{"id":"https://openalex.org/W4311402413","doi":"https://doi.org/10.1080/0952813x.2022.2149861","title":"Preserving sensitive data with deep learning assisted sanitisation process","display_name":"Preserving sensitive data with deep learning assisted sanitisation process","publication_year":2022,"publication_date":"2022-12-04","ids":{"openalex":"https://openalex.org/W4311402413","doi":"https://doi.org/10.1080/0952813x.2022.2149861"},"language":"en","primary_location":{"id":"doi:10.1080/0952813x.2022.2149861","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2022.2149861","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental &amp; Theoretical Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065227279","display_name":"S. Mohana","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"S. Mohana","raw_affiliation_strings":["Department of Computer Science and Engineering, Saranathan college of Engineering, Tiruchirappalli, Tamil Nadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Saranathan college of Engineering, Tiruchirappalli, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077900972","display_name":"C. Shyamala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C. Shyamala","raw_affiliation_strings":["Department of Computer Science and Engineering, K. Ramakrishnan College of Technology, Tiruchirappalli, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, K. Ramakrishnan College of Technology, Tiruchirappalli, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070072949","display_name":"E. Shapna Rani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"E. Shapna Rani","raw_affiliation_strings":["Department of Computer Science and Engineering, Saranathan college of Engineering, Tiruchirappalli, Tamil Nadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Saranathan college of Engineering, Tiruchirappalli, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031111811","display_name":"M. Ambika","orcid":"https://orcid.org/0000-0002-8748-1200"},"institutions":[{"id":"https://openalex.org/I932239252","display_name":"SASTRA University","ror":"https://ror.org/032jk8892","country_code":"IN","type":"education","lineage":["https://openalex.org/I932239252"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Ambika","raw_affiliation_strings":["Department of Computer Science and Engineering, School of Computing, Sastra Deemed University, Tiruchirappalli, Tamil Nadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, School of Computing, Sastra Deemed University, Tiruchirappalli, Tamil Nadu, India","institution_ids":["https://openalex.org/I932239252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065227279"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1388,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56437348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"35","issue":"4","first_page":"589","last_page":"616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.88698810338974},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6925353407859802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5155205726623535},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48752090334892273},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4215832054615021},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41403928399086}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.88698810338974},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6925353407859802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5155205726623535},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48752090334892273},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4215832054615021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41403928399086},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0952813x.2022.2149861","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2022.2149861","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental &amp; Theoretical Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1988566638","https://openalex.org/W2015861736","https://openalex.org/W2121571815","https://openalex.org/W2159058417","https://openalex.org/W2327031957","https://openalex.org/W2511683089","https://openalex.org/W2546350184","https://openalex.org/W2738900493","https://openalex.org/W2784014036","https://openalex.org/W2791668779","https://openalex.org/W2792587090","https://openalex.org/W2793214692","https://openalex.org/W2796305942","https://openalex.org/W2800663842","https://openalex.org/W2809951303","https://openalex.org/W2888422858","https://openalex.org/W2894022047","https://openalex.org/W2896120010","https://openalex.org/W2899516827","https://openalex.org/W2915946102","https://openalex.org/W2942154814","https://openalex.org/W2945031988","https://openalex.org/W2945539353","https://openalex.org/W2950816238","https://openalex.org/W2964756884","https://openalex.org/W2976560662","https://openalex.org/W2979092852","https://openalex.org/W2980435792","https://openalex.org/W2982092879","https://openalex.org/W2990790823","https://openalex.org/W2998553334","https://openalex.org/W2999279232","https://openalex.org/W3004208557","https://openalex.org/W3014777329","https://openalex.org/W3028719682","https://openalex.org/W3035983087","https://openalex.org/W3041440607","https://openalex.org/W3082884334","https://openalex.org/W3092818093","https://openalex.org/W3205187096","https://openalex.org/W3206073763","https://openalex.org/W3206133953","https://openalex.org/W4210708616","https://openalex.org/W4239614867","https://openalex.org/W4308649325","https://openalex.org/W4367181214"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127"],"abstract_inverted_index":{"This":[0],"work":[1],"introduces":[2],"a":[3,84],"novel":[4],"privacy":[5],"preservation":[6,102],"scheme.":[7],"In":[8],"large":[9],"databases,":[10],"the":[11,16,30,36,44,49,52,59,75,79,95,110,113,118,125,131,135,138,144,152,156,184],"data":[12,19,38,45,101,119,160],"sanitisation":[13,46,50,153],"process":[14,121],"preserves":[15],"stored":[17],"sensitive":[18],"safely":[20],"from":[21],"unauthorised":[22],"access":[23],"and":[24,39,68,88,104,128,166,180,197],"users":[25],"by":[26,57],"hiding":[27,105],"it.":[28],"Moreover,":[29],"statistical":[31],"features":[32,40],"are":[33,41,107,141],"extracted.":[34],"Further,":[35],"normalised":[37],"processed":[42],"under":[43],"process.":[47,116,133],"For":[48],"process,":[51],"optimal":[53],"key":[54,114],"is":[55,74,92,130,168],"produced":[56],"utilising":[58],"Deep":[60],"Belief":[61],"Network":[62],"(DBN)":[63],"with":[64],"Chaotic":[65],"Map-adopted":[66],"Poor":[67],"Rich":[69],"Optimisation":[70],"(CMPRO)":[71],"model.":[72],"It":[73],"modified":[76],"version":[77],"of":[78,137,155],"classical":[80],"PRO":[81],"algorithm.":[82,97],"As":[83],"novelty,":[85],"chaotic":[86],"map":[87],"cycle":[89],"crossover":[90],"operation":[91],"included":[93],"in":[94,162],"CMPRO":[96],"Privacy,":[98],"modification":[99],"degree,":[100],"ratio,":[103],"failure":[106],"considered":[108],"as":[109],"objectives":[111],"for":[112,159],"generation":[115],"Then,":[117,134],"restoration":[120],"restores":[122],"or":[123],"recovers":[124],"sanitised":[126],"data,":[127],"it":[129,167],"reverse":[132],"outcomes":[136],"adopted":[139],"scheme":[140],"analysed":[142],"over":[143],"traditional":[145],"systems":[146],"based":[147],"on":[148],"certain":[149],"measures.":[150],"Especially,":[151],"effectiveness":[154],"proposed":[157],"approach":[158],"1":[161],"test":[163],"case":[164],"2":[165],"54.56%,":[169],"51.82%,":[170],"47.94%,":[171],"49.59%,":[172],"18.17%,":[173],"43.32%,":[174],"47.03%,":[175,176],"55.79%,":[177],"21.84%,":[178],"47.33%,":[179],"32.13%":[181],"better":[182],"than":[183],"existing":[185],"CNN+CMPRO,":[186],"RNN+CMPRO,":[187],"LSTM+CMPRO,":[188],"BiLSTM+CMPRO,":[189],"DBN+PRO,":[190],"DBN+SSA,":[191],"DBN+SMO,":[192],"DBN+LA,":[193],"DBN+SSO,":[194],"DBN+J-SSO,":[195],"DBN+BS-WOA,":[196],"DBN+R-GDA":[198],"schemes.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2025-10-10T00:00:00"}
