Privacy-preserving tabular data publishing: A comprehensive evaluation from web to cloud

Computers & Security - Tập 72 - Trang 74-95 - 2018
Saad A. Abdelhameed1, Sherin M. Moussa2, Mohamed E. Khalifa1
1Faculty of Engineering and Technology, Egyptian Chinese University (ECU), Cairo 11351, Egypt
2Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt

Tài liệu tham khảo

Aggarwal, 2004, A condensation approach to privacy preserving data mining, 183 Aggarwal, 2003, A framework for clustering evolving data streams, 81 Agrawal, 2000, Privacy-preserving data mining, vol. 29, 439 Bacchus, 1992, From statistics to beliefs, 602 Banahatti, 2009, SafeMask Bayardo, 2005, Data privacy through optimal k-anonymization, 217 Blum, 2013, A learning theory approach to noninteractive database privacy, J ACM, 60, 12, 10.1145/2450142.2450148 Blum, 1973, Time bounds for selection, J Comput Syst Sci, 7, 448, 10.1016/S0022-0000(73)80033-9 Byun, 2006, Secure anonymization for incremental datasets, 48 Camenisch, 2001, An efficient system for non-transferable anonymous credentials with optional anonymity revocation, 93 Cao, 2008, CASTLE: a delay-constrained scheme for Ks-anonymizing data streams, 1376 Chakravorty, 2013, Privacy preserving data analytics for smart homes, 23 Chakravorty, 2014, A scalable k-anonymization solution for preserving privacy in an aging-in-place welfare intercloud, 424 Chen, 2009, Privacy-preserving data publishing, Found Trends Databases, 2, 1, 10.1561/1900000008 Chow, 2009, Casper*: query processing for location service without compromising privacy, ACM Trans Database Syst, 34, 1, 10.1145/1620585.1620591 Dean, 2008, MapReduce: simplified data processing on large clusters, Commun ACM, 51, 107, 10.1145/1327452.1327492 Domingo-Ferrer, 2008, An anonymity model achievable via microaggregation, 209 Dwork, 2006, Differential privacy Dwork, 2008, Differential privacy: a survey of results, 1 Dwork, 2006, Calibrating noise to sensitivity in private data analysis, 265 Fung, 2010, Privacy-preserving data publishing: a survey of recent developments, ACM Comput Surv, 42, 14, 10.1145/1749603.1749605 Fung, 2007, Anonymizing classification data for privacy preservation, IEEE Trans Knowl Data Eng, 19, 711, 10.1109/TKDE.2007.1015 Gilbert, 2004, Security analysis of SHA-256 and sisters, vol. 3006, 175 Hamza, 2013, Attacks on anonymization-based privacy-preserving: a survey for data mining and data publishing, J Inf Secur, 4, 101 Hansen, 2004, Privacy-enhancing identity management, Inf Secur Tech Rep, 9, 35, 10.1016/S1363-4127(04)00014-7 Hardt, 2012, A simple and practical algorithm for differentially private data release, 2339 He, 2011, Permutation anonymization: improving anatomy for privacy preservation in data publication, 111 Hendricks, 1936, The sampling distribution of the coefficient of variation, Ann Math Stat, 7, 129, 10.1214/aoms/1177732503 Huang, 2012, User interactive internet of things privacy preserved access control, 597 Huang, 2014, A new anonymity model for privacy-preserving data publishing, China Commun, 11, 47, 10.1109/CC.2014.6969710 Iyengar, 2002, Transforming data to satisfy privacy constraints, 279 Kalnis, 2007, Preventing location-based identity inference in anonymous spatial queries, IEEE Trans Knowl Data Eng, 19, 1719, 10.1109/TKDE.2007.190662 Ke, 2004, Bottom-up generalization: a data mining solution to privacy protection, 249 Kim, 1995, Masking microdata files, 114 Kim, 2014, A framework to preserve the privacy of electronic health data streams, J Biomed Inform, 50, 95, 10.1016/j.jbi.2014.03.015 Kiran, 2012, A survey on methods, attacks and metric for privacy preserving data publishing, Int J Comput Appl, 53 Kiruthika, 2013, Enhanced slicing models for preserving privacy in data publication, 406 LeFevre, 2005, Incognito: efficient full-domain k-anonymity, 49 LeFevre, 2006, Mondrian multidimensional k-anonymity, 25 Leskovec, 2014 Li, 2008, Anonymizing streaming data for privacy protection, 1367 Li, 2008, Preservation of proximity privacy in publishing numerical sensitive data, 473 Li, 2007, T-closeness: privacy beyond k-anonymity and l-diversity, 106 Li, 2010, Closeness: a new privacy measure for data publishing, IEEE Trans Knowl Data Eng, 22, 943, 10.1109/TKDE.2009.139 Li, 2009, Privacy preservation in wireless sensor networks: a state-of-the-art survey, Ad Hoc Netw, 7, 1501, 10.1016/j.adhoc.2009.04.009 Li, 2012, Slicing: a new approach for privacy preserving data publishing, IEEE Trans Knowl Data Eng, 24, 561, 10.1109/TKDE.2010.236 Luo, 2013, ANGELMS: a privacy preserving data publishing framework for microdata with multiple sensitive attributes, 393 Machanavajjhala, 2007, l-diversity: privacy beyond k-anonymity, ACM Trans Knowl Discov Data, 1, 3, 10.1145/1217299.1217302 Maheshwarkar, 2011, Privacy issues for k-anonymity model, Int J Eng Res, 1, 1857 Malina, 2016, On perspective of security and privacy-preserving solutions in the internet of things, Comput Netw, 102, 83, 10.1016/j.comnet.2016.03.011 Mendel, 2006, Analysis of step-reduced SHA-256, 126 Meyerson, 2004, On the complexity of optimal k-anonymity, 223 Mohammadian, 2014, FAST: fast anonymization of big data streams, 23 Mohammed, 2011, Differentially private data release for data mining, 493 Mokbel, 2006, The new Casper: query processing for location services without compromising privacy, 763 Otgonbayar, 2016, Toward anonymizing iot data streams via partitioning, 331 Peterson, 2009, K-nearest neighbor, Scholarpedia, 4, 1883, 10.4249/scholarpedia.1883 Rajaei, 2015, An improved Ambiguity+ anonymization technique with enhanced data utility, 1 Ramos, 2014, Towards privacy-preserving data sharing in smart environments, 334 Rastogi, 2007, The boundary between privacy and utility in data publishing, 531 Rose, 2016, Research paper on privacy preservation by data anonymization in public cloud for hospital management on big data, Int J Adv Comput Technol, 9, 3095 Rubner, 2000, The earth mover's distance as a metric for image retrieval, Int J Comput Vis, 40, 99, 10.1023/A:1026543900054 Sahai, 2005, Fuzzy identity-based encryption, 457 Sakpere, 2015, Adaptive buffer resizing for efficient anonymization of streaming data with minimal information loss, 1 Samarati, 1998, Generalizing data to provide anonymity when disclosing information, vol. 98, 188 Singh, 2013, A review of privacy preserving data publishing technique, Int J Emerg Res Manag Technol, 2278 Soria-Comas, 2016, Big data privacy: challenges to privacy principles and model, Data Sci Eng, 1, 21, 10.1007/s41019-015-0001-x Sowmyarani, 2015, A robust privacy preserving model for data publishing, 1 Sun, 2011, Extended k-anonymity models against sensitive attribute disclosure, Comput Commun, 34, 526, 10.1016/j.comcom.2010.03.020 Sweeney, 2002, k-anonymity: a model for protecting privacy, Int J Unc Fuzz Knowl Based Syst, 10, 557, 10.1142/S0218488502001648 Tao, 2009, Angel: enhancing the utility of generalization for privacy preserving publication, IEEE Trans Knowl Data Eng, 21, 1073, 10.1109/TKDE.2009.65 Truta, 2006, Privacy protection: p-sensitive k-anonymity property, 94 Ukil, 2012, Negotiation-based privacy preservation scheme in internet of things platform, 75 Vennila, 2015, Scalable privacy preservation in big data a survey, Procedia Comput Sci, 50, 369, 10.1016/j.procs.2015.04.033 Wang, 2010, Privacy-preserving data sharing in cloud computing, J Comput Sci Technol, 25, 401, 10.1007/s11390-010-9333-1 Wang, 2010, Providing privacy preserving in cloud computing, 472 Wang, 2007, Handicapping attacker's confidence: an alternative to k-anonymization, Knowl Inf Syst, 11, 345, 10.1007/s10115-006-0035-5 Wang, 2010, B-CASTLE: an efficient publishing algorithm for K-anonymizing data streams, vol. 2, 132 Wang, 2010, SANATOMY: privacy preserving publishing of data streams via anatomy, 54 Wang, 2013, Privacy preserving techniques in the internet of things, vol. 427, 2466 Wang, 2007, Privacy protection on sliding window of data streams, 213 Wei, 2008, Privacy-preserving data publishing based on de-clustering, 152 Wlodarczyk, 2011, Challenges in healthcare and welfare intercloud, 45 Wong, 2006, (α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing, 754 Wu, 2010, P-cover k-anonymity model for protecting multiple sensitive attributes, 179 Xiao, 2006, Anatomy: simple and effective privacy preservation, 139 Xu, 2006, Utility-based anonymization using local recoding, 785 Xu, 2014, A survey of privacy preserving data publishing using generalization and suppression, Appl Math Inf Sci, 8, 1103, 10.12785/amis/080321 Ya-Zhe, 2008, Privacy preserving approaches for multiple sensitive attributes in data publishing, Chin J Comput, 4, 005 Yang, 2010, Research on data streams publishing of privacy preserving, 199 Yang, 2012, Differential privacy in data publication and analysis, 601 Ye, 2009, Decomposition: privacy preservation for multiple sensitive attributes, 486 Yloenen, 1996, SSH – secure login connections over the internet Zakerzadeh, 2011, FAANST: fast anonymizing algorithm for numerical streaming data, 36 Zakerzadeh, 2013, Delay-sensitive approaches for anonymizing numerical streaming data, Int J Inf Secur, 12, 423, 10.1007/s10207-013-0196-7 Zhang, 2007, Aggregate query answering on anonymized tables, 116 Zhang, 1996, BIRCH: an efficient data clustering method for very large databases, vol. 25, 103 Zhang, 2013, SaC-FRAPP: a scalable and cost-effective framework for privacy preservation over big data on cloud, Concurr Comput, 25, 2561, 10.1002/cpe.3083 Zhang, 2013, A scalable two-phase top-down specialization approach for data anonymization using mapreduce on cloud, IEEE Trans Parallel Distrib Syst, 25, 363, 10.1109/TPDS.2013.48 Zhang, 2013, A MapReduce based approach of scalable multidimensional anonymization for big data privacy preservation on cloud, 105 Zhang, 2013, Combining top-down and bottom-up: scalable sub-tree anonymization over big data using MapReduce on cloud, 501 Zhang, 2014, A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud, J Comput Syst Sci, 80, 1008, 10.1016/j.jcss.2014.02.007 Zhu, 2014, Preserving privacy for sensitive values of individuals in data publishing based on a new additive noise approach, 1 Zhu, 2017, Differentially private data publishing and analysis: a survey, IEEE Trans Knowl Data Eng, 29, 10.1109/TKDE.2017.2697856