Computational Intelligence based Intrusion Detection Systems for Wireless Communication
This work addresses security and data confidentiality issues in wireless communication for IoT applications, representing an incremental advancement in intrusion detection methods.
The paper tackles the security challenges in wireless networks, particularly for Internet of Things devices, by proposing a novel three-tier architecture for intrusion detection systems using computational intelligence techniques to detect malicious activities.
The emerging trend of ubiquitous and pervasive computing aims at embedding everyday devices such as wristwatches, smart phones, home video systems, autofocus cameras, intelligent vehicles, musical instruments, kitchen appliances etc. with microprocessors and imparts them with wireless communication capability. This advanced computing paradigm, also known as the Internet of Things or cyber-physical computing, leads internet and computing to appear everywhere and anywhere using any device and location. With maximum appreciation and due regards to the evolutionary arc, depth and scope of ceaseless internet utilities, it is equally necessary to envisage the security and data confidentiality challenges posed by the free and ubiquitous availability of internet. This paper analyses the role of computational intelligence techniques to design adaptive and cognitive intrusion detection systems that can efficiently detect malicious network activities and proposes novel three-tier architecture for designing intelligent intrusion detection systems for wireless networks.