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Pre-processing is completed and documents are compared and verified with the use of wordnet. Cosine similarity is employed to see the similarity between both the documents and to perform this, a far economical VSM data structure is used. Wordnet hierarchical corpus is used to see syntax and semantics so that the identification of duplicates is done. NLTK provides a large vary of libraries and programs for symbolic and statistical natural language process (NLP) for the Python programming language that is used here for the unidentified words by cosine similarity. Within the previous strategies, cloud storage was used abundantly since similar files were allowed to store. By implementing our system, space for storing is reduced up to 85%. Since AES and SHA-256 are employed, it provides high security and efficiency.<\/jats:p>","DOI":"10.3233\/jifs-210038","type":"journal-article","created":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T10:55:41Z","timestamp":1627642541000},"page":"2969-2980","source":"Crossref","is-referenced-by-count":15,"title":["An efficient technique for cloud storage using secured de-duplication algorithm"],"prefix":"10.1177","volume":"41","author":[{"given":"Prakash","family":"Mohan","sequence":"first","affiliation":[{"name":"Data Science and Analytics Center, Karpagam College of Engineering, Coimbatore, India"}]},{"given":"Manikandan","family":"Sundaram","sequence":"additional","affiliation":[{"name":"Data Science and Analytics Center, Karpagam College of Engineering, Coimbatore, India"}]},{"given":"Sambit","family":"Satpathy","sequence":"additional","affiliation":[{"name":"Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, 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