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Privacy and Utility of Inference Control Mechanisms for Social Computing Applications
2016
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security - ASIA CCS '16
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on selected components of the user profile. ...
To the best of our knowledge, ours is the first work to articulate precise privacy and utility goals of inference control mechanisms for third-party applications in social computing platforms. ...
Acknowledgments This work is supported in part by an NSERC Discovery Grant (RGPIN-2014-06611) and a Canada Research Chair (950-229712). ...
doi:10.1145/2897845.2897878
dblp:conf/ccs/AhmadinejadFS16
fatcat:kux6h5qskvc7jegwgz33znzibi
Detection and Amelioration of Social Engineering Vulnerability in Contingency Table Data using an Orthogonalised Log-linear Analysis
[article]
2023
arXiv
pre-print
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In a dialog based attack, by having enough of a potential victim's personal data to be convincing, a social engineer impersonates the victim in order to manipulate the attack's target into revealing sufficient ...
We use an orthogonalised log linear analysis of data in the form of a contingence table to develop a measure of how susceptible particular subtables are to probabilistic inference as the basis for our ...
and detecting network based attacks. ...
arXiv:2302.13532v1
fatcat:seotrckjwzcuxm72m2qnty4eai
Privacy in Social Media: Identification, Mitigation and Applications
[article]
2018
arXiv
pre-print
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The increasing popularity of social media has attracted a huge number of people to participate in numerous activities on a daily basis. This results in tremendous amounts of rich user-generated data. ...
Consequently, various protection techniques have been proposed to anonymize user-generated social media data. There is a vast literature on privacy of users in social media from many perspectives. ...
A user's ego network is a subset of the original social network based on the user's friends and the social relations among them. ...
arXiv:1808.02191v1
fatcat:grcar6kx7nbqlf7o3ygrn4te44
Ontology-based Attack Graph Enrichment
[article]
2022
arXiv
pre-print
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As a result, predicates get periodically updated, based on attack evidences and ontology enrichment. ...
Attack graphs provide a representation of possible actions that adversaries can perpetrate to attack a system. ...
Images and videos of altercations, evacuation, and car fires are posted on social media. At the same time, a denial-of-service cyber-attack against the municipality network is perpetrated. ...
arXiv:2202.04016v1
fatcat:f2u4frckqvgjhesbxqm3vyghe4
Social Network De-Anonymization and Privacy Inference with Knowledge Graph Model
2017
IEEE Transactions on Dependable and Secure Computing
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Our experiment on data of real social networks shows that knowledge graphs can power de-anonymization and inference attacks, and thus increase the risk of privacy disclosure. ...
This suggests the validity of knowledge graphs as a general effective model of attackers' background knowledge for social network attack and privacy preservation. ...
EXPERIMENT EVALUATIONS We conduct de-anonymization and privacy inference experiments on two real world social network datasets and then we present a comprehensive evaluation on our methods, which validates ...
doi:10.1109/tdsc.2017.2697854
fatcat:g7p2dgdvxnb4hky63pv5kc7mlu
Social network topology: a Bayesian approach
2007
Journal of the Operational Research Society
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Here, a method based on Bayesian inference is presented that probabilistically infers the existence of links within a social network. It is tested on data from open source publications. ...
The result of the analysis is a probabilistic network, that is a network that consists of known links (established through direct surveillance) and proposed links (established through probabilistic inference ...
doi:10.1057/palgrave.jors.2602352
fatcat:swxo6dbdovdendanxn5fxs3fbq
Long-range Event-level Prediction and Response Simulation for Urban Crime and Global Terrorism with Granger Networks
[article]
2019
arXiv
pre-print
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Here, we are introducing Granger Network inference as a new forecasting approach for individual infractions with demonstrated performance far surpassing past results, yet transparent enough to validate ...
and extend social theory. ...
Data on terror attacks was downloaded from the GTD (https://www.start.umd.edu/data-tools/global-terrorismdatabase-gtd), which is a database of incidents of terrorism from 1970 -2016. ...
arXiv:1911.05647v1
fatcat:64vjy6jvjzdnbmp5mh6icrjb3a
User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy
[article]
2018
arXiv
pre-print
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in online social networks. ...
Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. ...
