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Privacy-Preserving Subgraph Discovery [chapter]

Danish Mehmood, Basit Shafiq, Jaideep Vaidya, Yuan Hong, Nabil Adam, Vijayalakshmi Atluri
2012 Lecture Notes in Computer Science  
In this paper, we address the problem of privacy-preserving subgraph discovery.  ...  We propose a flexible approach that can utilize any underlying frequent subgraph discovery algorithm and uses cryptographic primitives to preserve privacy.  ...  The general model of privacy preserving subgraph is as follows. The coordinator initiates a request for subgraph discovery.  ... 
doi:10.1007/978-3-642-31540-4_13 fatcat:l7ut55rukret7gfyebghuocr2u

Efficient Privacy-Preserving Link Discovery [chapter]

Xiaoyun He, Jaideep Vaidya, Basit Shafiq, Nabil Adam, Evimaria Terzi, Tyrone Grandison
2009 Lecture Notes in Computer Science  
It is known that link discovery can be done in a privacy-preserving manner by securely finding the transitive closure of a graph.  ...  Given the sensitive nature of information that can be revealed from link discovery, privacy is a major concern from the perspective of both individuals and organizations.  ...  [2] have proposed an approach for privacy-preserving link discovery in a complex and distributed network structure.  ... 
doi:10.1007/978-3-642-01307-2_5 fatcat:cigvna43jnbapaq655d2x75hwm

AI and Security Informatics

Hsinchun Chen
2010 IEEE Intelligent Systems  
keys to winning this international security war. 1 It is widely believed that information technology will play an indispensable role in making the world safer 2 by supporting intelligence and knowledge discovery  ...  They introduce the subgraph generalization approach for social network integration and demonstrate its feasibility for integrating social networks and preserving privacy.  ...  Privacy-preserving third-party data publication and privacy-preserving information integrations are also fruitful areas of research in security informatics.  ... 
doi:10.1109/mis.2010.116 fatcat:75x42d7bbbac7b4yj3qtowd744

Privacy-Preserving Data Analysis on Graphs and Social Networks [chapter]

Kun Liu, Kamalika Das, Tyrone Grandison, Hillol Kargupta
2008 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
Game-Theoretic Framework for Privacy-Preserving Computation Preliminaries of Game Theory Before describing the game-theoretic framework for privacy-preserving distributed computing, we first provide  ...  How well should we preserve those measures? • It is even difficult to devise graph-modification algorithms that balance the goals of preserving privacy with the utility of the data.  ... 
doi:10.1201/9781420085877.ch21 fatcat:kkdozdvg2zf63lcffvjc3l2k6m

A brief survey on anonymization techniques for privacy preserving publishing of social network data

Bin Zhou, Jian Pei, WoShun Luk
2008 SIGKDD Explorations  
. * The research was supported in part by an NSERC Discovery grant and an NSERC Discovery Accelerator Supplements grant.  ...  Although privacy preservation in social network data is a relatively new problem, several privacy preserving methods have been developed.  ... 
doi:10.1145/1540276.1540279 fatcat:rep53vw2hvb4ndombxfwr6r2qu

Private Graph Data Release: A Survey [article]

Yang Li, Michael Purcell, Thierry Rakotoarivelo, David Smith, Thilina Ranbaduge, Kee Siong Ng
2022 arXiv   pre-print
in real-world graph data that was supposed to preserve sensitive information.  ...  of the limitations of Differential Privacy.  ...  Subgraph Discovery An earlier work [71] provides a different privacy model over social network data to identify a targeted group of individuals in a graph.  ... 
arXiv:2107.04245v2 fatcat:54bvnswpnbfffiqd5ee5opfope

Limiting link disclosure in social network analysis through subgraph-wise perturbation

Amin Milani Fard, Ke Wang, Philip S. Yu
2012 Proceedings of the 15th International Conference on Extending Database Technology - EDBT '12  
We study the trade-off of utility and privacy of subgraph-wise perturbation.  ...  Link disclosure between two individuals in a social network could be a privacy breach.  ...  The work of Ke Wang was supported by Canada NSERC Discovery Grant, and the work of Philip S. Yu was supported by US NSF through grants CNS-1115234, and IIS-0914934, and Google Mobile 2014 Program.  ... 
doi:10.1145/2247596.2247610 dblp:conf/edbt/FardWY12 fatcat:yxxasf2n3bdyvjblqxuqiyjipu

Neighborhood randomization for link privacy in social network analysis

Amin Milani Fard, Ke Wang
2013 World wide web (Bussum)  
A standard technique for achieving link privacy is to probabilistically randomize a link over the space for node pairs.  ...  The trade-off between privacy and utility is dictated by the retention probability of a destination and by the size of the randomization neighborhood.  ...  Acknowledgements Ke Wang's work is partially funded by a Discovery Grant from Natural Sciences and Engineering Research Council of Canada and is partially done when Ke Wang visited SA Center for Big Data  ... 
doi:10.1007/s11280-013-0240-6 fatcat:yqkq22xdfjbihj3i5oz66krblm

