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Security and Privacy in Smart Cities Using Artificial Intelligence against Cyber Attacks Using LSTM Modelling
alshabrawi, Rasha
alshabrawi, Rasha
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Abstract
A smart city is a city that uses sensors to collect information from environmental elements and analyze it in real time. A smart city improves social offices, transportation, and open spaces while advancing maintainability. This article aims to clarify cyber security and reveal insight into digital assurance, smart city examine-action, and boards, and give a few solutions to the various worries of residents who need digitization. It features questions related to metropolitan foundations, public prosperity, well-being, and promising responses to similar things, while also leveraging human reasoning and artificial intelligence. The significance of the present work is that the general population and the surface area of metropolitan regions are rapidly developing; this speedy advancement requires a collaborative organization to deal with the issues made. In the context of smart cities, security, and privacy are major issues. This work explores the use of LSTM modeling and artificial intelligence to overcome these problems. Utilizing the UNSW-15 dataset to create an intrusion detection system especially suited for smart city contexts is part of the study process. The sequential patterns in network traffic data are intended to be captured by the LSTM-based model architecture. With a test accuracy of 99.68% and a low test loss of 0.0112, the model demonstrates excellent accuracy and is useful for correctly recognizing and categorizing network threats. To secure sensitive information inside the network traffic data, anonymization, and encryption techniques are also used, which involve privacy considerations. The study demonstrates how LSTM-based models might improve security and privacy in smart cities, laying the groundwork for further investigation and advancements in this area.