Secure and Efficient Data Collection and Storage of IoT in Smart Ocean

• Published in: IEEE internet of things journal Vol. 7; no. 10; pp. 9980 - 9994
• Main Authors: Hu, Chunqiang, Pu, Yuwen, Yang, Feihong, Zhao, Ruifeng, Alrawais, Arwa, Xiang, Tao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analytical models; Base stations; Cryptography; Curves; Data collection; Data compression; Denial of service attacks; Digital signatures; Environmental protection; Failure analysis; Internet of Things; Lossless equipment; Marine resources; Nodes; Oceans; Security; Sensors; smart ocean; storage; Underwater; underwater wireless sensor networks (UWSNs)
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2020.2988733

Due to the abundant marine resources, smart ocean has attracted much attention of the government, industry, and academy. The Internet-of-Things (IoT) architectures for smart ocean have been proposed to collect various of data from the ocean, thereby assisting environmental protection, military reconnaissance, and so on. However, few researchers have paid attention to the security and privacy issues of data collection and transmission. In this article, for the unreliable underwater environment, we present a secure, efficient, and complete data collection, and transmission and storage scheme for IoT in smart ocean. Especially, to prolong the lifetime of the underwater node, two novel data compression algorithms [lossy data compression algorithm (LCA) and lossless data compression algorithm (NLCA)] are also proposed. Moreover, due to the vulnerability of underwater nodes, we also propose a corresponding IoT framework and data collection pattern to resist the single point failure attack. Besides, to guarantee the confidentiality, reliability, and integrity of transmitting data, Elliptic Curve-ElGamal (EC-ElGamal) and elliptic curve digital signature algorithm (ECDSA) are employed. The consensus algorithm and blacklisting mechanism are also employed to detect and address failure or malicious nodes. Finally, the security analysis demonstrates that our scheme is able to resist many typical attacks for underwater nodes, such as manipulation attacks, Distributed Denial-of-Service (DDoS) attacks, malicious node injection attacks, and so on. Additionally, relevant experimental results show that the scheme is feasibility and efficiency.