{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T01:57:29Z","timestamp":1769392649848,"version":"3.49.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,3,28]],"date-time":"2019-03-28T00:00:00Z","timestamp":1553731200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1186\/s40537-019-0193-4","type":"journal-article","created":{"date-parts":[[2019,3,28]],"date-time":"2019-03-28T10:04:04Z","timestamp":1553767444000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Enhanced Secured Map Reduce layer for Big Data privacy and security"],"prefix":"10.1186","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7988-1338","authenticated-orcid":false,"given":"Priyank","family":"Jain","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manasi","family":"Gyanchandani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nilay","family":"Khare","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,3,28]]},"reference":[{"key":"193_CR1","doi-asserted-by":"crossref","unstructured":"Jain P, Gyanchandani M, Khare N. Big data privacy: a technological perspective and review. J Big Data. 2016;3:25. ISSN 2196-1115.","DOI":"10.1186\/s40537-016-0059-y"},{"key":"193_CR2","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.1109\/access.2016.2558446","volume":"4","author":"A Mehmood","year":"2016","unstructured":"Mehmood A, Natgunanathan I, Xiang Y, Hua G, Guo S. Protection of Big Data Privacy. IEEE Access. 2016;4:1821\u201334. \n                    https:\/\/doi.org\/10.1109\/access.2016.2558446\n                    \n                  .","journal-title":"IEEE Access"},{"key":"193_CR3","first-page":"20","volume":"1","author":"S Sagiroglu","year":"2013","unstructured":"Sagiroglu S, Sinanc D. Big Data: a review. J Big Data. 2013;1:20\u20134.","journal-title":"J Big Data"},{"issue":"6","key":"193_CR4","first-page":"7932","volume":"5","author":"V Chavan","year":"2014","unstructured":"Chavan V, Phursule RN. Survey paper on big data. Int J Comput Sci Inf Technol. 2014;5(6):7932\u20139.","journal-title":"Int J Comput Sci Inf Technol."},{"key":"193_CR5","volume-title":"The big data revolution in healthcare","author":"P Groves","year":"2013","unstructured":"Groves P, Kayyali B, Knott D, Kuiken SV. The big data revolution in healthcare. New York: McKinsey & Company; 2013."},{"key":"193_CR6","unstructured":"Lin J. MapReduce is good enough? The control project. IEEE Comput. 2013;32."},{"key":"193_CR7","doi-asserted-by":"crossref","unstructured":"Patel AB, Birla M, Nair U. Addressing Big Data Problem Using Hadoop and Map Reduce,\u201dNirma University International Conference On Engineering in Proc., 2012.","DOI":"10.1109\/NUICONE.2012.6493198"},{"key":"193_CR8","unstructured":"Cevher V, Becker S, Schmidt M. Convex optimization for Big Data: scalable, randomized, and parallel algorithms for Big Data analytics. In: IEEE Signal Processing Magazine. 2014; 31(5), p. 32\u201343."},{"issue":"1\/2","key":"193_CR9","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1504\/IJBDI.2014.063835","volume":"1","author":"M-H Kuo","year":"2014","unstructured":"Kuo M-H, Sahama T, Kushniruk AW, Borycki EM, Grunwell DK. Health Big Data analytics: current perspectives, challenges, and potential solutions. Int J Big Data Intell. 2014;1(1\/2):114\u201326.","journal-title":"Int J Big Data Intell."},{"key":"193_CR10","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1145\/1749603.1749605","volume":"42","author":"BCM Fung","year":"2010","unstructured":"Fung BCM, Wang K, Chen R, Yu PS. Privacy-preserving data publishing: a survey of recent developments. ACM Comput Surveys. 