Increasing user´s privacy control through flexible Web bug detection

People usually provide personal information when visiting Web sites, even though they are not aware of this fact. In some cases, the collected data is misused, resulting on user privacy violation. The existing tools which aim at guaranteeing user privacy usually restrict access to personalized services. In this work, we propose the Web bug detector. Upon detecting and informing users about browsing tracking mechanisms which invisibly collect their personal information when visiting sites, it represents an alternative that provides a better control over privacy while allowing personalization. Through experimental results, we demonstrate the applicability of our strategy by applying the detector to a real workload. We found that about 5.37% of user´s requests were being tracked by third-party sites.