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Title A Comprehensive Study Of Iot Security Risks In Building A Secure Smart City
ID_Doc 958
Authors Bhargava A.; Salunkhe G.; Bhargava S.; Goswami P.
Year 2021
Published Digital Cities Roadmap: IoT-Based Architecture and Sustainable Buildings
DOI http://dx.doi.org/10.1002/9781119792079.ch13
Abstract The Internet of Things (IoT) is capable of assimilating a variety of heterogeneous systems, by facilitating seamless access and communication amongst an expansive range of devices, people and their environment making it the key feature in developing the idea of Smart Cities. The advancement of technology and deployment of a plethora of digital devices across the city will also require resilience of the services provided and also the security of data. As the number of IoT devices increases, the data generated will also escalate which will require more efficient and sophisticated algorithms to handle the big data, so that optimized decisions could be made. Interdisciplinary components and integrative arrangements in the IoT system have instigated new security challenges. Present day security solutions are not effective in providing the solution and to meet up the requirements of heavy computation and communication load for IoT devices and are not capable of detecting zero-day attacks. Hence, perpetuating the security demand in a comprehensive IoT system is strenuous. A compendious solution is required to deal with the security issues. The objective of this chapter is to present a holistic review of ML/DL algorithms which can be deployed to improve security solutions. This chapter delineates aforesaid challenges on technology’s implementation and standardization, a brief overview of existing IoT architectures, enabling technologies and also explores the prospects of ML/DL methodologies that can be implemented on IoT platform to maintain an admissible level of services, security and privacy issues, aiming to enhance the overall experience of Smart Cities. © 2021 Scrivener Publishing LLC.
Author Keywords attacks; IoT architecture; machine learning; privacy; security; service management; smart cities


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