Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
SPIN: mining maximal frequent subgraphs from graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGKDD Explorations Newsletter
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Measuring and extracting proximity in networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Center-piece subgraphs: problem definition and fast solutions
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Proceedings of the 16th international conference on World Wide Web
Towards identity anonymization on graphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
The structure of information pathways in a social communication network
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Resisting structural re-identification in anonymized social networks
Proceedings of the VLDB Endowment
Anonymizing bipartite graph data using safe groupings
Proceedings of the VLDB Endowment
Preserving Privacy in Social Networks Against Neighborhood Attacks
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Context-Aware Object Connection Discovery in Large Graphs
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Topic and role discovery in social networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
k-automorphism: a general framework for privacy preserving network publication
Proceedings of the VLDB Endowment
Preserving the privacy of sensitive relationships in graph data
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
Finding maximal cliques in massive networks by H*-graph
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Anonymizing Set-Valued Social Data
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Neighborhood-privacy protected shortest distance computing in cloud
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Privacy-aware data management in information networks
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Anonymizing shortest paths on social network graphs
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Node protection in weighted social networks
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
An edge-based framework for fast subgraph matching in a large graph
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Privacy-preserving social network publication against friendship attacks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A generalization based approach for anonymizing weighted social network graphs
WAIM'11 Proceedings of the 12th international conference on Web-age information management
LORA: link obfuscation by randomization in graphs
SDM'11 Proceedings of the 8th VLDB international conference on Secure data management
On the privacy and utility of anonymized social networks
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Limiting link disclosure in social network analysis through subgraph-wise perturbation
Proceedings of the 15th International Conference on Extending Database Technology
Protecting sensitive relationships against inference attacks in social networks
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Semi-Edge anonymity: graph publication when the protection algorithm is available
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
EWNI: efficient anonymization of vulnerable individuals in social networks
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Privacy preserving social network publication on bipartite graphs
WISTP'12 Proceedings of the 6th IFIP WG 11.2 international conference on Information Security Theory and Practice: security, privacy and trust in computing systems and ambient intelligent ecosystems
Sensitive label privacy protection on social network data
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Delineating social network data anonymization via random edge perturbation
Proceedings of the 21st ACM international conference on Information and knowledge management
Discretionary social network data revelation with a user-centric utility guarantee
Proceedings of the 21st ACM international conference on Information and knowledge management
STK-anonymity: k-anonymity of social networks containing both structural and textual information
Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks
Privacy preserving release of blogosphere data in the presence of search engines
Information Processing and Management: an International Journal
Preserving privacy and frequent sharing patterns for social network data publishing
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Outsourcing shortest distance computing with privacy protection
The VLDB Journal — The International Journal on Very Large Data Bases
Efficiently anonymizing social networks with reachability preservation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Graph publication when the protection algorithm is available
Data & Knowledge Engineering
K-anonymous path privacy on social graphs
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
| Hi-index | 0.00 |
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due to the diversity and complexity of graph data, on which an adversary can use many types of background knowledge to conduct an attack. One popular type of attacks as studied by pioneer work [2] is the use of embedding subgraphs. We follow this line of work and identify two realistic targets of attacks, namely, NodeInfo and LinkInfo. Our investigations show that k-isomorphism, or anonymization by forming k pairwise isomorphic subgraphs, is both sufficient and necessary for the protection. The problem is shown to be NP-hard. We devise a number of techniques to enhance the anonymization efficiency while retaining the data utility. A compound vertex ID mechanism is also introduced for privacy preservation over multiple data releases. The satisfactory performance on a number of real datasets, including HEP-Th, EUemail and LiveJournal, illustrates that the high symmetry of social networks is very helpful in mitigating the difficulty of the problem.