Issue |
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
|
|
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Article Number | 01089 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/matecconf/202439201089 | |
Published online | 18 March 2024 |
Progressive Collaborative Method for Protecting Users Privacy in Location-Based Services
1 CSE Department, KG Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
2 Département of EEE, Bhagwant University, Rajasthan - India
3 Département of ECM, JBIET, Hyderabad - Telangana, India
4 CSE Department, KG Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
5 Département of EEE, Bhagwant University, Rajasthan - India
* Corresponding author: Krkreddy20@gmail.com
The development of new mobile communication and information service technologies has opened up exciting possibilities for location-based services. Users of location-based services (LBS) can access vital data from their service providers by utilizing their location data. Maps and navigation, information services, tourist information services, social networking, and many more popular applications are available. A user's location and other personal details must be submitted to the providers of location-based services in order for them to work. For example, details about one's whereabouts and identity. By "location privacy," we mean the idea that third parties shouldn't be able to track a user's precise whereabouts. It is important that users' sensitive information be hidden from unauthorized individuals when communicating. Most difficult in LBS location-based are concerns about communications and data. Each peer does their duty reciprocally in a collaborative method, which is a completely distributed technique. For the most secure and private location-based services (LBS), it employs cryptographic methods. The number of people using LBS is growing at a rapid pace these days. At this time, there isn't a single method available that has scalability capabilities. Building a realistic and computationally efficient solution that offers high privacy while decreasing processing overhead and improving scalability is a challenging task. The suggested method is cost-effective, supports scaling, is highly resilient against security and privacy assaults, and ensures privacy.
Key words: Collaborative / TTP Free / LBS / Privacy / Scalability / Homomorphic Encryption
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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