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An Efficient and Robust Social Network De-anonymization Attack [article]

Gábor György Gulyás and Benedek Simon and Sándor Imre
2016 arXiv   pre-print
In this paper we design and evaluate a novel social de-anonymization attack.  ...  In our work, we consider structural social network de-anonymization attacks, which are used when a malicious party uses connections in a public or other identified network to re-identify users in an anonymized  ...  This work was carried out during the tenure of an ERCIM 'Alain Bensoussan' Fellowship Programme.  ... 
arXiv:1610.04064v1 fatcat:aoq7rhv6zjajlcv2wcqz6mvmuy

Membership-concealing overlay networks

Eugene Vasserman, Rob Jansen, James Tyra, Nicholas Hopper, Yongdae Kim
2009 Proceedings of the 16th ACM conference on Computer and communications security - CCS '09  
We then propose three proof-of-concept MCON designs that resist those attacks: one that is more efficient, another that is more robust to membership churn, and a third that balances efficiency and robustness  ...  network.  ...  our anonymous reviewers for their very helpful suggestions.  ... 
doi:10.1145/1653662.1653709 dblp:conf/ccs/VassermanJTHK09 fatcat:3jdrvrwt2jen5bvzmlvhqauvdm

On anonymizing social network graphs

Anne V.D.M. Kayem, Azhar Deshai, Stuart Hammer
2012 2012 Information Security for South Africa  
The proliferation of social networks as a means of seamless communication between multiple parties across vast geographical distances has driven an increased interest from government organizations and  ...  Users typically post information containing personal data during social network interactions with other users because the aim is to share this information only with persons that are authorized to access  ...  As an example of how the embedded subgraph attack works, consider that a user say, Alice is an attacker and that she wishes to de-anonymize three target users (Tom, Dick, and Harry) in a social network  ... 
doi:10.1109/issa.2012.6320456 dblp:conf/issa/KayemDH12 fatcat:qmtx2mrpejaktbwpasrigtwyky

A Practical Attack to De-anonymize Social Network Users

Gilbert Wondracek, Thorsten Holz, Engin Kirda, Christopher Kruegel
2010 2010 IEEE Symposium on Security and Privacy  
Thus, whenever a social network user visits a malicious website, this website can launch our de-anonymization attack and learn the identity of its visitors.  ...  In this paper, we introduce a novel de-anonymization attack that exploits group membership information that is available on social networking sites.  ...  We also thank our shepherd Vitaly Shmatikov and the anonymous reviewers for their valuable insights and comments.  ... 
doi:10.1109/sp.2010.21 dblp:conf/sp/WondracekHKK10 fatcat:b5n6fvpsx5dgxpbvtjlwl5xnzm

Analysis of Grasshopper, a Novel Social Network De-anonymization Algorithm

Benedek Simon, Gábor György Gulyás, Sándor Imre
2014 Periodica Polytechnica Electrical Engineering and Computer Science  
Social networks have an important and possibly key role in our society today.  ...  A strong class of these attacks solely use the network structure to achieve their goals. In this paper we propose a novel structural de-anonymization attack called Grasshopper.  ...  Furthermore, it should be investigated why we observed differences in recall between Epinions and others networks.  ... 
doi:10.3311/ppee.7878 fatcat:f56zkd37rrcu3ibhnxui4jgfb4

Understanding structure-based social network de-anonymization techniques via empirical analysis

Jian Mao, Wenqian Tian, Jingbo Jiang, Zhaoyuan He, Zhihong Zhou, Jianwei Liu
2018 EURASIP Journal on Wireless Communications and Networking  
In this paper, we conduct a comprehensive analysis on the typical structure-based social network de-anonymization algorithms.  ...  However, de-anonymization techniques are actively studied to identify weaknesses in current social network data-publishing mechanisms.  ...  [37] discovered a unified similarity-based de-anonymization attack in both social networks and mobility traces.  ... 
doi:10.1186/s13638-018-1291-2 fatcat:r3h5b4yaonczdjtqljwr3bzzty

De-anonymizing Scale-Free Social Networks by Using Spectrum Partitioning Method

Qi Sun, Jiguo Yu, Honglu Jiang, Yixian Chen, Xiuzhen Cheng
2019 Procedia Computer Science  
In this paper, we transform the problem of de-anonymization into node matching problem in graph, and the de-anonymization method can reduce the number of nodes to be matched at each time.  ...  Even thought the network provider always perturbs the data before publishing it, attackers can still recover anonymous data according to the collected auxiliary information.  ...  Acknowledgment This work is supported by NSF of China under Grants 61373027 and 61672321.  ... 
doi:10.1016/j.procs.2019.01.262 fatcat:nxg4pw7msfgkradntq2rz3ssde

A Frame Work for Preserving Privacy in Social Media using Generalized Gaussian Mixture Model

