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

• Published in: Applied sciences Vol. 13; no. 8; p. 4953
• Main Authors: Jmal, Rihab, Ghabri, Walid, Guesmi, Ramzi, Alshammari, Badr M., Alshammari, Ahmed S., Alsaif, Haitham
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2023
• Subjects: ANN; Assaults; Blockchain; DDoS; Deep learning; Denial of service attacks; Infrastructure; Internet of Things; Internet of Things (IoT); Machine learning; Malware; Mitigation; Optimization techniques; Ransomware; Redesign; security; Software; Software-defined networking; software-defined networking (SDN); Virtual private networks; Tunisia
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13084953

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.