4 research outputs found
Comprehensive Survey and Taxonomies of False Injection Attacks in Smart Grid: Attack Models, Targets, and Impacts
Smart Grid has rapidly transformed the centrally controlled power system into
a massively interconnected cyber-physical system that benefits from the
revolutions happening in the communications (e.g. 5G) and the growing
proliferation of the Internet of Things devices (such as smart metres and
intelligent electronic devices). While the convergence of a significant number
of cyber-physical elements has enabled the Smart Grid to be far more efficient
and competitive in addressing the growing global energy challenges, it has also
introduced a large number of vulnerabilities culminating in violations of data
availability, integrity, and confidentiality. Recently, false data injection
(FDI) has become one of the most critical cyberattacks, and appears to be a
focal point of interest for both research and industry. To this end, this paper
presents a comprehensive review in the recent advances of the FDI attacks, with
particular emphasis on 1) adversarial models, 2) attack targets, and 3) impacts
in the Smart Grid infrastructure. This review paper aims to provide a thorough
understanding of the incumbent threats affecting the entire spectrum of the
Smart Grid. Related literature are analysed and compared in terms of their
theoretical and practical implications to the Smart Grid cybersecurity. In
conclusion, a range of technical limitations of existing false data attack
research is identified, and a number of future research directions is
recommended.Comment: Double-column of 24 pages, prepared based on IEEE Transaction articl