Preserving Location Privacy in Mobile Edge Computing [article]

Hongli Zhang, Yuhang Wang, Xiaojiang Du, Mohsen Guizani
2018 arXiv   pre-print
To address the location privacy in MEC environment, we designed LoPEC, a novel and effective scheme for protecting location privacy for the MEC devices.  ...  Although this transplant will avoid the location privacy threat from the central cloud provider, there still exists the privacy concerns in the LS of MEC scenario.  ...  To overcome this problem, we propose a faster Complete Subgraph Discovery Algorithm (CSDA). CSDA is based on the notion of clustering coefficients.  ... 
arXiv:1804.01636v1 fatcat:df6fntyzqfhtvif5elbncrmdce

Federated Graph Learning – A Position Paper [article]

Huanding Zhang, Tao Shen, Fei Wu, Mingyang Yin, Hongxia Yang, Chao Wu
2021 arXiv   pre-print
However, in some privacy sensitive scenarios (like finance, healthcare), training a GNN model centrally faces challenges due to the distributed data silos.  ...  [Wu et al., 2021] designs a federated GNN framework for privacy preserving recommendation.  ...  The main purpose of vertical intra-graph FL is to learn more comprehensive GNN by combining {X v |v ∈ V } in a privacy preserved and communication efficient manner.  ... 
arXiv:2105.11099v1 fatcat:6bhzsfiwwvgndizffwokpuiaym

Anonymization in Social Ne tworks: A Survey on the issues of Data Privacy in Social Network Sites

A. Praveena, Dr.S. Smys
2016 International Journal Of Engineering And Computer Science  
This leads for privacy-preserving social network data mining, which is the discovery of information and relationships from social network data without violating privacy.  ...  the existing anonymization techniques for privacy preserving publishing of social net-work data.  ...  [24] used K-isomorphism to preserve privacy when adversary has subgraph knowledge. Wu et al.  ... 
doi:10.18535/ijecs/v5i3.07 fatcat:oashkvfh6rgvrpfso2knjeb23e

Privacy-Preserving Query over Encrypted Graph-Structured Data in Cloud Computing

Ning Cao, Zhenyu Yang, Cong Wang, Kui Ren, Wenjing Lou
2011 2011 31st International Conference on Distributed Computing Systems  
In this paper, for the first time, we define and solve the problem of privacy-preserving query over encrypted graph-structured data in cloud computing (PPGQ), and establish a set of strict privacy requirements  ...  To meet the challenge of supporting graph query without privacy breaches, we propose a secure inner product computation technique, and then improve it to achieve various privacy requirements under the  ...  Our proposed privacy-preserving graph query scheme is designed as follows with details in Fig. 5 . • FSCon( , ) The data owner utilizes existing frequent subgraph mining algorithms to generate the frequent  ... 
doi:10.1109/icdcs.2011.84 dblp:conf/icdcs/CaoYWRL11 fatcat:yurhw427wrc5rgi6l2bz3fgj24

Influential Incremental Learning-Based Privacy Preservation for Social Network Information

Jalawi Sulaiman Alshudukhi, Bharat Bhushan
2022 Security and Communication Networks  
Aiming at the enumeration problem of seed set selection, an incremental strategy that supports privacy protection is proposed to construct seed sets to reduce time overhead; a local influence subgraph  ...  Its effect helps to reconcile the conflict between privacy protection and information distribution.  ...  protection constraints To deal with the three difficulties of the influence maximization problem under the constraints of privacy protection, this section proposes a privacy-preserving influence maximization  ... 
doi:10.1155/2022/8150325 fatcat:tba7vwjbajb57hs2tje6nw3npq

Privacy Disclosure and Preservation in Learning with Multi-Relational Databases

Hongyu Guo, Herna L. Viktor, Eric Paquet
2011 Journal of Computing Science and Engineering  
One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage.  ...  This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected.  ...  ACKNOWLEDGMENTS This paper extends our earlier work, as reported in the 2nd IEEE International Workshop on Privacy Aspects of Data Mining (PADM2010) (Guo et al. [42] ).  ... 
doi:10.5626/jcse.2011.5.3.183 fatcat:k5q2rpcvbred5nyxkdvqe6ugbq

Mining Frequent Graph Patterns with Differential Privacy [article]

Entong Shen, Ting Yu
2013 arXiv   pre-print
Differential privacy has recently emerged as the de facto standard for private data analysis due to its provable privacy guarantee.  ...  We first show that previous techniques on differentially private discovery of frequent itemsets cannot apply in mining frequent graph patterns due to the inherent complexity of handling structural information  ...  An efficient algorithm for counting the neighbors of a pattern has been proposed to greatly reduce the time-consuming subgraph isomorphism tests.  ... 
arXiv:1301.7015v2 fatcat:jgpzyhgmvfferkrdncblukiabi
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