ZIRCON: Zero-watermarking-based approach for data integrity and secure provenance in IoT networks

Omair Faraj, David Megías, Joaquin Garcia-Alfaro

Research output: Contribution to journalArticlepeer-review

Abstract

The Internet of Things (IoT) is integrating the Internet and smart devices in almost every domain, such as home automation, e-healthcare systems, vehicular networks, industrial control, and military applications. In these areas, sensory data, which is collected from multiple sources and managed through intermediate processing by multiple nodes, is used for decision-making processes. Ensuring data integrity and keeping track of data provenance are core requirements in such a highly dynamic context, since data provenance is an important tool for the assurance of data trustworthiness. Dealing with such requirements is challenging due to the limited computational and energy resources in IoT networks. This requires addressing several challenges such as processing overhead, secure provenance, bandwidth consumption and storage efficiency. In this paper, we propose Zero-watermarkIng based data pRovenanCe for iOt Networks (ZIRCON), a novel zero-watermarking approach to securely transmit provenance and ensure data integrity of sensor data in an IoT network. In ZIRCON, provenance information is stored in a tamper-proof network database through watermarks, generated at the source node before transmission. We provide an extensive security analysis showing the resilience of our scheme against passive and active attacks. We also compare our scheme with existing works based on performance metrics such as computational time, energy usage, and cost analysis. The results show that ZIRCON is robust against several attacks, lightweight, storage-efficient, and better in energy usage and bandwidth consumption, compared to prior art.

Original languageEnglish
Article number103840
JournalJournal of Information Security and Applications
Volume85
DOIs
Publication statusPublished - 1 Sept 2024

Keywords

  • Cryptography
  • Cybersecurity
  • Data integrity
  • Data provenance
  • Internet of Things
  • Intrusion detection
  • Zero-watermarking

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