P Anuradha, Y.Srinivas, MHM Krishna
2015 International Journal of Advanced Computer Science and Applications  
Face book is one such most popular and widely used Social Networking sites which have its own robust set of Privacy mechanisms. Yet they are also prone to various privacy issues and attacks.  ...  Nevertheless Social Networking sites are also vulnerable to various problems, threats and attacks such as disclosure of information, identity thefts etc.  ...  In this paper, we have analyzed the offered privacy methodologies for the social networking sites, and in particular focused on the De-Anonymization attack and propose some new privacy model to strengthen  ... 
doi:10.14569/ijacsa.2015.060711 fatcat:swwkly424zfytozn63pm3nd7jm

An Automated Social Graph De-anonymization Technique [article]

Kumar Sharad, George Danezis
2014 arXiv   pre-print
We present a generic and automated approach to re-identifying nodes in anonymized social networks which enables novel anonymization techniques to be quickly evaluated.  ...  Further, since it detects weaknesses in the black-box anonymization scheme it can re-identify nodes in one social network when trained on another.  ...  Narayanan and Shmatikov present [16] a de-anonymization attack on a social network using auxiliary information from a different social network.  ... 
arXiv:1408.1276v2 fatcat:dcwft434jrfwfjte2wv6mya7k4

The web of federal crimes in Brazil: topology, weaknesses, and control [article]

Bruno Requião da Cunha, Sebastian Gonçalves
2017 arXiv   pre-print
edge density and network efficiency.  ...  This component shows some typical social network characteristics, such as small-worldness and high clustering coefficient, however it is much "darker" than common social networks, having low levels of  ...  Despite that, the authors did not study the Mafia network's modularity and its robustness to Module-Based Attacks(MBA) [20] or other more efficient methods of attack [21] .  ... 
arXiv:1706.03153v1 fatcat:vcg4ebj325htxbk4qswxm5o4ou

Anonymity in the Wild: Mixes on unstructured networks [article]

Shishir Nagaraja
2007 arXiv   pre-print
We consider mix network topologies where mixes are placed on the nodes of an unstructured network, such as social networks and scale-free random networks.  ...  of the most central nodes has little effect on anonymization properties, and third, batch sizes required for warding off intersection attacks need to be an order of magnitude higher in unstructured networks  ...  Acknowledgements The authors are grateful to Ross Anderson for reviews on early versions of the paper, and to George Danezis and Roger Dingledine, for thought provoking discussions.  ... 
arXiv:0706.0430v1 fatcat:cqp7tw7kb5az3c6tzfhs56o7fu

Community-Enhanced De-anonymization of Online Social Networks

Shirin Nilizadeh, Apu Kapadia, Yong-Yeol Ahn
2014 Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security - CCS '14  
However, by using external information such as a reference social graph (from the same network or another network with similar users), researchers have shown how such datasets can be de-anonymized.  ...  Online social network providers have become treasure troves of information for marketers and researchers.  ...  In this paper we leverage 'mesoscopic' 1 properties of social networks for enhanced de-anonymization that is more robust to noise and a low number of seeds, and scales easier with large network size.  ... 
doi:10.1145/2660267.2660324 dblp:conf/ccs/NilizadehKA14 fatcat:2tq6pdhq7fcbbbwazoval2tcru

The Impact of Unlinkability on Adversarial Community Detection: Effects and Countermeasures [chapter]

Shishir Nagaraja
2010 Lecture Notes in Computer Science  
Similar clustering (attack) methods [13, 45, 7, 29] can be applied to human communication in order to de-anonymize the community membership of a social network.  ...  Our analysis shows that even when using anonymous communications an adversary placing a selectively chosen 8% of the nodes of this network under surveillance (using key-logger probes) can de-anonymize  ...  An attacker who has partial or complete knowledge of the social network can cause significant damage to user privacy.  ... 
doi:10.1007/978-3-642-14527-8_15 fatcat:pkyya7qn75eericxn3z7curave

Robust active attacks on social graphs

Sjouke Mauw, Yunior Ramírez-Cruz, Rolando Trujillo-Rasua
2019 Data mining and knowledge discovery  
In order to support this claim, we develop the notion of a robust active attack, which is an active attack that is resilient to small perturbations of the social network graph.  ...  We formulate the design of robust active attacks as an optimisation problem and we give definitions of robustness for different stages of the active attack strategy.  ...  Acknowledgements We thank the anonymous reviewers for their valuable comments and suggestions.  ... 
doi:10.1007/s10618-019-00631-5 fatcat:uiwc5ikddzeozjyhc5jcknggvq

Topology, robustness, and structural controllability of the Brazilian Federal Police criminal intelligence network

Bruno Requião da Cunha, Sebastián Gonçalves
2018 Applied Network Science  
However, it is less dense and less efficient than typical social networks.  ...  We focus on the largest connected cluster of this network and show it has many social network features, such as small-worldness and heavy-tail degree distribution.  ...  It consists of a CSV file with the anonymized edge list relative to the Brazilian Federal Police criminal relationship data, i.e. each cell contains a hash which identifies an investigated person, and  ... 
doi:10.1007/s41109-018-0092-1 pmid:30839817 pmcid:PMC6214327 fatcat:nlzogxuuwvfwfh7zp7vusowtcm
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