Browsing by Author "Maseno, Elijah M."

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  • Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection 
    Maseno, Elijah M.; Wang, Zenghui (Springer, 2024-02)
    Intrusion detection systems play a critical role in the mitigation of cyber-attacks on the Internet of Things (IoT) environment. Due to the integration of many devices within the IoT environment, a huge amount of data is ...
  • Intrusion detection in IoT using ensemble approach 
    Maseno, Elijah M.; Wang, Zenghui (2023-08)
    Protection of the Internet of Things (IoT) devices is an area of concern, even with the success that has been achieved in this area. IoT involves configuring and deploying smart devices to send and share information. ...
  • Intrusion detection system in IoT based on GAELM hybrid method 
    Maseno, Elijah M.; Wang, Zenghui; Liu, Fangzhou (2023-07)
    —In recent years, we have witnessed rapid growth in the application of IoT globally. IoT has found its applications in governmental and non-governmental institutions. The integration of a large number of electronic ...
  • A novel Elm optimization and its application in IoT intrusion detection 
    Maseno, Elijah M.; Wang, Zenghui (Springer, 2024-09)
    Globally, the Internet of Things (IoT) has grown exponentially in the last few years. The integration of numerous IoT devices enhances connectivity but also exposes them to various cyber-attacks. With the increase of complex ...
  • A systematic review on hybrid intrusion detection system 
    Maseno, Elijah M.; Wang, Zenghui; Xing, Hongyan (Wiley, 2022-05)
    As computer networks keep growing at a high rate, achieving confidentiality, integrity, and availability of the information system is essential. Intrusion detection systems (IDSs) have been widely used to monitor and secure ...
  • Vishing attack detection model for mobile users 
    Maseno, Elijah M. (2017)
    Voice phishing (vishing) is a type of phishing attack where social engineers manipulate individuals during phone conversation into divulging sensitive information. Mobile users are target to most criminals, through mobile ...

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