Skip to main content

A Generalized Approach for Social Network Integration and Analysis with Privacy Preservation

  • Chapter
Data Mining and Knowledge Discovery for Big Data

Part of the book series: Studies in Big Data ((SBD,volume 1))

Abstract

Social network analysis is very useful in discovering the embedded knowledge in social network structures, which is applicable in many practical domains including homeland security, publish safety, epidemiology, public health, electronic commerce, marketing, and social science. However, social network data is usually distributed and no single organization is able to capture the global social network. For example, a law enforcement unit in Region A has the criminal social network data of her region; similarly, another law enforcement unit in Region B has another criminal social network data of Region B. Unfortunately, due the privacy concerns, these law enforcement units may not be allowed to share the data, and therefore, neither of them can benefit by analyzing the integrated social network that combines the data from the social networks in Region A and Region B. In this chapter, we discuss aspects of sharing the insensitive and generalized information of social networks to support social network analysis while preserving the privacy at the same time. We discuss the generalization approach to construct a generalized social network in which only insensitive and generalized information is shared. We will also discuss the integration of the generalized information and how it can satisfy a prescribed level of privacy leakage tolerance which is measured independently to the privacy-preserving techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adibi, Chalupsky, H., Melz, E., Valente, A.: The KOJAK Group Finder: Connecting the Dots via Intergrated Knowledge-based and Statistical Reasoning. In: Innovative Applications of Artificial Intelligence Conference (2004)

    Google Scholar 

  2. Agrawal, R., Srikant, R., Thomas, D.: Privacy Preserving OLAP. In: ACM SIGMOD 2005 (2005)

    Google Scholar 

  3. Ahmad, M.A., Srivastava, J.: An Ant Colony Optimization Approach to Expert Identification in Social Networks. In: Liu, H., Salerno, J.J., Young, M.J. (eds.) Social Computing, Behavioral Modeling, and Prediction. Springer (2008)

    Google Scholar 

  4. Backstrom, L., Dwork, C., Kleinberg, J.: Wherefore Art Thou R3579X? Anonymized Social Networks, Hidden Patterns, and Structural Steganography. In: WWW 2007, Banff, Alberta, Canada (2007)

    Google Scholar 

  5. Bhatt, R., Chaoji, V., Parekh, R.: Predicting Product Adoption in Large-Scale Social Networks. In: ACM CIKM, Toronto, Ontario (2010)

    Google Scholar 

  6. Bhattacharya, I., Getoor, L.: Iterative Record Linkage for Cleaning and Integration. In: SIGMOD 2004 Workshop on Research Issues on Data Mining and Knowledge Discovery (2004)

    Google Scholar 

  7. Bhattacharya, I., Getoor, L.: Entity Resolution in Graphs. Technical Report 4758, Computer Science Department, University of Maryland (2005)

    Google Scholar 

  8. Blum, A., Dwork, C., McSherry, F., Nissim, K.: Practical Privacy: the Sulq Framework. In: ACM PODS 2005 (2005)

    Google Scholar 

  9. Brickell, J., Shmatikov, V.: Privacy-Preserving Graph Algorithms in the Semi-honest Model. In: Roy, B. (ed.) ASIACRYPT 2005. LNCS, vol. 3788, pp. 236–252. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Chakrabarti, S., Dom, B., Indyk, P.: Enhanced Hypertext Categorization using Hyperlinks. In: ACM SIGMOD 1998 (1998)

    Google Scholar 

  11. Chau, A.Y.K., Yang, C.C.: The Shift towards Multi-Disciplinarily in Information Science. Journal of the American Society for Information Science and Technology (2008)

    Google Scholar 

  12. Chen, H., Yang, C.C.: Intelligence and Security Informatics: Techniques and Applications. Springer (2008)

    Google Scholar 

  13. Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., Slattery, S.: Learning to Construct Knowledge Bases from the World Wide Web. Artificial Intelligence 118, 69–114 (2000)

