IEEE Transactions on Emerging Topics in Computing. https://doi.org/10.1109/tetc.2016.2633228
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