April 2025
Intermediate to advanced
480 pages
12h 39m
English
book
Next-Generation Systems and Secure Computing
by Subhabrata Barman, Santanu Koley, Subhankar Joardar
Content preview from Next-Generation Systems and Secure Computing
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13Security Analysis for Mobile Crowdsensing Scheme by Predicting Vehicle Mobility Using Deep Learning Algorithm
Monojit Manna1*, Arpan Adhikary1,2 and Sima Das2,3
1RCC Institute of Information Technology, Beleghata, Kolkata, India
2Bengal College of Engineering and Technology, Durgapur, India
3Haldia Institute of Technology, Haldia Purba Medinipur, India
Abstract
Mobile crowdsensing (MCS) systems are designed to improve multimedia service quality and encourage safe sensing in Internet of Things applications such as medical and traffic monitoring. Currently, mobile vehicles are used in metropolitan areas to perform data sensing and collection tasks for mobility and universality. In this study, we focused on large-scale dynamic and heterogeneous networks. To fulfil the necessary data in the future era within a few minutes, systems must handle security concerns, including jamming, spoofing, and fake sensing attacks during both the sensing and information exchange phases. To configure the maximum data optimization problem and budget, we map the requirements of the vehicle. The implementation of the program is essentially designed to generate a realistic online platform where real-time automobiles appear to be moving continuously. We examined safe mobile crowdsensing and outlined applications for deep learning (DL) techniques. The data center has the authority to immediately select a set of vehicles. Mobile vehicles (DLMV) will be used in a deep-learning-based plan to gather sensing ...
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