Nasir Sayed1, Muhammad Shoaib2,*, Waqas Ahmed3, Sultan Noman Qasem4, Abdullah M. Albarrak4, Faisal Saeed5
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1351-1374, 2023, DOI:10.32604/cmc.2023.030831
- 22 September 2022
Abstract Due to their low power consumption and limited computing power, Internet of Things (IoT) devices are difficult to secure. Moreover, the rapid growth of IoT devices in homes increases the risk of cyber-attacks. Intrusion detection systems (IDS) are commonly employed to prevent cyberattacks. These systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate countermeasures. Attempts have been made in the past to detect new attacks using machine learning and deep learning techniques, however, these efforts have been unsuccessful. In this paper, we propose two deep learning models to automatically More >