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Privacy Violation Classification of Snort Ruleset
2010
2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing
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Such information can be useful both for privacy impact assessments and automated tests for detecting privacy violations. ...
It is important to analyse the privacy impact of Intrusion Detection System (IDS) rules, in order to understand and quantify the privacy-invasiveness of network monitoring services. ...
what a privacy violation consists of. ...
doi:10.1109/pdp.2010.87
dblp:conf/pdp/Ulltveit-MoeO10
fatcat:uqcn2l7lvzhbficx3zivi4k7hy
Investigation and Application of Differential Privacy in Bitcoin
2022
IEEE Access
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We show that these mechanisms decrease the fraction of the cases violating differential privacy, therefore they can be used for improving anonymity and privacy in Bitcoin. ...
In this paper, we provide a theoretical examination of differential privacy in Bitcoin. ...
All possible cases for neighbor datasets are evaluated and the violations are detected. The fractions of the cases violating differential privacy are given in Table 15 . ...
doi:10.1109/access.2022.3151784
fatcat:4l2iblpkenbmrar7iey4bjnrwq
Testing the Lipschitz Property over Product Distributions with Applications to Data Privacy
[chapter]
2013
Lecture Notes in Computer Science
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DPTD, a similar notion to generalized differential privacy first proposed by [3] , is a distributional relaxation of the popular notion of differential privacy [14] . ...
In this work, we address the following question: Can we design algorithms which tests if a given algorithm satisfies some specific rigorous notion of privacy (e.g., differential privacy)? ...
We would like to thank Adam Smith for suggesting the name Differential Privacy on Typical Datasets and for various other suggestions and comments. ...
doi:10.1007/978-3-642-36594-2_24
fatcat:33xlvxxsuzapzbo65w322hxssy
Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework
2019
Applied Sciences
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The experiments showed that the framework helped to improve the detection of agent quality violations in a dynamic smart city application. ...
Violations of those properties may occur during execution due to the dynamic of agent behavior, decision-making capabilities, and social activities. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app9235111
fatcat:haqwrh5h2rd3jadassbtnhp3sq
GUEST EDITORIAL: Special Issue on Social Sensing and Privacy Computing in Intelligent Social Systems
2020
IEEE Transactions on Computational Social Systems
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The article entitled "Improving Sentiment Polarity Detection through Target Identification" by Basiril et al. proposed a new method to detect the main target of reviews and aggregate sentiment toward this ...
To address this issue, the article entitled "DNN-DP: Differential Privacy Enabled Deep Neural Network Learning Framework for Sensitive Crowdsourcing Data" by Gu et al. developed a differential privacy-enabled ...
doi:10.1109/tcss.2020.2970304
fatcat:heirossfwbcafnzaz5gnqeaiqe
PRIvacy LEakage Methodology (PRILE) for IDS Rules
[chapter]
2010
IFIP Advances in Information and Communication Technology
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This paper introduces a methodology for evaluating PRIvacy LEakage in signature-based Network Intrusion Detection System (IDS) rules. ...
IDS rules that expose more data than a given percentage of all data sessions are defined as privacy leaking. ...
Introduction One of the largest threats towards on-line security and privacy today is attacks caused by cyber-criminals. ...
doi:10.1007/978-3-642-14282-6_17
fatcat:r46uhs3h35hivjmdis5lralkze
Toward a framework for detecting privacy policy violations in android application code
2016
Proceedings of the 38th International Conference on Software Engineering - ICSE '16
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Our empirical evaluation on 477 top Android apps discovered 341 potential privacy policy violations. ...
We present an implementation of our framework based on a privacy-policy-phrase ontology and a collection of mappings from API methods to policy phrases. ...
Acknowledgement The authors are supported in part by NSF Awards CNS-0964710, CNS-1330596, CCF-1464425, NSA Grant on Science of Security, and DHS grant DHS-14-ST-062-001. ...
doi:10.1145/2884781.2884855
dblp:conf/icse/SlavinWHHKBBN16
fatcat:amncvqee25bm5kp2dhniedugie
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images
[article]
2017
arXiv
pre-print
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Second, we run a user study to understand the privacy preferences of different users w.r.t. such attributes. ...
With an increasing number of users sharing information online, privacy implications entailing such actions are a major concern. ...
