Abstract
Ubiquitous computing blended with context awareness gives user the facility of “anywhere anytime” computing. Location based services represents a class of context aware computing. Involvement of location as the primary input in location based services triggered concerns for user’s privacy. Most of the privacy work in domain of location based services relies on obfuscation strategy along with K anonymity. The proposed work acknowledges the idea of calculating value of K for K anonymity using context factors in fuzzy format. However, with increasing number of these fuzzy context factors resulting in more fuzzy rules, the system will tend to get slower. In order to address this issue, requirement is to reduce the size of rule base without hampering the performance much. Goal of the proposed work is to attain scalability and high performance for the above said system. Towards this, reduction of number of rules in the rule base, of fuzzy inference system has been done using Fuzzy C Means and Genetic Algorithm. Results of reduced rule base have been compared with the results of exhaustive rule base. It has been identified that number of rules can be reduced up to considerable extent with comparable performances and acceptable level of error.
Highlights
The explosive growth of mobile technology and internet development has facilitated users with many context aware services
Work described in [11] proposes a combined anonymizing algorithm based on K-member Fuzzy Clustering and Firefly Algorithm (KFCFA) to protect the anonymized database against identity disclosure, attribute disclosure, link disclosure, and similarity attacks, and significantly minimize the information loss
This work provides the contribution of, evolving the reduced set of rules and optimizing the rule base for scalability and system performance, This reduction is done firstly done through Fuzzy C Means Clustering (FCM) technique and the result obtained are verified through Genetic Algorithm (GA)
Summary
The explosive growth of mobile technology and internet development has facilitated users with many context aware services. K-anonymity is achieved with respect to a specific area which is obtained through spatial cloaking Using this technique, a user’s exact location is blurred into a spatial region in order to preserve the location privacy. Higher location disclosure and lower will be the K value for anonymity. This value of K is based on current spatial temporal context through location disclosure and is valid, and personalized for all users present in that context. The above mentioned system was implemented in the work [2] This system contain fuzzy inference system (FIS) as one of its key components because factors representing context like sensitivity of location, density of location etc.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