    Article  MATH  Google Scholar 

  14. Dinur, I., Nissim, K.: Revealing Information While Preserving Privacy. In: ACM PODS 2003 (2003)

    Google Scholar 

  15. Dong, X., Halevy, A., Madhavan, J.: Reference Reconciliation in Complex Information Spaces. In: ACM SIGMOD International Conference on Management of Data (2005)

    Google Scholar 

  16. Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating Noise to Sensitivity in Private Data Analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265–284. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  17. Frantz, T., Carley, K.M.: A Formal Characterization of Cellular Networks. Technical Report CMU-ISRI-05-109, Carnegie Mellon University (2005)

    Google Scholar 

  18. Frikken, K.B., Golle, P.: Private Social Network Analysis: How to Assemble Pieces of a Graphy Privately. In: The 5th ACM Workshop on Privacy in Electronic Society (WPES 2006), Alexandria, VA (2006)

    Google Scholar 

  19. Gao, J., Qiu, H., Jiang, X., Wang, T., Yang, D.: Fast Top-K Simple Shortest Discovery in Graphs. In: ACM CIKM, Toronto, Ontario (2010)

    Google Scholar 

  20. Gartner, T.: Exponential and Geometric Kernels for Graphs. In: NIPS Workshop on Unreal Data: Principles of Modeling Nonvectorial Data (2002)

    Google Scholar 

  21. Gartner, T.: A Survey of Kernels for Structured Data. ACM SIGKDD Explorations 5, 49–58 (2003)

    Article  Google Scholar 

  22. Getoor, L., Diehl, C.P.: Link Mining: A Survey. ACM SIGKDD Explorations 7, 3–12 (2005)

    Article  Google Scholar 

  23. Hay, M., Miklau, G., Jensen, D., Weis, P., Srivastava, S.: Anonymizing Social Networks. Technical Report 07-19, University of Massachusetts, Amherst (2007)

    Google Scholar 

  24. Gubichev, A., Bedathur, S., Seufert, S., Weikum, G.: Fast and Accurate Estimation of Shortest Paths in Large Graphs. In: ACM CIKM, Toronto, Ontario (2010)

    Google Scholar 

  25. Himmel, R., Zucker, S.: On the Foundations of Relaxation Labeling Process. IEEE Transactions on Pattern Analysis and Machine Intelligence, 267–287 (1983)

    Google Scholar 

  26. Huang, J., Sun, H., Han, J., Deng, H., Sun, Y., Liu, Y.: SHRINK: A Structural Clustering Algorithm for Detecting Hierarchical Communities in Networks. In: ACM CIKM, Toronto, Ontario (2010)

    Google Scholar 

  27. Huang, J., Zhuang, Z., Li, J., Giles, C.L.: Collaboration Over Time: Characterizing and Modeling Network Evolution. In: ACM WSDM 2008 Palo Alto, CA (2008)

    Google Scholar 

  28. Jin, X., Zhang, M., Zhang, N., Das, G.: Versatile Publishing for Privacy Preservation. In: ACM KDD, Washington, DC (2010)

    Google Scholar 

  29. Kenthapadi, K., Mishra, N., Nissim, K.: Simulatable Auditing. In: PODS 2005 (2005)

    Google Scholar 

  30. Kerschbaum, F., Schaad, A.: Privacy-Preserving Social Network Analysis for Criminal Investigations. In: Proceedings of the ACM Workshop on Privacy in Electronic Society, Alexandria, VA (2008)

    Google Scholar 

  31. Ketkar, N., Holder, L., Cook, D.: Comparison of Graph-based and Logic-based Multi-relational Data Mining. In: ACM SIGKDD Explorations, vol. 7 (December 2005)

    Google Scholar 

  32. Kleinberg, J.: Authoritative Sources in a Hyperlinked Environment. Journal of the ACM 46, 604–632 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  33. Kubica, J., Moore, A., Schneider, J., Yang, Y.: Stochastic Link and Group Detection. In: National Conference on Artificial Intelligence: American Association for Artificial Intelligence (2002)