Responses for the question are collected on a scale of 1 to 5, where: (1) Privacy is not violated (2) Privacy is slightly violated (3) Privacy is somewhat violated (4) Privacy is violated (5) Privacy is ...
arXiv:1703.10660v2
fatcat:7goroqiu35cghmj2hdfi7jxiqy
Challenges for Log Based Detection of Privacy Violations during Healthcare Emergencies
2017
GLOBECOM 2017 - 2017 IEEE Global Communications Conference
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OpenEMR has event logs which record the details of events on health record accesses but which is not sufficient to detect information privacy violations. ...
. • Log formulation: Difficulties arise in detecting privacy violations when the details recorded in a log file are insufficient. ...
doi:10.1109/glocom.2017.8254433
dblp:conf/globecom/WickramageFSW17
fatcat:l73q6y3q6zgnzlnycokrna7xxe
Testing Lipschitz Property over Product Distribution and its Applications to Statistical Data Privacy
[article]
2012
arXiv
pre-print
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In this work, we present a connection between Lipschitz property testing and a relaxed notion of differential privacy, where we assume that the datasets are being sampled from a domain according to some ...
We also initiate the study of distribution Lipschitz testing. ...
Acknowledgements: We would like to thank Sofya Raskhodnikova and Adam Smith for various suggestions and comments during the course of this project. ...
arXiv:1209.4056v1
fatcat:ot3q6x5lsnee5ibnyaepwrgojy
Security and privacy of collaborative spectrum sensing in cognitive radio networks
2012
IEEE wireless communications
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in the aspects of security and privacy. ...
We also show that the proposed privacy preserving framework can significantly improve the location privacy of secondary users with a minimal effect on the performance of the collaborative sensing. ...
Thus the location privacy of the users can be easily violated. ...
doi:10.1109/mwc.2012.6393525
fatcat:p26havo5sjcklmbnxpc3rhylei
Deterrence approach on the compliance with electronic medical records privacy policy: the moderating role of computer monitoring
2019
BMC Medical Informatics and Decision Making
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Further, we also investigated the moderating effect of computer monitoring on relationships among the antecedents and the level of hospital employees' compliance intention. ...
This study explored the possible antecedents that will motivate hospital employees' compliance with privacy policy related to electronic medical records (EMR) from a deterrence perspective. ...
From an academic standpoint, our study provides one of the few tests of the differential deterrence hypothesis in the realm of EMR privacy protection. ...
doi:10.1186/s12911-019-0957-y
pmid:31801545
pmcid:PMC6894129
fatcat:wfjwp7frgrdwjlke4kou5wuw4a
Redactable Signatures to Control the Maximum Noise for Differential Privacy in the Smart Grid
[chapter]
2014
Lecture Notes in Computer Science
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We propose to use the value obtained by calculating the worst case guarantee of differential privacy as a metric to compare and judge a Smart Grid application's privacy invasiveness. ...
On the other hand we limit the noise's range and keep a verifiable level of integrity of consumption values from the Smart Metering Gateway by using a redactable signature. ...
The contribution of this paper is to provide a differential privacy guarantee in the BSI Smart Metering Setting (see Fig. 4 ) and to control the amount of integrity violations needed to achieve the privacy ...
doi:10.1007/978-3-319-10329-7_6
fatcat:6futu4g4ibem7jgw2laqjmi55u
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach
[article]
2020
arXiv
pre-print
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The method relies on the notion of differential privacy and the use of Lagrangian duality to design neural networks that can accommodate fairness constraints while guaranteeing the privacy of sensitive ...
The paper analyses the tension between accuracy, privacy, and fairness and the experimental evaluation illustrates the benefits of the proposed model on several prediction tasks. ...
differential privacy. ...
arXiv:2009.12562v1
fatcat:objnqxrywves5pgqxbfk25fgci
Assessing Dimensions of the Security-Liberty Trade-off in the United States
2020
Surveillance & Society
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Finally, because general attitudes towards surveillance and privacy often fail to have practical implications, we assess whether these attitudes matter for understanding the structure of policy support ...
Next, we evaluate the source of these attitudes with a focus on whether attitudes toward surveillance policies merely relate to core political values or whether they also depend on the messages from political ...
Finally, to capture an individual's personal sensitivity towards privacy violations, we include a measure of past personal privacy violations. ...
doi:10.24908/ss.v18i1.10419
fatcat:pwzrctqa3zaqlouyld66gogmvq
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