Today`s location based provisions relies on customer`s mobile device to find the present area. This licenses malignant customers to enter a continued holding or outfit fake guards by undermining their areas. To address this issue, we propose Wi-Fi Based Location Proof Updating System (WBLPUS) in which colocated mobile phones usually make location verification and send data to the location confirmation server. This schema screens the location of the customer and guarantees the assurance reliant upon the advancement of the customer in the particular moment. Furthermore similarly recognize that either the particular customer is the customary customer or the assailant by emulating the log records in the Wi-Fi framework. The source area is ensured subordinate upon the weighed customer in the particular location. Extensive experimental results demonstrate that WBLPUS can enough give location proofs, on a very basic level defend the source location security, and effectively perceive the plotting assaults.

Location Based Services, Colluding Attacks, RSSI (Received Signal Strength Indicator), Wi-Fi, Location Privacy

[1] A.R. Beresford and F. Stajano, �Location Privacy in Pervasive Computing,� IEEE Security and Privacy, 2003.
[2] S. Brands and D. Chaum, �Distance-Bounding Protocols,� Proc. Workshop Theory and Application of Cryptographic Techniques on Advances in Cryptology (EUROCRYPT �93), 1994.
[3] L. Buttya�n, T. Holczer, and I. Vajda, �On the Effectiveness of Changing Pseudonyms to Provide Location Privacy in VANETs,� Proc. Fourth European Conf. Security and Privacy in Ad-Hoc and Sensor Networks, 2007.
[4] S. Capkun and J.-P. Hubaux, �Secure Positioning of Wireless Devices with Application to Sensor Networks,� Proc. IEEE INFOCOM, 2005.
[5] L.P. Cox, A. Dalton, and V. Marupadi, �SmokeScreen: Flexible Privacy Controls for Presence-Sharing,� Proc. ACM MobiSys, 2007.
[6] E.D. Demaine, D. Emanuel, A. Fiat, and N. Immorlica, �Correlation Clustering in General Weighted Graphs,� Theoretical Computer Science, vol. 361, nos. 2/3, pp. 172-187, 2006.
[7] N. Eagle and A. Pentland, �CRAWDAD Data Set mit/reality (v.2005-07-01),�http://crawdad.cs.dartmouth.edu/mit/reality, July 2005.
[8] J. Freudiger, M.H. Manshaei, J.P. Hubaux, and D.C. Parkes, �On Non-Cooperative Location Privacy: A Game-Theoretic Analysis,� Proc. 16th ACM Conf. Computer and Comm. Security (CCS), 2009.
[9] B. Gedik and L. Liu, �A Customizable K-Anonymity Model for Protecting Location Privacy,� Proc. IEEE Int�l Conf. Distributed Computing Systems (ICDCS), 2005.
[10] M. Gruteser and D. Grunwald, �Anonymous Usage of Location- Based Services through Spatial and Temporal Cloaking,� Proc. ACM MobiSys, 2003.
[11] Guohong Cao, and Zhichao Zhu, �Toward Privacy Preserving and Collusion Resistance in a Location Proof Updating System�, IEEE Transactions on Mobile Computing, 2013, Vol 12, no.1, pp.51-64.
[12] R. Herring, J. Ban B. Hoh , M. Gruteser, D. Work, J.C. Herrera, A.M. Bayen, M. Annavaram, and Q. Jacobson, �Virtual Trip Lines for Distributed Privacy-Preserving Traffic Monitoring,� Proc. ACM MobiSys, 2008.
[13] Jiang T, H.J. Wang, and Y.C. Hu, �Location Privacy in Wireless Networks,� Proc. ACM MobiSys, 2007.
[14] Lenders, E. Koukoumidis, P. Zhang, and M. Martonosi, �Location-Based Trust for Mobile User-Generated Content: Applications Challenges and Implementations,� Proc. Ninth Workshop Mobile Computing Systems and Applications, 2008.
[15] Y. Li and J. Ren, �Source-Location Privacy Through Dynamic Routing in Wireless Sensor Networks,� Proc. IEEE INFOCOM, 2010.
[16] W. Luo and U. Hengartner,� Providing Your Location Without Giving Up Your Privacy,� Proc. ACM 11th Workshop Mobile Computing Systems and Applications (HotMobile �10), 2010.
[17] J. Manweiler, R. Scudellari, Z. Cancio, and L.P. Cox, �We Saw Each Other on the Subway: Secure Anonymous Proximity-Based Missed Connections,� Proc. ACM 10th Workshop Mobile Computing Systems and Applications (HotMobile �09), 2009.
[18] J. Manweiler, R. Scudellari, and L.P. Cox, �SMILE: Encounter- Based Trust for Mobile Social Services,� Proc. ACM Conf. Computer and Comm. Security (CCS), 2009.
[19] S.Saroiu and A. Wolman, �Enabling New Mobile Applications with Location Proofs,� Proc.ACM 10th Workshop Mobile Computing Systems and Applications (HotMobile �09), 2009.
[20] M. Shao, Y. Yang, S. Zhu, and G. Cao, �Towards Statistically Strong Source Anonymity for Sensor Networks,� Proc. IEEE INFOCOM, 2008.
[21] Shih-Hau Fang, Chung-Chih Chung, and Chiapin Wang,�Attack-Resistant Wireless Localization Using an Inclusive Disjunction Model�. IEEE Transactions on Communications, 2012, vol.60, no.5, pp.1209-1218.
[22] T. Xu and Y. Cai, �Feeling-Based Location Privacy Protection for Location-Based Services,� Proc. 16th ACM Conf. Computer Comm.Security (CCS), 2009.
[23] Y. Yang, M. Shao, S. Zhu, B. Urgaonkar, and G. Cao, �Towards Event Source Unobservability with Minimum Network Traffic in Sensor Networks,� Proc. First ACM Conf. Wireless Network Security (WiSec), 2008.
[24] Y. Zhang, W. Liu, and W. Lou, �Anonymous Communications in Mobile Ad Hoc Networks,� Proc. IEEE INFOCOM, 2005.
[25] Z. Zhu, G. Cao, S. Zhu, S. Ranjan, and A. Nucci,� A Social Network Based Patching Sheme for WORM Containment in cellular Networks�, Proc. IEEE INFOCOM, 2009.