Document Type

Journal Article

Publication Title

Complex Adaptive Systems Modeling

Publisher

Springer

School

School of Science

RAS ID

31507

Comments

Ahmed, M., & Pathan, A. S. K. (2020). False data injection attack (FDIA): An overview and new metrics for fair evaluation of its countermeasure. Complex Adaptive Systems Modeling, 8, Article 4. https://doi.org/10.1186/s40294-020-00070-w

Abstract

The concept of false data injection attack (FDIA) was introduced originally in the smart grid domain. While the term sounds common, it specifically means the case when an attacker compromises sensor readings in such tricky way that undetected errors are introduced into calculations of state variables and values. Due to the rapid growth of the Internet and associated complex adaptive systems, cyber attackers are interested in exploiting similar attacks in other application domains such as healthcare, finance, defense, governance, etc. In today’s increasingly perilous cyber world of complex adaptive systems, FDIA has become one of the top-priority issues to deal with. It is a necessity today for greater awareness and better mechanism to counter such attack in the cyberspace. Hence, this work presents an overview of the attack, identifies the impact of FDIA in critical domains, and talks about the countermeasures. A taxonomy of the existing countermeasures to defend against FDIA is provided. Unlike other works, we propose some evaluation metrics for FDIA detection and also highlight the scarcity of benchmark datasets to validate the performance of FDIA detection techniques. [Figure not available: see fulltext.] © 2020, The Author(s).

DOI

10.1186/s40294-020-00070-w

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Research Themes

Securing Digital Futures

Priority Areas

Artificial intelligence and autonomous systems

Included in

Engineering Commons

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