journal article·2023-04-14Open access

Distributed Blockchain-SDN Secure IoT System Based on ANN to Mitigate DDoS Attacks

Rihab Jmal, Walid Ghabri, Ramzi Guesmi, Badr M. Alshammari, Ahmed S. Alshammari, Haitham Alsaif

Applied Sciences· Volume 13· Issue 8

Abstract

By bringing smart and advanced solutions, the Internet of Things (IoT) has opened up new dimensions of innovative services and processing power for contemporary living standards. IoT has a wide range of devices and communication entities as a result of the widespread applications of these services, making network management a challenging task. Therefore, it is critical to redesign the IoT network’s management. The inherent programmability and centralized capabilities of software-defined networking (SDN) make network management simpler, enable network abstraction, make network evolution easier, and have the potential to handle the IoT network. However, security issues still present the IoT dilemma. Distributed Denial of Service (DDoS) attacks are among the most significant security threats in IoT systems. This paper studies in-depth DDoS attacks in IoT and in SDN. A review of different detection and mitigation techniques based on SDN, blockchain and machine learning models is conducted. A holistic, secure IoT system is proposed on the basis of SDN with multicontrollers. Blockchain is considered to guarantee security in distributed SDN-IoT networks and ANN to improve the detection and mitigation process.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Network Security and Intrusion Detection · Software-Defined Networks and 5G · Smart Grid Security and Resilience

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Higher Institute of Computer Science and Multimedia of Sfax (ISIMS), University of Sfax, Sfax 3021, Tunisia

SM@RTS Laboratory, Digital Research Center of Sfax (CRNS), Sfax 3021, Tunisia

ISLAI Beja, University of Jendouba, Beja 9000, Tunisia

Laboratory of Electronics and Information Technology, National Engineering School of Sfax, Sfax University, Sfax 3038, Tunisia

Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 81481, Saudi Arabia

Funding

Scientific Research Deanship at University of Ha’il—Saudi Arabia

References (54)