2010;42:4.","journal-title":"ACM Comput Surveys"},{"key":"193_CR11","doi-asserted-by":"crossref","unstructured":"Machanavajjhala A, Gehrke J, Kifer D. L-diversity: privacy beyond k-anonymity,\u201d 22nd International Conference on Data Engineering (ICDE\u201906), Atlanta, GA, USA, 2006, p. 24.","DOI":"10.1109\/ICDE.2006.1"},{"key":"193_CR12","doi-asserted-by":"crossref","unstructured":"R. Nix, M. Kantarcioglu, and K. J. Han, Approximate privacy preserving data mining on vertically partitioned data, in Data and Applications Security and Privacy XXVI, Springer, 2012, p. 129-144.","DOI":"10.1007\/978-3-642-31540-4_11"},{"key":"193_CR13","doi-asserted-by":"crossref","unstructured":"Jain P, Pathak N, Tapashetti P, Umesh AS. Privacy-preserving processing of data decision tree based on sample selection and Singular Value Decomposition, 2013 In: 9th International Conference on Information Assurance and Security (IAS), Gammarth, 2013, p. 91\u20135.","DOI":"10.1109\/ISIAS.2013.6947739"},{"issue":"1","key":"193_CR14","first-page":"18","volume":"12","author":"P Jain","year":"2017","unstructured":"Jain P, Gyanchandani M, Khare N. Privacy and security concerns in healthcare big data: an innovative prescriptive. J Inform Assur Secur. 2017;12(1):18\u201330.","journal-title":"J Inform Assur Secur"},{"key":"193_CR15","doi-asserted-by":"crossref","unstructured":"Yin C, Zhang S, Xi J, Wang J. An improved anonymity model for Big Data security based on clustering algorithm\u201d Combined Special Issues on Security and privacy in social networks (NSS2015) and 18th IEEE International Conference on Computational Science and Engineering (CSE2015). Volume 29, Issue 7 10, 2017.","DOI":"10.1002\/cpe.3902"},{"key":"193_CR16","unstructured":"Big Data Top challenge 2016. Online. \n                    https:\/\/downloads.cloudsecurityalliance.org\/initiatives\/bdwg\/BigDataTopTenv1.pdf\n                    \n                  . Accessed 15 Jan 2018."},{"key":"193_CR17","unstructured":"Big Data Submits Online. \n                    https:\/\/theinnovationenterprise.com\/summits\/big-data-innovation-mumbai\/eventactivities=5546\n                    \n                  . Accessed 17 Feb 2018."},{"key":"193_CR18","unstructured":"The intersection of privacy and security data privacy day event 2012. \n                    https:\/\/concurringopinions.com\/archives\/2012\/01\/the-intersection-of-privacy-and-security-data-privacy-day-event-at-gw-law-school.html\n                    \n                  . Accessed 16 Feb 2018."},{"key":"193_CR19","doi-asserted-by":"crossref","unstructured":"Savas O, Deng J. Big data analytics in cybersecurity. CRC Press, Taylor Francis Group, 2017.","DOI":"10.1201\/9781315154374"},{"key":"193_CR20","doi-asserted-by":"crossref","unstructured":"Priyank Jain, Manasi Gyanchandani and Nilay Khare,\u201dData Privacy for Big Data Publishing Using Newly Enhanced PASS Data Mining Mechanism\u201d, Data mining book chapter, Intech open Publisher,2018. DOI: \n                    http:\/\/dx.doi.org\/10.5772\/intechopen.77033\n                    \n                  .","DOI":"10.5772\/intechopen.77033"},{"key":"193_CR21","unstructured":"Mohammadian E, Noferesti M, Jalili R. FAST: Fast Anonymization of Big Data Streams. In: Proc. of the 2014 International Conference on Big Data Science and Computing, p. 23, 2014."},{"key":"193_CR22","doi-asserted-by":"crossref","unstructured":"Evfimievski S. Randomization techniques for privacy preserving association rule mining. In: SIGKDD Explorations. 2002; 4(2).","DOI":"10.1145\/772862.772869"},{"key":"193_CR23","doi-asserted-by":"crossref","unstructured":"K. Tripathy, Anirban Mitra, An Algorithm to achieve k-anonymity and l-diversity anonymization in Social Networks, In Proc. of Fourth International Conference on Computational Aspects of Social Networks (CA-SoN), Sao Carlos, 2012.","DOI":"10.1109\/CASoN.2012.6412390"},{"key":"193_CR24","doi-asserted-by":"crossref","unstructured":"Jain P., Gyanchandani M., Khare N, Improved k-Anonymity Privacy-Preserving Algorithm Using Madhya Pradesh State Election Commission Big Data, Integrated Intelligent Computing, Communication, and Security. Studies in Computational Intelligence, vol 771. Springer, Singapore p. 1\u201310, 2019.","DOI":"10.1007\/978-981-10-8797-4_1"},{"key":"193_CR25","series-title":"Lecture Notes in Computer Science","volume-title":"Intelligent data engineering and automated learning\u2014IDEAL","author":"MA Kadampur","year":"2008","unstructured":"Kadampur MA. A data perturbation method by field rotation and binning by averages strategy for privacy preservation. In: Fyfe C, Kim D, Lee SY, Yin H, editors. Intelligent data engineering and automated learning\u2014IDEAL, vol. 5326., Lecture Notes in Computer ScienceBerlin: Springer; 2008."},{"key":"193_CR26","doi-asserted-by":"crossref","unstructured":"LeFevre K, DeWitt DJ, Ramakrishnan R. Mondrian multidimensional k-anonymity\u2019. Proc. 22nd Int. Conf. Data Engineering, Ser. ICDE\u201906, Washington, DC, USA: IEEE Computer Society, April 2006, p. 1\u201311.","DOI":"10.1109\/ICDE.2006.101"},{"key":"193_CR27","doi-asserted-by":"crossref","unstructured":"Zakerzadeh, H., Aggarwal, C.C., Barker, K.: \u2018Privacy-preserving big data publishing\u2019. Proc. 27th Int. Conf. Scientific and Statistical Database Management, Ser. SSDBM \u201815, New York: ACM; 2015, p. 26:1\u201326:11.","DOI":"10.1145\/2791347.2791380"},{"key":"193_CR28","unstructured":"Roy I, Ramadan HE, Setty STV, Kilzer A, Shmatikov V, Witchel E. Airavat: Security and privacy for MapReduce, In: Castro M, eds. In: Proc. of the 7th Usenix Symp. on Networked Systems Design and Implementation. San Jose: USENIX Association; 2010."},{"key":"193_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cosrev.2016.05.001","volume":"20","author":"P Derbeko","year":"2016","unstructured":"Derbeko P, et al. Security and privacy aspects in MapReduce on clouds: a survey. Comput Sci Rev. 2016;20:1.","journal-title":"Comput Sci Rev"},{"key":"193_CR30","doi-asserted-by":"publisher","unstructured":"Pathak K, Chaudhari NS, Tiwari A. Privacy preserving association rule mining by introducing concept of impact factor. In: 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), Singapore, 2012, p. 1458\u201361. \n                    https:\/\/doi.org\/10.1109\/iciea.2012.6360953\n                    \n                  .","DOI":"10.1109\/iciea.2012.6360953"},{"key":"193_CR31","doi-asserted-by":"publisher","first-page":"16319","DOI":"10.1007\/s11042-017-5200-1","volume":"77","author":"GS Yadav","year":"2018","unstructured":"Yadav GS, Ojha A. Multimed Tools Appl. 2018;77:16319. \n                    https:\/\/doi.org\/10.1007\/s11042-017-5200-1\n                    \n                  .","journal-title":"Multimed Tools Appl"},{"key":"193_CR32","doi-asserted-by":"crossref","unstructured":"Terzi, R. Terzi, and S. Sagiroglu. A survey on security and privacy issues in Big Data. In Proc. of ICITST 2015, London, UK, December 2015.","DOI":"10.1109\/ICITST.2015.7412089"},{"key":"193_CR33","doi-asserted-by":"crossref","unstructured":"Kacha L, Zitouni A. An Overview on Data Security in Cloud Computing, CoMeSySo: cybernetics approaches in intelligent systems, Springer, 2017, p. 250\u201361.","DOI":"10.1007\/978-3-319-67618-0_23"},{"key":"193_CR34","volume-title":"An evolutionary feature set decomposition based anonymization for classification workloads: privacy preserving data mining Journal of cluster computing","author":"K Ilavarasi","year":"2017","unstructured":"Ilavarasi K, Sathiyabhama B. An evolutionary feature set decomposition based anonymization for classification workloads: privacy preserving data mining Journal of cluster computing. New York: Springer; 2017."},{"key":"193_CR35","unstructured":"Acampora G, et al. Data analytics for pervasive health. In: Healthcare data analytics, ISSN: 533-576, 2015."},{"issue":"5","key":"193_CR36","first-page":"82","volume":"4","author":"AP Kulkarni","year":"2014","unstructured":"Kulkarni AP, Khandewal M. Survey on hadoop and introduction to YARN. Int J Emerg Technol Adv Eng. 2014;4(5):82\u20137.","journal-title":"Int J Emerg Technol Adv Eng"},{"key":"193_CR37","unstructured":"Yu E, Deng S. Understanding software ecosystems: a strategic modeling approach, in Proceedings of the Workshop on Software Ecosystems 2011, IWSECO-2011. p. 6-16."},{"key":"193_CR38","doi-asserted-by":"crossref","unstructured":"Shim K. MapReduce Algorithms for Big Data Analysis, DNIS, LNCS, 2013. p. 44\u20138.","DOI":"10.1007\/978-3-642-37134-9_3"},{"key":"193_CR39","unstructured":"Arora S, Goel DM. Survey Paper on scheduling in hadoop international journal of advanced research in computer science and software engineering. 2014; 4(5)."},{"key":"193_CR40","doi-asserted-by":"crossref","unstructured":"Jain P., Gyanchandani M., Khare N. \u201cBig Data Security and Privacy: New Proposed Model of Big Data with Secured MR Layer\u201d, Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 883. Springer, Singapore 2019.","DOI":"10.1007\/978-981-13-3702-4_3"},{"issue":"5","key":"193_CR41","first-page":"55770","volume":"10","author":"L Sweeney","year":"2002","unstructured":"Sweeney L. K-anonymity: a model for protecting privacy. Int J Uncertain Fuzz. 2002;10(5):55770.","journal-title":"Int J Uncertain Fuzz."},{"key":"193_CR42","volume-title":"Privacy-preserving Big Data publishing","author":"CC Zakerdah","year":"2015","unstructured":"Zakerdah CC, Aggarwal KB. Privacy-preserving Big Data publishing. La Jolla: ACM; 2015."},{"issue":"5","key":"193_CR43","first-page":"96","volume":"93","author":"T Morey","year":"2015","unstructured":"Morey T, Forbath T, Schoop A. Customer data: designing for transparency and trust. Harvard Business Rev. 2015;93(5):96\u2013105.","journal-title":"Harvard Business Rev."},{"issue":"4","key":"193_CR44","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1007\/s00778-006-0039-5","volume":"17","author":"A Friedman","year":"2008","unstructured":"Friedman A, Wolff R, Schuster A. Providing k-anonymity in data mining. VLDB J. 2008;17(4):789\u2013804.","journal-title":"VLDB J."},{"key":"193_CR45","first-page":"42","volume":"1","author":"B Fung","year":"2010","unstructured":"Fung B, et al. Privacy-preserving data publishing: a survey of recent developments. ACM Comput Surveys (CSUR). 2010;1:42\u20134.","journal-title":"ACM Comput Surveys (CSUR)"},{"key":"193_CR46","unstructured":"Ko SY, Jeon K, Morales R. The HybrEx model for confidentiality and privacy in cloud computing. In: 3rd USENIX workshop on hot topics in cloud computing, HotCloud\u201911, Portland; 2011."},{"key":"193_CR47","unstructured":"Apache Hive. \n                    http:\/\/hive.apache.org\n                    \n                  . Accessed 18 Mar 2018."},{"key":"193_CR48","unstructured":"ApacheHDFS. \n                    http:\/\/hadoop.apache.org\/hdfs\n                    \n                  . Accessed 17 Mar 2018."},{"key":"193_CR49","unstructured":"Tweepy dataset online. \n                    https:\/\/marcobonzanini.com\/2015\/03\/02\/mining-twitter-data-with-python-part-1\/\n                    \n                  . Accessed 18 March 2018."},{"key":"193_CR50","unstructured":"Ghinita G, Karras P, Kalnis P, Mamoulis N. Fast data anonymization with low information loss. In: Proc. Int\u2019l Conf. very large data bases (VLDB), p. 758\u201369, 2007."}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-019-0193-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s40537-019-0193-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-019-0193-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,27]],"date-time":"2020-03-27T00:09:43Z","timestamp":1585267783000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofbigdata.springeropen.com\/articles\/10.1186\/s40537-019-0193-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,28]]},"references-count":50,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["193"],"URL":"https:\/\/doi.org\/10.1186\/s40537-019-0193-4","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,28]]},"assertion":[{"value":"29 November 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 March 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 March 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"30"}}