000			01412nam a2200169 a 4500
005			20260901030328.0
008			250101s2020 xx o 000 0 eng d
100	1		_aMuhammad Imran Khan
245	1	0	_aPrivacy Interpretation of Behavioural-based Anomaly Detection Approaches
264		1	_barXiv _c2020
336			_atext
338			_aonline resource
520			_aThis paper proposes the notion of 'Privacy-Anomaly Detection' and considers the question of whether behavioural-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 such as k-anonymity. The idea is to learn the user's past querying behaviour in terms of privacy and then identifying 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 also considered in the 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
506	0		_aOpen access — freely available to read.
856	4	0	_uhttps://arxiv.org/pdf/2012.11541v1 _yRead the full paper (PDF)
942			_cERES
999			_c639 _d639