There has been a great concern regarding the privacy of data collected from users with the advancement of data mining techniques. Any data which is collected and stored in the database for any kind of use must be safe and necessary measures should be taken in order to prevent leaking of user data in to the public domain as any private information which is leaked will tamper the reputation of the organization that was not able to successfully prevent compromising of the privacy of a user. It is relatively easy for any organization to infer patterns and trends of user in order to find their target audience and based on their privacy analysis try to sell them products in order to increase their profits. Although, this can be done on a wider group, but being able to track down an individual’s activity violates his/her privacy. As a part of sensibility testbed project, data is collected from Android Sensors using the sensibility testbed framework. The main purpose of the overall project is to collect data and evaluate them on the collaborative sensors platform. Any sensor data obtained can have private information about a user such as user id, his location coordinates etc. These data will be stored in data brokers for providing users with responses to various requests. Care needs to be taken in order to protect the privacy of users whose data has been collected. A very common approach in order to solve this problem is to use k-anonymity. This project will include studying of various k-anonymity techniques and find a tool that can be used on the sensor dataset and anonymize data before publishing them or storing in data brokers in order to protect the privacy of users. However, the main challenge which will be focused on is to not dilute the information by losing most of it in the process of anonymization and reduce the utility of a dataset by anonymizing it and making the dataset completely useless.