As mentioned, each social network follows a different goal compared with other ones. Basically, social network sites can be categorized based on different purposes. ...
arXiv:1806.07629v1
fatcat:fbo7j4wq2jf6xmlqkxw2777sfe
Privacy in trajectory micro-data publishing : a survey
[article]
2020
arXiv
pre-print
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This paper serves as an introductory reading on a critical subject in an era of growing awareness about privacy risks connected to digital services, and provides insights into open problems and future ...
We classify and present the literature of attacks against trajectory micro-data, as well as solutions proposed to date for protecting databases from such attacks. ...
The result is in fact merely probabilistic, as it is not based on actual ground truth (i.e., the identity -as social network username -of users in the trajectory micro-data): instead, a maximum a-posteriori ...
arXiv:1903.12211v3
fatcat:kyz7k56e6bcunkzmsdz7xdx5ri
Advances in Inference Control in Statistical Databases: An Overview
[chapter]
2002
Lecture Notes in Computer Science
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Inference control in statistical databases is a discipline with several other names, such as statistical disclosure control, statistical disclosure limitation, or statistical database protection. ...
Massive production of computerized statistics by government agencies combined with an increasing social importance of individual privacy has led to a renewed interest in this topic. ...
"Extending cell suppression to protect tabular data against several attackers", by Salazar, points out that attackers to confidentiality need not be just external intruders; internal attackers, i.e. special ...
doi:10.1007/3-540-47804-3_1
fatcat:3wfmojfvpvbylb7gsznkb33rry
Privacy in Social Networks
2012
Synthesis Lectures on Data Mining and Knowledge Discovery
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Acknowledgments The authors would like to thank Michael Hay and Ashwin Machanavajjhala for the invaluable and thorough feedback on this manuscript. ...
One type of attack, which we call an attribute inference attack, assumes that an attribute is sensitive only for a subset of the users in the network and that the other users in the network are willing ...
One can see suppression as a special case of generalization, and that suppressing all attributes would guarantee k-anonymity. ...
doi:10.2200/s00408ed1v01y201203dmk004
fatcat:x2zivcq7fjakbkkdayab5nuu2i
Anonymized Data: Generation, models, usage
2010
2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)
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Essentially, anonymized data describes a set of possible worlds, one of which corresponds to the original data. ...
They enable publication of detailed information, which permits ad hoc queries and analyses, while guaranteeing the privacy of sensitive information in the data against a variety of attacks. ...
, which represents sensitive associations between entities (e.g., people in social networks). ...
doi:10.1109/icde.2010.5447721
dblp:conf/icde/CormodeS10
fatcat:q76eqshvongpbnzfsnebgzpmti
Anonymized data
2009
Proceedings of the 35th SIGMOD international conference on Management of data - SIGMOD '09
Preserved Fulltext
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Essentially, anonymized data describes a set of possible worlds, one of which corresponds to the original data. ...
They enable publication of detailed information, which permits ad hoc queries and analyses, while guaranteeing the privacy of sensitive information in the data against a variety of attacks. ...
, which represents sensitive associations between entities (e.g., people in social networks). ...
doi:10.1145/1559845.1559968
dblp:conf/sigmod/CormodeS09
fatcat:zstvbpoah5g5hiqim4fzi7crra
A Simple Model for Sequences of Relational State Descriptions
[chapter]
2008
Lecture Notes in Computer Science
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It is based on CP-logic, an expressive probabilistic logic for modeling causality. ...
Standard probabilistic sequence models provide efficient inference and learning techniques, but typically cannot fully capture the relational complexity. ...
This work was supported by FWO-Vlaanderen, and the GOA/08/008 project "Probabilistic Logic Learning". ...
doi:10.1007/978-3-540-87481-2_33
fatcat:6ymfjy4lfbbvjck5mgnk3ysbxq
Evaluating the impact of k-anonymization on the inference of interaction networks
2016
Transactions on Data Privacy
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Moreover, the nature of academic data is such that many implicit social interaction networks can be derived from available datasets, either anonymized or not, raising the need for researching how anonymity ...
We address the publication of a large academic information dataset while ensuring privacy. ...
Acknowledgements A preliminary version of this work was presented at the ACM CIKM 2014 Workshop on Privacy and Security of Big Data (PSDB). ...
dblp:journals/tdp/RijoFS16
fatcat:z2zgaqgwcjbplcus4lai7gckqu
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