Privacy or Security?: Take A Look And Then Decide

Big data paradigm is currently the leading paradigm for data production and management. As a matter of fact, new information are generated at high rates in specialized fields (e.g., cybersecurity scenario). This may cause that the events to be studied occur at rates that are too fast to be effectively analyzed in real time. For example, in order to detect possible security threats, millions of records in a high-speed flow stream must be screened. To ameliorate this problem, a viable solution is the use of data compression for reducing the amount of data to be analyzed. In this paper we propose the use of privacy-preserving histograms, that provide approximate answers to 'safe' queries, for analyzing data in the cybersecurity scenario without compromising individuals' privacy, and we describe our system that has been used in a real life scenario.