Privacy Interpretation of Behaviour-based Anomaly Detection Approaches

This paper introduces the notion of 'Privacy-Anomaly Detection' and considers the question of whether behaviour-based anomaly detection approaches can have a privacy semantic interpretation and whether the detected anomalies can be related to the conventional (formal) definitions of privacy semantics. The idea is to learn user's past querying behaviour in terms of privacy and then identify deviations from past behaviour in order to detect privacy violations. Privacy attacks, violations of formal privacy definition, based on a sequence of SQL queries (query correlations) are considered in this paper and it is shown that interactive querying settings are vulnerable to privacy attacks based on query sequences. Investigation on whether these types of privacy attacks can potentially manifest themselves as anomalies, specifically as privacy-Anomalies was carried out. It is shown, in this paper, that behaviour-based anomaly detection approaches have the potential to detect privacy attacks based on query sequences (violation of formal privacy definition) as privacy-Anomalies.