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k-Metric Antidimension: a Privacy Measure for Social Graphs
[article]
2015
arXiv
pre-print
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In this article, we introduce a novel privacy measure, named (k, ℓ)-anonymity and based on the k-metric antidimension problem, aimed at evaluating the resistance of social graphs to active attacks. ...
We, therefore, propose a true-biased algorithm for computing the k-metric antidimension of random graphs. ...
It also introduces the k-metric antidimension as the basis for the privacy measure (k, )-anonymity. ...
arXiv:1408.2154v2
fatcat:5tlnqmeh5ncy7agx4d4xhxa25u
k -Metric antidimension: A privacy measure for social graphs
2016
Information Sciences
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In this article, we introduce (k, )-anonymity; a novel privacy measure aimed at evaluating the resistance of social graphs to active attacks. ...
(k, )-anonymity is based on a new problem in Graph Theory, the k-metric antidimension defined as follows. ...
It also introduces the k-metric antidimension as the basis for the privacy measure (k, )-anonymity. ...
doi:10.1016/j.ins.2015.08.048
fatcat:sxt7ebz5lfdchj75dog5sjiumy
K-metric antidimension of some generalized Petersen graphs
2019
Filomat
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Recently introduced k-metric antidimension graph invariant is used to define a new measure for resistance of social graphs. ...
In this paper we have found and proved the k-metric antidimension for generalized Petersen graphs GP(n, 1) and GP(n, 2). ...
For some graphs with special structures it would be interesting to investigate the privacy measure based on the k-metric antidimension. ...
doi:10.2298/fil1913085k
fatcat:5c6jtclbjbddbagw4sub24f5au
k , l -Anonymity in Wheel-Related Social Graphs Measured on the Base of k -Metric Antidimension
2021
Journal of Mathematics
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By determining their k -metric antidimension, we prove that each social graph of these families is the maximum degree metric antidimensional, where the degree of a vertex is the number of vertices linked ...
In this regard, a novel privacy measure, called the k , l -anonymity, is used since the last few years on the base of k -metric antidimension of G in which l is the maximum number of attacker nodes defining ...
Trujillo-Rasua and Yero defined, studied in detail, and promoted the idea of k-metric antidimension, which provides a basis for the privacy measure (k, l)-anonymity [7] . ey defined this privacy measure ...
doi:10.1155/2021/8038253
fatcat:xphufcovfvakjgrlvrsxdh3ag4
A Review of Several Privacy Violation Measures for Large Networks under Active Attacks
[chapter]
2020
Ethics, Laws, and Policies for Privacy, Security, and Liability [Working Title]
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measure for social networks. ...
However, since such anonymization processes may not always succeed, an important research goal is to quantify and measure how much privacy a given social network can achieve. ...
Yero for useful discussions. This research was partially supported by NSF grants IIS-1160995 and IIS-1814931. ...
doi:10.5772/intechopen.90909
fatcat:is77dhuxvbbn7msphcajwlgxdy
Counteracting Active Attacks in Social Network Graphs
[chapter]
2016
Lecture Notes in Computer Science
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Active attackers can affect the structure of the social network graphs actively and use structural information, as a passive attacker does, to re-identify a user in a social graph. ...
Consequently, social graphs, which express the relations between the actors in a social network, ought to be sanitized or anonymized before being published. ...
Related work Most privacy notions for social graphs are based on k-anonymity [9] , which was originally proposed as a privacy measure for microdata. ...
doi:10.1007/978-3-319-41483-6_17
fatcat:3aepovfzkjdexoobb5s3s5zhcu
Anonymising social graphs in the presence of active attackers
2018
Transactions on Data Privacy
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To that end, we introduce a class of perturbation methods based on edge additions that transform a (1, 1)-anonymous graph into a graph satisfying (k, )-anonymity for some k > 1 or some > 1. ...
This article addresses the challenge of publishing social graphs with proven privacy guarantees. ...
Ergo, the 1-metric antidimension of this graph is 1. ...
dblp:journals/tdp/MauwRT18
fatcat:4xif4e2pxfdazd4lysrwsdfsqi
Rethinking (k,ℓ)-anonymity in social graphs: (k,ℓ)-adjacency anonymity and (k,ℓ)-(adjacency) anonymous transformations
[article]
2017
arXiv
pre-print
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The new privacy property is in turn the basis for a new type of graph perturbation: (k,ℓ)-adjacency anonymous transformations. ...
This paper treats the privacy-preserving publication of social graphs in the presence of active adversaries, that is, adversaries with the ability to introduce sybil nodes in the graph prior to publication ...
The notion of (k, ℓ)-anonymity was introduced in [11] as a measure of the resistance of a social graph to active attacks. ...
arXiv:1704.07078v1
fatcat:ydvxxxr44vfi7fg2u3bg3ymgke
On analyzing and evaluating privacy measures for social networks under active attack
2018
Information Sciences
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Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2018 pre-print arXiv:1809.05926v1 fatcat:3twkkfbl5fcbbnngl6bndxa2b4
Widespread usage of complex interconnected social networks such as Facebook, Twitter and LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks ...
Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network if its topology does not contain a cycle. ...
Acknowledgements We thank the anonymous reviewers for their helpful comments. B.D. and N.M. thankfully acknowledges partially support from NSF grant IIS-1160995. ...
doi:10.1016/j.ins.2018.09.023
fatcat:i7uvkffuevb5pkvhn2l5myehdu
On the Computational Complexities of Three Privacy Measures for Large Networks Under Active Attack
[article]
2016
arXiv
pre-print
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In this paper, we formalize three such privacy measures for large networks and provide non-trivial theoretical computational complexity results for computing these measures. ...
such a network by analyzing the network and deliberately using such privacy violations for deleterious purposes. ...
This privacy measure relies on a graph parameter called the k-metric anti-dimension. ...
arXiv:1607.01438v1
fatcat:k7ah6zwls5e2hfiwsnjlpqt3we
Conditional adjacency anonymity in social graphs under active attacks
2018
Knowledge and Information Systems
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In doing so, social graphs need to be anonymised to resist various privacy attacks. ...
We achieve this goal by introducing (k, G, )-adjacency anonymity: a privacy property based on (k, )-anonymity that alleviates the computational burden suffered by anonymisation algorithms based on (k, ...
[4] , who showed that the k-metric antidimension problem used in (k, )anonymity is NP-Hard. ...
doi:10.1007/s10115-018-1283-x
fatcat:6f5mdiscsvbljcgzjg4fizneoq
Two Novel Network Measures and Their Applications with a Case Study on ADHD for Human Brain Networks
2021
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results and tools can be used for practical applications in both biological and social networks. ...
In this thesis, I would be describing my work on the use of two novel network measures that use graph theoretic and computational tools to analyze heterogeneous complex networks and show how these algorithmic ...
This leads us to our third problem: Problem 3 (k = -metric antidimension or Adim =k ). ...
doi:10.25417/uic.15261984
fatcat:ds64oaguqrexxl6cmgjxr6qxnm