Visible to the public A smart city cyber security platform for narrowband networks

TitleA smart city cyber security platform for narrowband networks
Publication TypeConference Paper
Year of Publication2017
AuthorsElsaeidy, A., Elgendi, I., Munasinghe, K. S., Sharma, D., Jamalipour, A.
Conference Name2017 27th International Telecommunication Networks and Applications Conference (ITNAC)
KeywordsComputer crime, cyber-attack detection, Data models, Deep Learning, denial of service attack, DoS, IDS, Intrusion detection, learning (artificial intelligence), LoRaWAN, Narrowband, narrowband networks, narrowband technologies, NB-IOT, Network Security Architecture, pubcrawl, public administration, resilience, Resiliency, security of data, Sigfox, smart cities, smart city, smart city cyber security platform, threat deep learning-based model
Abstract

Smart city is gaining a significant attention all around the world. Narrowband technologies would have strong impact on achieving the smart city promises to its citizens with its powerful and efficient spectrum. The expected diversity of applications, different data structures and high volume of connecting devices for smart cities increase the persistent need to apply narrowband technologies. However, narrowband technologies have recognized limitations regarding security which make them an attractive target to cyber-attacks. In this paper, a novel platform architecture to secure smart city against cyber attackers is presented. The framework is providing a threat deep learning-based model to detect attackers based on users data behavior. The proposed architecture could be considered as an attempt toward developing a universal model to identify and block Denial of Service (DoS) attackers in a real time for smart city applications.

URLhttp://ieeexplore.ieee.org/document/8215388/
DOI10.1109/ATNAC.2017.8215388
Citation Keyelsaeidy_smart_2017