SoftFence: An Anonymiser and Active Object based TTP Location Privacy Framework

Abstract

In today’s world most of the applications are based on the location information of users for identifying the

point of interest automatically without the explicit query. Mainly the usages are involving with mobility based devices such as cell phones, PDSA’s, laptops, GPS based devices etc. The device transmits the location information along with the device identity to the location server. Sometimes the application demands more data than it actually needs. There is also a situation where the application uses location information up to certain accuracy. If more accuracy is passed to those applications than there is a chance of security compromises related to confidentiality, integrity and availability. Thus, there must privacy based information handling before passing the values to location server. During the last few years there are various architectural based solutions suggested for serving more privacy in least cost. But after studying the various articles regarding to that techniques, it is found that there are some issues which remains unsolved. Existing privacy algorithm will apply more complex query processing with no control over the accuracy and providers authenticity. Also, the query must hide the user’s identity and control the application data requirements. Most of the previous algorithms are based on k-anonymisers and proximity with a defined architecture. There a various direction where the improvements can be applied. This paper introduces a novel SoftFence framework for improving the privacy of location based services. The approach uses the phenomenons of k-Anonymisers, cloaking and active objects for achieving its goals. The system reduces the query processing load with restricted content usability limits and accuracy for each application. More controlling can be served using the active object transfusions. Overall process involves blocking of additional and leveled information belongs to the user’s identity and location from malicious activities. This work also analyses the security and privacy provisions along with performance measurement of proposed SoftFence approach. At the analytical level of evaluation, it  seems to reduces the overhead and improve the privacy protections in a robust way.