Maryam Mahsal Khan1, Attaullah Buriro2, Tahir Ahmad3,*, Subhan Ullah4
CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4691-4705, 2024, DOI:10.32604/cmc.2024.057648
- 19 December 2024
Abstract With the ever-increasing continuous adoption of Industrial Internet of Things (IoT) technologies, security concerns have grown exponentially, especially regarding securing critical infrastructures. This is primarily due to the potential for backdoors to provide unauthorized access, disrupt operations, and compromise sensitive data. Backdoors pose a significant threat to the integrity and security of Industrial IoT setups by exploiting vulnerabilities and bypassing standard authentication processes. Hence its detection becomes of paramount importance. This paper not only investigates the capabilities of Machine Learning (ML) models in identifying backdoor malware but also evaluates the impact of balancing the dataset More >
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