    Google Scholar 

  34. Kubica, J., Moore, A., Schneider, J.: Tractable Group Detection on Large Link Data Sets. In: IEEE International Conference on Data Mining (2003)

    Google Scholar 

  35. Kuramochi, M., Karypis, G.: Frequent Subgraph Discover. In: IEEE International Conference on Data Mining (2001)

    Google Scholar 

  36. Lafferty, L., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: International Conference on Machine Learning (2001)

    Google Scholar 

  37. Leroy, V., Cambazoglu, B.B., Bonchi, F.: Cold Start Link Prediction. In: ACM SIGKDD, Washington, DC (2010)

    Google Scholar 

  38. Leung, C.W., Lim, E., Lo, D., Weng, J.: Mining Ineresting Link Formation Rules in Social Networks. In: ACM CIKM, Toronto, Ontario (2010)

    Google Scholar 

  39. Li, N., Li, T.: t-closeness: Privacy Beyond k-anonymity and ldiversity. In: ICDE 2007 (2007)

    Google Scholar 

  40. Liben-Nowell, D., Kleinberg, J.: The Link Prediction Problem for Social Networks. In: International Conference on Information and Knowledge Management, CIKM 2003 (2003)

    Google Scholar 

  41. Lindell, Y., Pinkas, B.: Secure Multiparty Computation for Privacy-Preserving Data Mining. The Journal of Privacy and Confidentiality 1(1), 59–98 (2009)

    Google Scholar 

  42. Liu, K., Terzi, E.: Towards Identity Anonymization on Graphs. In: ACM SIGMOD 2008. ACM Press, Vancouver (2008)

    Google Scholar 

  43. Lu, Q., Getoor, L.: Link-based Classification. In: International Conference on Machine Learning (2003)

    Google Scholar 

  44. Machanavajjhala, A., Gehrke, J., Kifer, D.: L-diversity: Privacy beyond k-anonymity. In: ICDE 2006 (2006)

    Google Scholar 

  45. Merugu, S., Ghosh, J.: A Distributed Learning Framework for Heterogeneous Data Sources. In: ACM KDD 2005, Chicago, Illinois, USA (2005)

    Google Scholar 

  46. Morris, M.: Network Epidemiology: A Handmbook for Survey Design and Data Collection. Oxford University Press, London (2004)

    Book  Google Scholar 

  47. Muralidhar, K., Sarathy, R.: Security of Random Data Perturbation Methods. ACM Transactions on Database Systems 24, 487–493 (1999)

    Article  Google Scholar 

  48. Nabar, S.U., Marthi, B., Kenthapadi, K., Mishra, N., Motwani, R.: Towards Robustness in Query Auditing. In: VLDB, pp. 151-162 (2006)

    Google Scholar 

  49. Nakashima, E.: “Cyber Attack Data-Sharing is Lacking, Congress Told,” the Washington Post, p. D02 (September 19, 2008), http://www.washingtonpost.com/wp-dyn/content/article/2008/09/18/AR2008091803730.html

  50. Nergiz, M.E., Atzori, M., Clifton, C.: Hiding the Presence of Individuals from Shared Database. In: SIGMOD 2007 (2007)

    Google Scholar 

  51. Newman, M.E.J.: Detecting Community Structure in Networks. European Physical Journal B 38, 321–330 (2004)

    Article  Google Scholar 

  52. Oh, H.J., Myeaeng, S.H., Lee, M.H.: A Practical Hypertext Categorization Method using Links and Incrementally Available Class Information. In: International ACM SIGIR Conference on Research and Development in Information Retrieval (2000)

    Google Scholar 

  53. O’Madadhain, J., Hutchins, J., Smyth, P.: Prediction and Ranking Algorithms for Even-based Network Data. ACM SIGKDD Explorations 7 (December 2005)

