A comprehensive survey on data provenance: State-of-the-art approaches and their deployments for IoT security enforcement

Article type: Research Article

Authors: Alam, Md Morshed^{; *} | Wang, Weichao

Affiliations: Department of Software and Information Systems, University of North Carolina at Charlotte, NC, USA. E-mails: malam3@uncc.edu, wwang22@uncc.edu

Correspondence: [*] Corresponding author. E-mail: malam3@uncc.edu.

Abstract: Data provenance collects comprehensive information about the events and operations in a computer system at both application and kernel levels. It provides a detailed and accurate history of transactions that help delineate the data flow scenario across the whole system. Data provenance helps achieve system resilience by uncovering several malicious attack traces after a system compromise that are leveraged by the analyzer to understand the attack behavior and discover the level of damage. Existing literature demonstrates a number of research efforts on information capture, management, and analysis of data provenance. In recent years, provenance in IoT devices attracts several research efforts because of the proliferation of commodity IoT devices. In this survey paper, we present a comparative study of the state-of-the-art approaches to provenance by classifying them based on frameworks, deployed techniques, and subjects of interest. We also discuss the emergence and scope of data provenance in IoT network. Finally, we present the urgency in several directions that data provenance needs to pursue, including data management and analysis.

Keywords: Data provenance, information flow control, digital forensic, Internet of Things, cyber-physical systems

DOI: 10.3233/JCS-200108

Journal: Journal of Computer Security, vol. 29, no. 4, pp. 423-446, 2021