Ashraf S. Mashaleh^1,2,*, Noor Farizah Binti Ibrahim¹, Mohammad Alauthman³, Mohammad Almseidin⁴, Amjad Gawanmeh⁵

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2245-2267, 2024, DOI:10.32604/cmc.2023.047323

Abstract Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards. As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods. This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization (PSO) to address the risks associated with IoT botnets. Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically. Fuzzy component settings are optimized using PSO to improve accuracy. The methodology allows for more complex thinking by transitioning from binary to continuous assessment. Instead of expert inputs, PSO data-driven tunes rules and membership functions. This study presents a… More >

Donghyun Kim¹, Seungho Jeon², Jiho Shin³, Jung Taek Seo^4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2979-2997, 2023, DOI:10.32604/iasc.2023.040019

Abstract The smart city comprises various infrastructures, including healthcare, transportation, manufacturing, and energy. A smart city’s Internet of Things (IoT) environment constitutes a massive IoT environment encompassing numerous devices. As many devices are installed, managing security for the entire IoT device ecosystem becomes challenging, and attack vectors accessible to attackers increase. However, these devices often have low power and specifications, lacking the same security features as general Information Technology (IT) systems, making them susceptible to cyberattacks. This vulnerability is particularly concerning in smart cities, where IoT devices are connected to essential support systems such as healthcare and transportation. Disruptions can lead… More >

Ye-Eun Kim¹, Min-Gyu Kim², Hwankuk Kim^2,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4467-4488, 2022, DOI:10.32604/cmc.2022.026581

Abstract As Internet of Things (IoT) devices with security issues are connected to 5G mobile networks, the importance of IoT Botnet detection research in mobile network environments is increasing. However, the existing research focused on AI-based IoT Botnet detection research in wired network environments. In addition, the existing research related to IoT Botnet detection in ML-based mobile network environments have been conducted up to 4G. Therefore, this paper conducts a study on ML-based IoT Botnet traffic detection in the 5G core network. The binary and multiclass classification was performed to compare simple normal/malicious detection and normal/three-type IoT Botnet malware detection. In… More >