Mashael M Asiri1, Heba G. Mohamed2, Mohamed K Nour3, Mesfer Al Duhayyim4,*, Amira Sayed A. Aziz5, Abdelwahed Motwakel6, Abu Sarwar Zamani6, Mohamed I. Eldesouki7
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1679-1694, 2023, DOI:10.32604/csse.2023.031063
Abstract Due to exponential increase in smart resource limited devices and high speed communication technologies, Internet of Things (IoT) have received significant attention in different application areas. However, IoT environment is highly susceptible to cyber-attacks because of memory, processing, and communication restrictions. Since traditional models are not adequate for accomplishing security in the IoT environment, the recent developments of deep learning (DL) models find beneficial. This study introduces novel hybrid metaheuristics feature selection with stacked deep learning enabled cyber-attack detection (HMFS-SDLCAD) model. The major intention of the HMFS-SDLCAD model is to recognize the occurrence of cyberattacks in the IoT environment. At… More >