An Efficient Kernel Density Based Algorithm of Big Data in Cybersecurity for Enhancing Smart City
DOI:
https://doi.org/10.3991/ijoe.v18i01.27875Keywords:
Big data, cybersecurity, smart cities, auditing, SVM algorithm, KDEAbstract
Smart cities are attracting much interest in terms of future development. As new technologies come on stream, ordinary towns are reshaping themselves as smart cities, where technology is used to improve connections between all elements of the town. The technology can be embedded everywhere and can harvest data for dedicated smart city applications. Smart cities will have a huge number of different devices running these applications. There will be a substantial amount of data associated with these devices. In the interlinked smart city environment, many different messages could be shared between them. Such devices will be associated with many security risks and privacy issues, as many of the shared statistics could also hold personal data. A substantial review of research has been recently undertaken to ensure that data will be safe in the smart city environment. This review has included all the latest research in the area and is intended to ensure that all the data required to run green smart cities and the devices required for them will remain secure and confidential.
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Copyright (c) 2021 Khaled H. Alyoubi
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