An Identity-Based Data Integrity Auditing Scheme for Cloud-Based Maritime Transportation Systems

Xiong Li, Shuai Shang, Shanpeng Liu, Ke Gu, Mian Ahmad Jan, Xiaosong Zhang, Fazlullah Khan

Research output: Journal PublicationArticlepeer-review

7 Citations (Scopus)


With the development of Internet of Things (IoT)-enabled Maritime Transportation Systems (MTS), massive data generated in the system not only requires to be stored reliably and cheaply, but also needs to be analyzed timely. The Cloud-based Maritime Transportation Systems (CMTS) allow users to upload the data without worrying about the price, capacity, location and so on. However, CMTS also brings some security issues, where the integrity protection of outsourced data is one of the most important issues since it is crucial for the safety, reliability and efficiency of sea lanes. To solve this problem, we propose an identity-based dynamic data integrity auditing scheme for CMTS. Our scheme decreases the burden of key management and improves the auditing efficiency by batch auditing. Besides, our scheme also supports dynamic operations on the outsourced data for CMTS. The security analysis shows that our scheme can ensure the feature of storage correctness and resist common attacks. In addition, the performance comparison results with other related schemes show that our scheme not only has the lowest computational cost on all entities, but also greatly reduces the communication overhead of the auditing phase. Therefore, our scheme is very suitable for data integrity verification in CMTS.

Original languageEnglish
Pages (from-to)2556-2567
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number2
Publication statusPublished - 1 Feb 2023
Externally publishedYes


  • batch auditing
  • cloud storage
  • dynamic operations
  • identity-based integrity auditing
  • Maritime transportation systems

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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