首页|IoT-Dedup: Device Relationship-Based IoT Data Deduplication Scheme

IoT-Dedup: Device Relationship-Based IoT Data Deduplication Scheme

扫码查看
原文链接
  • NETL
  • NSTL
  • IEEE
The cyclical and continuous working characteristics of Internet of Things (IoT) devices make a large amount of the same or similar data, which can significantly consume storage space. To solve this problem, various secure data deduplication schemes have been proposed. However, existing deduplication schemes only perform deduplication based on data similarity, ignoring the internal connection among devices, making the existing schemes not directly applicable to parallel and distributed scenarios like IoT. Furthermore, since secure data deduplication leads to multiple users sharing same encryption key, which may lead to security issues. To this end, we propose a device relationship-based IoT data deduplication scheme that fully considers the IoT data characteristics and devices internal connections. Specifically, we propose a device relationship prediction approach, which can obtain device collaborative relationships by clustering the topology of their communication graph, and classifies the data types based on device relationships to achieve data deduplication with different security levels. Then, we design a similarity-preserving encryption algorithm, so that the security level of encryption key is determined by the data type, ensuring the security of the deduplicated data. In addition, two different data deduplication methods, identical deduplication and similar deduplication, have been designed to meet the privacy requirement of different data types, improving the efficiency of deduplication while ensuring data privacy as much as possible. We evaluate the performance of our scheme using five real datasets, and the results show that our scheme has favorable results in terms of both deduplication performance and computational cost.

Internet of ThingsPerformance evaluationEncryptionSecurityElectronic mailClustering algorithmsData privacyClustering methodsTopologyTemperature sensors

Yuan Gao、Liquan Chen、Jianchang Lai、Tianyi Wang、Xiaoming Wu、Shui Yu

展开 >

School of Computer Science & Technology, China University of Mining and Technology, Xuzhou, China|Mine Digitization Engineering Research Center of the Ministry of Education, Xuzhou, China

School of Cyber Science and Engineering, Southeast University, Nanjing, China

Nanyang Technological University, Singapore

Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China

School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia

展开 >

2025

10.1109/TPDS.2025.3544315

IEEE transactions on parallel and distributed systems

IEEE transactions on parallel and distributed systems

SCI
ISSN：
年,卷(期)：2025.36(5)
  • 36