Command Injection Attacks in Smart Grids: A Survey

• Published in: IEEE open journal of industry applications Vol. 5; pp. 1 - 11
• Main Authors: Usama, Muhammad, Aman, Muhammad Naveed
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: AI-based detection algorithms; and model-based detection; Artificial intelligence (AI)-based detection algorithms; command injection; Computer crime; Critical infrastructure; Cyber-physical systems; cyber-physical systems (CPSs); Cybersecurity; detection techniques; model-based detection; Power system reliability; Safety; Security; Smart grid; Smart grids; Surveys
• ISSN: 2644-1241; 2644-1241
• DOI: 10.1109/OJIA.2024.3365576

Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The False Command Injection Attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This paper presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this paper provides an extensive review of detection studies, categorizing them based on the type of detection technique employed.