User Privacy Conservation Over Cloud To Eradicate Shortcoming Occurrrence

Abstract

Internet is the place where tons of online user behavior data are generated every day. These data are used to extract users’ valuable information for research purposes or business interests. But, the data are under the risk of being exposed to third parties. Using the data the deceiving advertisements are added with low cost on the same products searched. Here some methods are implemented to perform the data aggregation in a privacy preserving manner. Most of the available methods assure strong privacy protection at the cost of very limited aggregation such as only summation, which hardly satisfies the need of behavior analysis. I propose a model called Privacy Preserving Selective Aggregation (PPSA). This model encrypts the users’ sensitive data to prevent privacy from both outside analysts and the aggregation service provider. Also, completely supports selective aggregate functions for online user behavior analysis and guaranteeing differential privacy. ECC (Elliptical Curve Cryptography) algorithm is used for encrypting users’ online behavior data. Implementation is done and its performances are evaluated based on a real time behavior set.