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The recent advancement in mobile technology & wireless communication has change the way of people’s communication & execution of tasks. In location based services (LBS), there are large number of LBS users who are available to get their location based information. In LBS, Users work together mutually to compute the centroid by per-forming large number of data aggregation operation that aggregate user’s location before sending it to the LBS provider. Users have to submit their personalized information to the LBS provider. Location privacy is the one of the most critical issue. Homomorphic encryption technique ensures the secure data aggregation by encrypting the user’s location using Homomorphic encryption algorithm. For privacy requirement, semantic security is a standard for any encryption schema. Many Homomorphic encryption algorithm are available, so it’s require to investigate the performance of those that are semantically secure. In this paper, we will discuss homomorphic encryption algorithm and also attempt to evaluate the performance of various additive asymmetric Homomorphic encryption algorithms. Our work is inspired to recognize an asymmetric homomorphic encryption algorithms for LBS that offers strongest location privacy.

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) & without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability.  In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability.