- Authors:
- Charu C. Aggarwal,
- Philip S. Yu
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions. Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners.
Cited By
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- Alavi A, Gupta R and Qian Z When the Attacker Knows a Lot: The GAGA Graph Anonymizer Information Security, (211-230)
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- Zhang H and Zhu Y (2020). A Method of Sanitizing Privacy-Sensitive Sequence Pattern Networks Mined From Trajectories Released, International Journal of Data Warehousing and Mining, 15:3, (63-89), Online publication date: 1-Jul-2019.
- Zainab S and Kechadi T Sensitive and Private Data Analysis Proceedings of the 3rd International Conference on Future Networks and Distributed Systems, (1-11)
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- Stavropoulos E, Verykios V and Kagklis V (2016). A transversal hypergraph approach for the frequent itemset hiding problem, Knowledge and Information Systems, 47:3, (625-645), Online publication date: 1-Jun-2016.
- Ahmadinejad S, Fong P and Safavi-Naini R Privacy and Utility of Inference Control Mechanisms for Social Computing Applications Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, (829-840)
- Sharma S, Powers J and Chen K Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, (71-82)
- Gómez M, Rouvoy R, Adams B and Seinturier L Reproducing context-sensitive crashes of mobile apps using crowdsourced monitoring Proceedings of the International Conference on Mobile Software Engineering and Systems, (88-99)
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- Yasuda M and Sugimura Y (2015). Biometric key-binding using lattice masking, Security and Communication Networks, 8:18, (3405-3414), Online publication date: 1-Dec-2015.
- Estivill-Castro V and Nettleton D Privacy Tips Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015, (1449-1456)
- Zakerzadeh H, Aggarwal C and Barker K Privacy-preserving big data publishing Proceedings of the 27th International Conference on Scientific and Statistical Database Management, (1-11)
- Dong C Efficient Data Intensive Secure Computation Revised Selected Papers of the 23rd International Workshop on Security Protocols XXIII - Volume 9379, (350-360)
- Honda K, Oda T, Tanaka D and Notsu A (2015). A collaborative framework for privacy preserving fuzzy co-clustering of vertically distributed cooccurrence matrices, Advances in Fuzzy Systems, 2015, (3-3), Online publication date: 1-Jan-2015.
- Iacovazzi A, D'Alconzo A, Ricciato F and Burkhart M (2013). Elementary secure-multiparty computation for massive-scale collaborative network monitoring, Computer Networks: The International Journal of Computer and Telecommunications Networking, 57:17, (3728-3742), Online publication date: 1-Dec-2013.
- Kerschbaum F, Lim H and Gudymenko I Privacy-preserving billing for e-ticketing systems in public transportation Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society, (143-154)
- Dong C, Chen L and Wen Z When private set intersection meets big data Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security, (789-800)
- Sakai H, Wu M, Yamaguchi N and Nakata M Rough Set-Based Information Dilution by Non-deterministic Information Proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume 8170, (55-66)
- Shen E and Yu T Mining frequent graph patterns with differential privacy Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, (545-553)
- Ageev M, Lagun D and Agichtein E Improving search result summaries by using searcher behavior data Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, (13-22)
- Loukides G, Gkoulalas-Divanis A and Shao J (2013). Efficient and flexible anonymization of transaction data, Knowledge and Information Systems, 36:1, (153-210), Online publication date: 1-Jul-2013.
- Maurino A, Venturini C and Viscusi G Coopetitive data warehouse Proceedings of the 25th international conference on Advanced Information Systems Engineering, (482-497)
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- Davidson S, Milo T and Roy S A propagation model for provenance views of public/private workflows Proceedings of the 16th International Conference on Database Theory, (165-176)
- Sun J, Wang F, Hu J and Edabollahi S (2012). Supervised patient similarity measure of heterogeneous patient records, ACM SIGKDD Explorations Newsletter, 14:1, (16-24), Online publication date: 10-Dec-2012.
- Li W r-Anonymized clustering Proceedings of the 19th international conference on Neural Information Processing - Volume Part I, (455-464)
- Wang Y, Wu X, Zhu J and Xiang Y On Learning Cluster Coefficient of Private Networks Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012), (395-402)
- Lee J and Clifton C Differential identifiability Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, (1041-1049)
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- Gambs S, Gmati A and Hurfin M Reconstruction attack through classifier analysis Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy, (274-281)
- Mayer D and Wetzel S Verifiable private equality test Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security, (46-47)
- Fard A, Wang K and Yu P Limiting link disclosure in social network analysis through subgraph-wise perturbation Proceedings of the 15th International Conference on Extending Database Technology, (109-119)
- Benabdeslem K, Effantin B and Elghazel H A graph enrichment based clustering over vertically partitioned data Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I, (42-54)
- Guo J, Zhang P, Tan J and Guo L Mining frequent patterns across multiple data streams Proceedings of the 20th ACM international conference on Information and knowledge management, (2325-2328)
- Majumdar D, Catherine R, Ikbal S and Visweswariah K Privacy protected knowledge management in services with emphasis on quality data Proceedings of the 20th ACM international conference on Information and knowledge management, (1889-1894)
- Biskup J and Tadros C Inference-Proof view update transactions with minimal refusals Proceedings of the 6th international conference, and 4th international conference on Data Privacy Management and Autonomous Spontaneus Security, (104-121)
- Taneja K, Grechanik M, Ghani R and Xie T Testing software in age of data privacy Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering, (201-211)
- Gkoulalas-Divanis A and Cope E (2011). A publication process model to enable privacy-aware data sharing, IBM Journal of Research and Development, 55:5, (517-526), Online publication date: 1-Sep-2011.
