Efficient and Privacy – Preserving Polygons Spatial Query Framework for Location – Based Services

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Efficient and Privacy-preserving Polygons Spatial Query Framework for Location-based Services

Efficient and Privacy – Preserving Polygons Spatial Query Framework for
Location – Based Services

Abstract

Efficient and Privacy-Preserving

Efficient and Privacy-Preserving Polygons Spatial Query Framework for Location-Based Services,With the pervasiveness of mobile devices and the development of wireless communication technique, location-based services (LBSs) have made our life more convenient, and the polygons spatial query, which can provide more flexible LBS, has attracted considerable interest recently. However, the flourish of polygons spatial query still faces many challenges including the query information privacy. In this Efficient and Privacy-preserving Polygons Spatial Query Framework system project paper, we present an efficient and privacy-preserving polygons spatial query framework for location-based services, called Polaris.

System Configuration

H/W System Configuration
Speed                   : 1.1 GHz
RAM                      : 256 MB(min)
Hard Disk              : 20 GB
Floppy Drive          : 1.44 MB
Key Board             : Standard Windows Keyboard
Mouse                  : Two or Three Button Mouse
Monitor                : SVGA
S/W System Configuration

Platform                     :  IOT

Operating system       : Windows Xp,7,
Server                       : WAMP/Apache
Working on                : Browser Like Firefox, IE

Conclusion

In this Efficient and Privacy-Preserving Polygons Spatial Query Framework for Location-Based Services paper, we have proposed an efficient and privacypreserving polygons spatial query framework for LBSs, named Polaris. Based on an improved efficient homomorphic encryption technology over composite order group, the proposed Efficient and Privacy-preserving Polygons Spatial Query Framework Polaris can achieve query polygons privacy preservation and confidentiality of LBS data. Specifically, for an LBS query request from a registered LU, the LBS query execution is directly performed over ciphertext on CS without decryption, and the result of LBS query can only be decrypted by LU. Thus, LU can get accurate LBS query result without divulging his/her query information. Detailed security analysis shows its security strength and privacy-preserving ability, and extensive experiments are conducted to demonstrate its efficiency. In this system project paper, we present an efficient and privacy-preserving polygons spatial query framework for location-based services, called Polaris.