Open Access

REVIEW

Security and Privacy Challenges in SDN-Enabled IoT Systems: Causes, Proposed Solutions, and Future Directions

by Ahmad Rahdari^1,6, Ahmad Jalili², Mehdi Esnaashari³, Mehdi Gheisari^1,4,7,8,*, Alisa A. Vorobeva⁵, Zhaoxi Fang¹, Panjun Sun^1,*, Viktoriia M. Korzhuk⁵, Ilya Popov⁵, Zongda Wu¹, Hamid Tahaei¹

1 Institute of Artificial Intelligence, Shaoxing University, Shaoxing, 312000, China
2 Department of Computer Engineering, Gonbad Kavous University, Gonbad-e Kavus, 49717-99151, Iran
3 Faculty of Computer Engineering, K. N. Toosi University of Technology, Tehran, 196976-4499, Iran
4 Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India
5 Secure Information Technologies Department, National Research University ITMO, St. Petersburg, 197101, Russia
6 School of Electrical and Computer Engineering, Shiraz University, Shiraz, 71946–84334, Iran
7 Department of Computer Science and Engineering, Islamic Azad University, Damavand, 1477893855, Iran
8 Department of R&D, Shenzhen BKD Co., Ltd., Shenzhen, 518000, China

* Corresponding Authors: Mehdi Gheisari. Email: ; Panjun Sun. Email:

Computers, Materials & Continua 2024, 80(2), 2511-2533. https://doi.org/10.32604/cmc.2024.052994

Received 21 April 2024; Accepted 26 June 2024; Issue published 15 August 2024

Abstract

Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes. A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy protection. Recent investigations have explored cutting-edge methods, such as leveraging blockchain for transaction recording to enhance security and privacy, along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Moreover, the analysis indicates that encryption and hashing techniques are prevalent in the data plane, whereas access control and certificate authorization are prominently considered in the control plane, and authentication is commonly employed within the application plane. Additionally, this paper outlines future directions, offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.

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Keywords

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