@inbook{0602fc35e01540ffaf19ad1278997c54,
title = "Computing the identification capability of SQL queries for privacy comparison",
abstract = "Comparing SQL queries is an interesting area of research, with applications of query similarity in different domains; for instance, anomaly-based intrusion detection systems. Comparing two SQL queries in terms of privacy-privacy comparison as well as computing a quantitative value for the identification capability of an SQL query is desirable. In this paper, we compute the identification capability of an SQL query and subsequently we propose an approach to compare two SQL queries in terms of privacy by introducing the notion of privacy equivalence, less-private and more-private relations. Additionally, an edge-labelled directed acyclic graph style privacyaware attribute relationship diagram is proposed that facilitates the privacy comparison.",
keywords = "Database monitoring, Electronic privacy, Privacy Audit, RDBMS,Data-Mining",
author = "Khan, \{Muhammad Imran\} and Foley, \{Simon N.\} and Barry O'Sullivan",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 5th ACM International Workshop on Security and Privacy Analytics, IWSPA 2019, co-located with CODASPY 2019 ; Conference date: 27-03-2019",
year = "2019",
month = mar,
day = "13",
doi = "10.1145/3309182.3309188",
language = "English",
series = "IWSPA 2019 - Proceedings of the ACM International Workshop on Security and Privacy Analytics, co-located with CODASPY 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "47--52",
booktitle = "IWSPA 2019 - Proceedings of the ACM International Workshop on Security and Privacy Analytics, co-located with CODASPY 2019",
}