    Google Scholar 

  54. Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank Citation Ranking: Bringing Order to the Web. Technical Report, Standford University (1998)

    Google Scholar 

  55. Sageman, M.: Understanding Terror Networks. University of Pennsylvania Press (2004)

    Google Scholar 

  56. Sakuma, J., Kobayashi, S.: Link Analysis for Private Weighted Graphs. In: Proceedings of ACM SIGIR 2009, Boston, MA, pp. 235–242 (2009)

    Google Scholar 

  57. Samarati, P.: Protecting Respondents’ Identities in Microdata Release. IEEE Transactions on Knowledge and Data Engineering 13, 1010–1027 (2001)

    Article  Google Scholar 

  58. Srivastava, J., Pathak, N., Mane, S., Ahmad, M.A.: Data Mining for Social Network Analysis. Tutorial Notes in the 2006 IEEE International Conference on Data Mining, Hong Kong, December 18-22 (2006)

    Google Scholar 

  59. Sweeney, L.: Uniqueness of Simple Demographics in the US Population. Technical Report, Carnegie Mellon University (2000)

    Google Scholar 

  60. Sweeney, L.: K-Anonymity: A Model for Protecting Privacy. International Journal of Uncertainty Fuzziness Knowledge-based Systems 10, 557–570 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  61. Tai, C., Yu, P.S., Chen, M.: k-Support Anonymity Based on Pseudo Taxonomy for Outsourcing of Frequent Itemset Mining. In: ACM SIGKDD, Washington, DC (2010)

    Google Scholar 

  62. Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., Su, Z.: ArnetMiner: Extraction and Mining of Academic Social Networks. In: ACM KDD 2008. ACM Press, Las Vegas (2008)

    Google Scholar 

  63. Thuraisingham, B.: Security Issues for Federated Databases Systems. In: Computers and Security. North Holland (1994)

    Google Scholar 

  64. Thuraisingham, B.: Assured Information Sharing: Technologies, Challenges and Directions. In: Chen, H., Yang, C.C. (eds.) Intelligence and Security Informatics: Technqiues and Applications. SCI, vol. 135, pp. 1–15. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  65. Tyler, J.R., Wilkinson, D.M., Huberman, B.A.: Email as Spectroscopy: Automated Discovery of Community Structure within Organizations, The Netherlands (2003)

    Google Scholar 

  66. Vaidya, R.J., Clifton, C.: Privacy-preserving top-k queries. In: International Conference of Data Engineering (2005)

    Google Scholar 

  67. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Google Scholar 

  68. Watts, D.J., Strogatz, S.H.: Collective Dynamics of "Small-wolrd" Networks. Nature 339, 440–442 (1998)

    Article  Google Scholar 

  69. Wolfe, A.P., Jensen, D.: Playing Multiple Roles: Discovering Overlapping Roles in Social Networks. In: ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (2004)

    Google Scholar 

  70. Wong, R.C., Li, J., Fu, A., Wang, K.: (a,k)-Anonymity: An enhanced k-Anonymity Model for Privacy-Preserving Data Publishing. In: SIGKDD, Philadelphia, PA (2006)

    Google Scholar 

  71. Xiao, X., Tao, Y.: Personalized Privacy Preservation. In: SIGMOD, Chicago, Illinois (2006)

    Google Scholar 

  72. Xiao, X., Tao, Y.: m-invariance: Towards Privacy Preserving Republication of Dynamic Datasets. In: ACM SIGMOD 2007. ACM Press (2007)

    Google Scholar 

  73. Xiao, X., Tao, Y.: Dynamic Anonymization: Accurate Statistical Analysis with Privacy Preservation. In: ACM SIGMOD 2008. ACM Press, Vancouver (2008)

    Google Scholar 

  74. Xu, J., Chen, H.: CrimeNet Explorer: A Framework for Criminal Network Knowledge Discovery. ACM Transactions on Information Systems 23, 201–226 (2005)

