Yin, D and Zhang, L and Yang, K (2018) A DDoS Attack Detection and Mitigation with Software-Defined Internet of Things Framework. IEEE Access, 6. pp. 24694-24705. DOI https://doi.org/10.1109/ACCESS.2018.2831284
Yin, D and Zhang, L and Yang, K (2018) A DDoS Attack Detection and Mitigation with Software-Defined Internet of Things Framework. IEEE Access, 6. pp. 24694-24705. DOI https://doi.org/10.1109/ACCESS.2018.2831284
Yin, D and Zhang, L and Yang, K (2018) A DDoS Attack Detection and Mitigation with Software-Defined Internet of Things Framework. IEEE Access, 6. pp. 24694-24705. DOI https://doi.org/10.1109/ACCESS.2018.2831284
Abstract
With the spread of Internet of Things' (IoT) applications, security has become extremely important. A recent distributed denial-of-service (DDoS) attack revealed the ubiquity of vulnerabilities in IoT, and many IoT devices unwittingly contributed to the DDoS attack. The emerging software-defined anything (SDx) paradigm provides a way to safely manage IoT devices. In this paper, we first present a general framework for software-defined Internet of Things (SD-IoT) based on the SDx paradigm. The proposed framework consists of a controller pool containing SD-IoT controllers, SD-IoT switches integrated with an IoT gateway, and IoT devices. We then propose an algorithm for detecting and mitigating DDoS attacks using the proposed SD-IoT framework, and in the proposed algorithm, the cosine similarity of the vectors of the packet-in message rate at boundary SD-IoT switch ports is used to determine whether DDoS attacks occur in the IoT. Finally, experimental results show that the proposed algorithm has good performance, and the proposed framework adapts to strengthen the security of the IoT with heterogeneous and vulnerable devices.
Item Type: | Article |
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Uncontrolled Keywords: | Software-defined Internet of Things (SD-IoT); distributed denial of service (DDoS); attack detection; attack mitigation; cosine similarity |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 26 Jun 2018 12:30 |
Last Modified: | 30 Oct 2024 16:08 |
URI: | http://repository.essex.ac.uk/id/eprint/22259 |
Available files
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Licence: Creative Commons: Attribution-Noncommercial 3.0