Collaborative intrusion detection system in cognitive smart city network (CSC-Net)
Artificial Intelligence (AI); Cognitive Smart City Network (CSC-Net); Internet of Things (IoT); Mobile Edge Computing Solution (MEC); Smart environment
Smart environment is about incorporating smart thinking in the environment and implementing the technical intervention that improvise the city's environment. Artificial intelligence (AI) provides solutions in huge technological issues in various aspects of day-to-day life such as autonomous transportation, governance, healthcare, agriculture, maintenance, logistics, and education that are automated, managed, controlled, and accessed remotely with the aid of smart devices. Cognitive computing is denoted as a next-generation AI-dependent method that gives human-computer interactions with personalized services that replicate manual behavior. Simultaneously, massive data is generated from the applications of the smart city like smart transportation, retail industry, healthcare, and governance. It is necessary to obtain a reliable, sustainable, continuous, and secure framework in the cloud centralized infrastructure. In this research article, the authors proposed the architecture of cognitive smart city network (CSC-Net) that defines how data are collected from applications of smart city and scrutinized by cognitive computing. This research article predicts the mobile edge computing solution (MEC) that permits node collaboration between internet of things (IoT) devices for providing secure and reliable communication among smart devices and fog layer, conversely fog layer and cloud layer. This proposed work helps to reduce the excessive traffic flow in smart environment with the support of node to node communication protocols. Collaborative-dependent intrusion detection system (C-IDS) is proposed to solve the data security issues in fog and cloud layers. Copyright 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Daniel D.; Preethi N.; Jakka A.; Eswaran S.
International Journal of Knowledge and Systems Science, Vol-12, No. 1, pp. 60-73.
https://doi.org/10.4018/IJKSS.2021010105 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100421747&doi=10.4018%2fIJKSS.2021010105&partnerID=40&md5=7b4196eb7ac6e98a947d979eb93c5afd
Daniel D., Christ University (Deemed), Kengeri, India; Preethi N., Christ University (Deemed), Kengeri, India; Jakka A., University of Pittsburgh, United States; Eswaran S., PES University, India