Show source-provided references
1. Internet of things (IoT), applications and challenges: A comprehensive review10.1007/s11277-020-07446-4 ↗
2. Application domains, evaluation data sets, and research challenges of IoT: A Systematic Review10.1109/JIOT.2020.3048439 ↗
3. Internet of Things (IoT) Enables Robot-Assisted Therapy as a Home Program for Training upper Limb Functions in Chronic Stroke: A Randomized Control Crossover Study10.1016/j.apmr.2022.08.976 ↗
4. Leveraging IIoT to improve machine safety in the mining industry
5. Integrating sensing and communications for ubiquitous IoT: Applications, trends, and challenges10.1109/MNET.010.2100152 ↗
6. Heidari, A., and Jabraeil Jamali, M.A. (2022). Internet of Things intrusion detection systems: A comprehensive review and future directions. Clust. Comput., 1–28.10.1007/s10586-022-03776-z ↗
7. Anatomy of threats to the internet of things10.1109/COMST.2018.2874978 ↗
8. DDoS attacks in IoT networks: A comprehensive systematic literature review10.1007/s11280-020-00855-2 ↗
9. Internet of Things Management Based on Software Defined Networking: A Survey10.1007/s10776-020-00488-2 ↗
10. An efficient counter-based DDoS attack detection framework leveraging software defined IoT (SD-IoT)10.1109/ACCESS.2020.3043082 ↗
11. Ali, J., and Roh, B.H. (2022). An Effective Approach for Controller Placement in Software-Defined Internet-of-Things (SD-IoT). Sensors, 22.10.3390/s22082992 ↗
12. Shah, Z., Ullah, I., Li, H., Levula, A., and Khurshid, K. (2022). Blockchain based solutions to mitigate distributed denial of service (ddos) attacks in the Internet of Things (IoT): A survey. Sensors, 22.10.3390/s22031094 ↗
13. Rathod, T., Jadav, N.K., Alshehri, M.D., Tanwar, S., Sharma, R., Felseghi, R.-A., and Raboaca, M.S. (2022). Blockchain for Future Wireless Networks: A Decade Survey. Sensors, 22.10.3390/s22114182 ↗
14. AlShamsi, M., Al-Emran, M., and Shaalan, K. (2022). A Systematic Review on Blockchain Adoption. Appl. Sci., 12.10.3390/app12094245 ↗
15. Heidari, A., Navimipour, N.J., and Unal, M. (2023). A Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Drones. IEEE Internet Things J., 1.10.1109/JIOT.2023.3237661 ↗
16. Chaganti, R., Bhushan, B., and Ravi, V. (arXiv, 2022). The role of Blockchain in DDoS attacks mitigation: Techniques, open challenges and future directions, arXiv, preprint.10.1016/j.comcom.2022.10.026 ↗
17. Wang, S., Gomez, K., Sithamparanathan, K., Asghar, M.R., Russello, G., and Zanna, P. (2021). Mitigating ddos attacks in sdn-based iot networks leveraging secure control and data plane algorithm. Appl. Sci., 11.10.3390/app11030929 ↗
18. Gadze, J.D., Bamfo-Asante, A.A., Agyemang, J.O., Nunoo-Mensah, H., and Opare, K.A.B. (2021). An investigation into the application of deep learning in the detection and mitigation of DDOS attack on SDN controllers. Technologies, 9.10.3390/technologies9010014 ↗
19. Islam, U., Muhammad, A., Mansoor, R., Hossain, M.S., Ahmad, I., Eldin, E.T., Khan, J.A., Rehman, A.U., and Shafiq, M. (2022). Detection of distributed denial of service (DDoS) attacks in IOT based monitoring system of banking sector using machine learning models. Sustainability, 14.10.3390/su14148374 ↗
20. Mishra, S., Albarakati, A., and Sharma, S.K. (2022). Cyber Threat Intelligence for IoT Using Machine Learning. Processes, 10.10.3390/pr10122673 ↗
21. Sarker, I.H., Khan, A.I., Abushark, Y.B., and Alsolami, F. (2022). Internet of Things (IoT) security intelligence: A comprehensive overview, machine learning solutions and research directions. Mob. Netw. Appl., 1–17.10.1007/s11036-022-01937-3 ↗
22. The DDoS attacks detection through machine learning and statistical methods in SDN10.1007/s11227-020-03323-w ↗
23. A comprehensive survey on attacks, security issues and blockchain solutions for IoT and IIoT10.1016/j.jnca.2019.102481 ↗
24. Ibrahim, R.F., Abu Al-Haija, Q., and Ahmad, A. (2022). DDoS Attack Prevention for Internet of Thing Devices Using Ethereum Blockchain Technology. Sensors, 22.10.3390/s22186806 ↗
25. Yamaguchi, S., and Gupta, B. (2021). Research Anthology on Combating Denial-of-Service Attacks, IGI Global.
26. Towards a deep learning-driven intrusion detection approach for Internet of Things10.1016/j.comnet.2020.107784 ↗
27. Toward a distributed approach for detection and mitigation of denial-of-service attacks within industrial Internet of Things10.1109/JIOT.2020.3028652 ↗
28. Distributed denial of service attacks and its defenses in IoT: A survey10.1007/s11227-019-02945-z ↗
29. Bekri, W., Layeb, T., Jmal, R., and Fourati, L.C. (June, January 30). Intelligent IoT Systems: Security issues, attacks, and countermeasures. Proceedings of the 2022 International Wireless Communications and Mobile Computing (IWCMC), Dubrovnik, Croatia.10.1109/IWCMC55113.2022.9825120 ↗
30. Software-defined networking-based DDoS defense mechanisms10.1145/3301614 ↗
31. Detection and mitigation of DDoS attacks in SDN: A comprehensive review, research challenges and future directions10.1016/j.cosrev.2020.100279 ↗
32. New-flow based DDoS attacks in SDN: Taxonomy, rationales, and research challenges10.1016/j.comcom.2020.02.085 ↗
33. Security in software-defined networking: Threats and countermeasures10.1007/s11036-016-0676-x ↗
34. DoS and DDoS attacks in Software Defined Networks: A survey of existing solutions and research challenges10.1016/j.future.2021.03.011 ↗
35. Techniques for DDoS Attack in SDN: A Comparative Study
36. A survey of distributed denial-of-service attack, prevention, and mitigation techniques10.1177/1550147717741463 ↗
37. A survey on blockchain, SDN and NFV for the smart-home security10.1016/j.iot.2022.100588 ↗
38. On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives10.1007/s10922-022-09682-4 ↗
39. A survey of Blockchain technologies applied to software-defined networking: Research challenges and solutions10.1049/wss2.12031 ↗
40. Derhab, A., Guerroumi, M., Gumaei, A., Maglaras, L., Ferrag, M.A., Mukherjee, M., and Khan, F.A. (2019). Blockchain and random subspace learning-based IDS for SDN-enabled industrial IoT security. Sensors, 19.10.3390/s19143119 ↗
41. Boukria, S., Guerroumi, M., and Romdhani, I. (July, January 29). BCFR: Blockchain-based controller against false flow rule injection in SDN. Proceedings of the 2019 IEEE Symposium on Computers and Communications (ISCC), Barcelona, Spain.10.1109/ISCC47284.2019.8969780 ↗
42. Zhao, B., Liu, Y., Li, X., Li, J., and Zou, J. (2020). TrustBlock: An adaptive trust evaluation of SDN network nodes based on double-layer blockchain. PLoS ONE, 15.10.1371/journal.pone.0228844 ↗
43. Distributed blockchain-based trusted multidomain collaboration for mobile edge computing in 5G and beyond10.1109/TII.2020.2964563 ↗
44. Fernando, P., and Wei, J. (2020, January 10–13). Blockchain-powered software defined network-enabled networking infrastructure for cloud management. Proceedings of the 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA.10.1109/CCNC46108.2020.9045378 ↗
45. BMC-SDN: Blockchain-based multicontroller architecture for secure software-defined networks10.1155/2021/9984666 ↗
46. Collaborative detection and mitigation of distributed denial-of-service attacks on software-defined network10.1007/s11036-020-01552-0 ↗
47. Deep-learning-based blockchain framework for secure software-defined industrial networks10.1109/TII.2020.2968946 ↗
48. Hayat, R.F., Aurangzeb, S., Aleem, M., Srivastava, G., and Lin, J.C. (2022). ML-DDoS: A blockchain-based multilevel DDoS mitigation mechanism for IoT environments. IEEE Trans. Eng. Manag., 1–14.10.1109/TEM.2022.3170519 ↗
49. A flexible SDN-based framework for slow-rate DDoS attack mitigation by using deep reinforcement learning10.1016/j.jnca.2022.103444 ↗
50. Bhale, P., Chowdhury, D.R., Biswas, S., and Nandi, S. (2023). OPTIMIST: Lightweight and Transparent IDS with Optimum Placement Strategy to Mitigate Mixed-rate DDoS Attacks in IoT Networks. IEEE Internet Things J., 1.10.1109/JIOT.2023.3234530 ↗
51. Low-rate DDoS attack detection based on factorization machine in software defined network10.1109/ACCESS.2020.2967478 ↗
52. Intrusion Detection System for IoT Based on Deep Learning and Modified Reptile Search Algorithm10.1155/2022/6473507 ↗
53. Sarica, A.K., and Angin, P. (2020, January 2–6). A novel sdn dataset for intrusion detection in iot networks. Proceedings of the 2020 16th International Conference on Network and Service Management (CNSM), Izmir, Turkey.
54. Heuristic recommendation technique in Internet of Things featuring swarm intelligence approach10.1016/j.eswa.2021.115904 ↗