- Tran D, Ng W, Lim H and Nguyen H An efficient cacheable secure scalar product protocol for privacy-preserving data mining Proceedings of the 13th international conference on Data warehousing and knowledge discovery, (354-366)
- Gkoulalas-Divanis A and Loukides G Revisiting sequential pattern hiding to enhance utility Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, (1316-1324)
- Monreale A, Trasarti R, Pedreschi D, Renso C and Bogorny V (2011). C-safety, Transactions on Data Privacy, 4:2, (73-101), Online publication date: 1-Aug-2011.
- Davidson S, Khanna S, Milo T, Panigrahi D and Roy S Provenance views for module privacy Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, (175-186)
- Minami T and Kim E Seat usage data analysis and its application for library marketing Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I, (238-247)
- Ray S, Nizam M, Das S and Fung B Verification of data pattern for interactive privacy preservation model Proceedings of the 2011 ACM Symposium on Applied Computing, (1716-1723)
- Davidson S, Khanna S, Roy S, Stoyanovich J, Tannen V and Chen Y On provenance and privacy Proceedings of the 14th International Conference on Database Theory, (3-10)
- Mohammed N, Fung B, Hung P and Lee C (2010). Centralized and Distributed Anonymization for High-Dimensional Healthcare Data, ACM Transactions on Knowledge Discovery from Data, 4:4, (1-33), Online publication date: 1-Oct-2010.
- Cano I and Torra V Edit constraints on microaggregation and additive noise Proceedings of the international ECML/PKDD conference on Privacy and security issues in data mining and machine learning, (1-14)
- Bezzi M, De Capitani Di Vimercati S, Livraga G and Samarati P Protecting privacy of sensitive value distributions in data release Proceedings of the 6th international conference on Security and trust management, (255-270)
- Van Quoc P and Dang T eM² Proceedings of the 7th VLDB conference on Secure data management, (26-40)
- Kadampur M and Somayajulu D Privacy preserving technique for Euclidean distance based mining algorithms using a wavelet related transform Proceedings of the 11th international conference on Intelligent data engineering and automated learning, (202-209)
- Yang B, Nakagawa H, Sato I and Sakuma J Collusion-resistant privacy-preserving data mining Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, (483-492)
- Yang B and Nakagawa H Computation of ratios of secure summations in multi-party privacy-preserving latent dirichlet allocation Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I, (189-197)
- Fung B, Wang K, Chen R and Yu P (2010). Privacy-preserving data publishing, ACM Computing Surveys, 42:4, (1-53), Online publication date: 1-Jun-2010.
- Chakrabarti S, Chen Z, Gangopadhyay A and Mukherjee S Privacy preserving linear discriminant analysis from perturbed data Proceedings of the 2010 ACM Symposium on Applied Computing, (610-615)
- Wang S, Lai T, Hong T and Wu Y (2010). Hiding collaborative recommendation association rules on horizontally partitioned data, Intelligent Data Analysis, 14:1, (47-67), Online publication date: 1-Jan-2010.
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- Mohammed N, Fung B, Hung P and Lee C Anonymizing healthcare data Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, (1285-1294)
- Chen B, Kifer D, LeFevre K and Machanavajjhala A (2009). Privacy-Preserving Data Publishing, Foundations and Trends in Databases, 2:1–2, (1-167), Online publication date: 1-Jan-2009.
- Liu K and Terzi E Towards identity anonymization on graphs Proceedings of the 2008 ACM SIGMOD international conference on Management of data, (93-106)
Index Terms
- Privacy-Preserving Data Mining: Models and Algorithms
Reviews
Aris Gkoulalas-Divanis
Since Gutenberg's era, there hasn't been an invention providing individuals with the capability to access information that is more powerful and far reaching than Google. This invention, however, relied on advances in different areas of computer science (CS), including algorithms, data structures, and computer systems. This book is an up-to-date and well-written textbook for an increasingly important and rapidly growing area of CS. The authors provide a comprehensive and erudite presentation of classical and Web information retrieval techniques. The first eight chapters are devoted to the basics of information retrieval and, in particular, the heart of search engines. The next chapters cover a variety of more advanced topics. Specifically, chapters 9 to 12 cover relevance feedback, Extensible Markup Language (XML) retrieval, probability information retrieval, and language models. Chapters 13 to 18 "give a treatment of various forms of machine learning and numerical methods in information retrieval." Chapters 19 to 21 deal with Web search. The book covers every important aspect of information retrieval, and is presented in an original and practical way. Although there are many books on the market that deal with this subject, this particular book is an excellent resource, and could be used as the primary textbook for information retrieval undergraduate and postgraduate courses. In fact, this book is the result of a series of courses that the authors taught at their institutions. A set of exercises is provided at the end of each chapter to further solidify the material covered. I found the examples quite useful. The user-friendly index is also worth mentioning; it was very helpful for quickly looking up content. Finally, the Web site for the book was also very useful (http://www-csli.stanford.edu/~hinrich/information-retrieval-book.html). The Web site contains a set of slides for each chapter, as well as a set of information retrieval resources. This book will appeal to a large audience, including graduate and postgraduate students and research engineers. Overall, this is an interesting and informative book that presents up-to-date coverage of information retrieval fundamentals. Online Computing Reviews Service
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