{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T16:56:21Z","timestamp":1781974581088,"version":"3.54.5"},"reference-count":9,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2020,12,4]]},"abstract":"<jats:p>Like many open-source technologies such as UNIX or TCP\/IP, Hadoop was not created with Security in mind. Hadoop however evolved from the other tools over time and got widely adopted across large enterprises. Some of Hadoop\u2019s architectural features present Hadoop its unique security issues. Given this security vulnerability and potential invasion of confidentiality due to malicious attackers or internal customers, organizations face challenges in implementing a strong security framework for Hadoop. Furthermore, given the method in which data is placed in Hadoop Cluster adds to the only growing list of these potential security vulnerabilities. Data privacy is compromised when these critical and data-sensitive blocks are accessed either by unauthorized users or for that matter even misuse by authorized users. In this paper, we intend to address the strategy of data block placement across the allotted DataNodes. Prescriptive analytics algorithms are used to determine the Sensitivity Index of the Data and thereby decide on data placement allocation to provide impenetrable access to an unauthorized user. This data block placement strategy aims to adaptively distribute the data across the cluster using innovative ML techniques to make the data infrastructure extra secured.<\/jats:p>","DOI":"10.3233\/jifs-189165","type":"journal-article","created":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T13:10:06Z","timestamp":1601989806000},"page":"8477-8486","source":"Crossref","is-referenced-by-count":5,"title":["HadoopSec 2.0: Prescriptive analytics-based multi-model sensitivity-aware constraints centric block placement strategy for Hadoop"],"prefix":"10.1177","volume":"39","author":[{"given":"P.","family":"Revathy","sequence":"first","affiliation":[{"name":"Cognizant Techmology Solutions, Changi Business Park Crescent, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajeswari","family":"Mukesh","sequence":"additional","affiliation":[{"name":"Deparment of Computer Science, Hindustan University, Padur, Kelambakam, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-189165_ref1","unstructured":"Kumar A. , et al., Identifying Sensitive Data Items within Hadoop, 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC)."},{"key":"10.3233\/JIFS-189165_ref2","unstructured":"Xie J. , et al., Improving MapReduce performance through data placement in heterogeneous Hadoop clusters, 2010 IEEE International Symposium \u2013 2010."},{"key":"10.3233\/JIFS-189165_ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2345396.2345474"},{"key":"10.3233\/JIFS-189165_ref4","unstructured":"Ye X. , et al., A Novel Blocks Placement Strategy for Hadoop, Computer and Information Science (ICIS), 2012."},{"key":"10.3233\/JIFS-189165_ref5","doi-asserted-by":"crossref","unstructured":"Yadav, et al., Big Data Hadoop: Security and Privacy, 2nd International Conference on Advanced Computing and Software Engineering \u2013 2019.","DOI":"10.2139\/ssrn.3350308"},{"key":"10.3233\/JIFS-189165_ref6","doi-asserted-by":"crossref","unstructured":"Jain P. , et al., Enhanced Secured Map Reduce layer for Big Data privacy and security, Journal of Big Data, 2019.","DOI":"10.1186\/s40537-019-0193-4"},{"key":"10.3233\/JIFS-189165_ref7","doi-asserted-by":"crossref","unstructured":"Luo J. , et al., Word clustering based on word2vec and semantic similarity, IEEE: ISBN: 978-9-8815-6387-3, 2014.","DOI":"10.1109\/ChiCC.2014.6896677"},{"key":"10.3233\/JIFS-189165_ref8","unstructured":"Eissa M. , et al., Improvement of Sentiment Analysis Based on Clustering of Word2Vec Features, IEEE: ISBN: 978-1-5386-1051-0, 2017."},{"key":"10.3233\/JIFS-189165_ref9","doi-asserted-by":"crossref","unstructured":"Xiong C. , et al., An Improved K-means Text Clustering Algorithm by Optimizing Initial Cluster Centers, IEEE: ISBN:978-1-5090-3555-7, 2016.","DOI":"10.1109\/CCBD.2016.059"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-189165","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:41:41Z","timestamp":1777455701000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-189165"}},"subtitle":[],"editor":[{"given":"Vijayakumar","family":"Varadarajan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"Piet","family":"Kommers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"Vincenzo","family":"Piuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"V.","family":"Subramaniyaswamy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2020,12,4]]},"references-count":9,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.3233\/jifs-189165","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,4]]}}}