    Article  Google Scholar 

  75. Yan, X., Han, J.: gSpan: Graph-based Substructure Pattern Mining. In: International Conference on Data Mining (2002)

    Google Scholar 

  76. Yang, C.C., Liu, N., Sageman, M.: Analyzing the Terrorist Social Networks with Visualization Tools. In: IEEE International Conference on Intelligence and Security Informatics, San Diego, CA (2006)

    Google Scholar 

  77. Yang, C.C., Ng, T.D.: Terrorism and Crime Related Weblog Social Network: Link, Content Analysis and Information Visualization. In: IEEE International Conference on Intelligence and Security Informatics, New Brunswick, NJ (2007)

    Google Scholar 

  78. Yang, C.C., Ng, T.D., Wang, J.-H., Wei, C.-P., Chen, H.: Analyzing and Visualizing Gray Web Forum Structure. In: Yang, C.C., et al. (eds.) PAISI 2007. LNCS, vol. 4430, pp. 21–33. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  79. Yang, C.C.: Information Sharing and Privacy Protection of Terrorist or Criminal Social Networks. In: IEEE International Conference on Intelligence and Security Informatics, Taipei, Taiwan, pp. 40–45 (2008)

    Google Scholar 

  80. Yang, C.C., Ng, T.D.: Analyzing Content Development and Visualizing Social Interactions in Web Forum. In: IEEE International Conference on Intelligence and Security Informatics Taipei, Taiwan (2008)

    Google Scholar 

  81. Yang, C.C., Sageman, M.: Analysis of Terrorist Social Networks with Fractal Views. Journal of Information Science (2009)

    Google Scholar 

  82. Yang, C.C., Tang, X.: Social Networks Integration and Privacy Preservation using Subgraph Generalization. In: Proceedings of AMC SIGKDD Workshop on CyberSecurity and Intelligence Informatics, Paris, France (June 28, 2009)

    Google Scholar 

  83. Yang, C.C., Tang, X., Thuraisingham, B.: An Analysis of User Influence Ranking Algorithms on Dark Web Forums. In: Proceedings of ACM SIGKDD Workshop on Intelligence and Security Informatics (ISI-KDD), Washington, D.C. (July 25, 2010)

    Google Scholar 

  84. Yang, C.C., Thuraisingham, B.: Privacy-Preserved Social Network Integration and Analysis for Security Informatics. IEEE Intelligent Systems 25(3), 88–90 (2010)

    Google Scholar 

  85. Yang, X., Asur, S., Parthasarathy, S., Mehta, S.: A Visual-Analytic Toolkit for Dynamic Interaction Graphs. In: ACM KDD 2008, Las Vegas, Nevada (2008)

    Google Scholar 

  86. Yao, A.: Protocols for Secure Computations. In: Proceedings of the Annual IEEE Symposium on Foundations of Computer Science, vol. 23 (1982)

    Google Scholar 

  87. Ying, X., Wu, X.: Randomizing Social Networks: A Spectrum Preserving Approach. In: SIAM International Conference on Data Mining (SDM 2008), Atlanta, GA (2008)

    Google Scholar 

  88. Zheleva, E., Getoor, L.: Preserving the Privacy of Sensitive Relationships in Graph Data. In: Bonchi, F., Malin, B., Saygın, Y. (eds.) PInKDD 2007. LNCS, vol. 4890, pp. 153–171. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  89. Zhou, B., Pei, J.: Preserving Privacy in Social Networks against Neighborhood Attacks. In: IEEE International Conference on Data Engineering (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chris Yang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Yang, C., Thuraisingham, B. (2014). A Generalized Approach for Social Network Integration and Analysis with Privacy Preservation. In: Chu, W. (eds) Data Mining and Knowledge Discovery for Big Data. Studies in Big Data, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40837-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40837-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40836-6

  • Online ISBN: 978-3-642-40837-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics