Big Data Privacy: Challenges to Privacy Principles and Models
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Aggarwal G, Feder T, Kenthapadi K, Motwani R, Panigrahy R, Thomas D, Zhu A (2005) Anonymizing tables. In: Eiter T, Libkin L (eds) Database theory—ICDT 2005, vol 3363., Lecture Notes in Computer Science. Springer, Berlin, p 246–258
Barbaro M, Zeller T (2006) A face is exposed for AOL searcher no. 4417749. New York Times, August 14
Brookman J, Hans GS (2013) Why collection matters: surveillance as a de facto privacy harm. In: Big data and privacy: making ends meet. The center for internet and society - Stanford Law School
Chen A (2010) Gcreep: google engineer stalked teens, spied on chats. Gawker, New York
Cormode G, Procopiuc C, Srivastava D, Shen E, Yu T (2012) Differentially private spatial decompositions. In: Proceedings of the 2012 IEEE 28th international conference on data engineering. ICDE’12, Washington, DC, USA. IEEE Computer Society, p 20–31
Danezis G, Domingo-Ferrer J, Hansen M, Hoepman J-H, Le Métayer D, Tirtea R, Schiffner S (2015) Privacy and data protection by design—from policy to engineering. Technical report, ENISA
Dean J, Ghemawat S (2008) MapReduce: simplified data processing on large clusters. Comm ACM 51(1):107–113
Domingo-Ferrer J, Torra V (2005) Ordinal, continuous and heterogeneous k-anonymity through microaggregation. Data Min Knowl Discov 11(2):195–212
Duhigg C (2012) How companies learn your secrets. New York Times Magazine, February 16
Dwork C (2006) Differential privacy. In: Bugliesi M, Preneel B, Sassone V, Wegener I (eds) Automata, languages and programming, vol 4052., Lecture notes in computer science. Berlin, Springer, p 1–12
Dwork C, McSherry F, Nissim K, Smith A (2006) Calibrating noise to sensitivity in private data analysis. In: Halevi S, Rabin T (eds) Proceedings of the third conference on the theory of cryptography, vol 3876., lecture notes in computer science. Springer, p 265–284
Ganta SR, Kasiviswanathan SP, Smith A (2008) Composition attacks and auxiliary information in data privacy. In: Proceedings of the 14th ACM SIGKDD international conference on knowledge discovery and data mining, KDD’08, New York, NY, USA. ACM, p 265–273
Hansell S (2006) AOL removes search data on vast group of web users. New York Times, August 8
Hundepool A, Domingo-Ferrer J, Franconi L, Giessing S, Nordholt ES, Spicer K, de Wolf P-P (2012) Statistical disclosure control. Wiley, New York
LeFevre K, DeWitt DJ, Ramakrishnan R (2005) Incognito: efficient full-domain k-anonymity. In: Proceedings of the 2005 ACM SIGMOD international conference on management of data, SIGMOD’05, New York, NY, USA. ACM, p 49–60
LeFevre K, DeWitt DJ, Ramakrishnan R (2006) Mondrian multidimensional k-anonymity. In: Proceedings of the 22nd international conference on data engineering, ICDE’06, Washington, DC, USA. IEEE Computer Society
Li N, Li T, Venkatasubramanian S (2007) t-Closeness: privacy beyond k-anonymity and l-diversity. In: Chirkova R, Dogac A, Özsu MT, Sellis TK (eds) Proceedings of the 23rd IEEE international conference on data engineering (ICDE 2007), p 106–115
Machanavajjhala A, Kifer D, Gehrke J, Venkitasubramaniam M (2007) l-diversity: privacy beyond k-anonymity. ACM Trans Knowl Discov Data, 1(1):3
Machanavajjhala A, Kifer D, Abowd J, Gehrke J, Vilhuber L (2008) Privacy: theory meets practice on the map. In: Proceedings of the 2008 IEEE 24th international conference on data engineering, ICDE’08, Washington, DC, USA. IEEE Computer Society, p 277–286
McSherry FD (2009) Privacy integrated queries: an extensible platform for privacy-preserving data analysis. In: Proceedings of the 2009 ACM SIGMOD international conference on management of data, SIGMOD’09, New York, NY, USA. ACM, p 19–30
Meyerson A, Williams R (2004) On the complexity of optimal k-anonymity. In: Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems, PODS’04, New York, NY, USA. ACM, p 223–228
Nissim K, Raskhodnikova S, Smith A (2007) Smooth sensitivity and sampling in private data analysis. In: Proceedings of the thirty-ninth annual ACM symposium on the theory of computing, STOC’07, New York, NY, USA. ACM, p 75–84
Oganian A, Domingo-Ferrer J (2001) On the complexity of optimal microaggregation for statistical disclosure control. Stat J UN Econ Comm Eur 18:345–354
Samarati P (2001) Protecting respondents’ identities in microdata release. IEEE Trans Knowl Data Eng 13(6):1010–1027
Sánchez D, Domingo-Ferrer J, Martínez S (2014) Improving the utility of differential privacy via univariate microaggregation. In: Domingo-Ferrer J (ed) Privacy in statistical databases, vol 8744, lecture notes in computer science. Springer, New York, pp 130–142
Smith A (2011) Privacy-preserving statistical estimation with optimal convergence rates. In: Proceedings of the forty-third annual ACM symposium on theory of computing, STOC’11, New York, NY, USA. ACM, p 813–822
Solove DJ (2011) Nothing to hide: the false tradeoff between privacy an security. Yale University Press, New Haven
Soria-Comas J, Domingo-Ferrer J (2012) Probabilistic k-anonymity through microaggregation and data swapping. In: Proceedings of the IEEE international conference on fuzzy systems (FUZZ-IEEE 2012), p 1–8
Soria-Comas J, Domingo-Ferrer J, Sánchez D, Martínez S (2014) Enhancing data utility in differential privacy via microaggregation-based k-anonymity. VLDB J 23(5):771–794
Xiao Y, Xiong L, Yuan C (2010) Differentially private data release through multidimensional partitioning. In: Proceedings of the 7th VLDB conference on secure data management, SDM’10. Springer, Berlin, p 150–168
Xu J, Zhang Z, Xiao X, Yang Y, Yu G (2012) Differentially private histogram publication. In: Proceedings of the 2012 IEEE 28th international conference on data engineering, ICDE’12, Washington, DC, USA. IEEE Computer Society, p 32–43