{"id":"https://openalex.org/W4411137084","doi":"https://doi.org/10.1093/comjnl/bxaf031","title":"Efficient unlearning for data security in deep learning systems","display_name":"Efficient unlearning for data security in deep learning systems","publication_year":2025,"publication_date":"2025-03-15","ids":{"openalex":"https://openalex.org/W4411137084","doi":"https://doi.org/10.1093/comjnl/bxaf031"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxaf031","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaf031","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","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/A5035249711","display_name":"Enting Guo","orcid":"https://orcid.org/0000-0002-3462-1505"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Enting Guo","raw_affiliation_strings":["Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3462-1505","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","institution_ids":["https://openalex.org/I141591182"]},{"raw_affiliation_string":"Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045817362","display_name":"Chunhua Su","orcid":"https://orcid.org/0000-0002-6461-9684"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chunhua Su","raw_affiliation_strings":["Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6461-9684","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","institution_ids":["https://openalex.org/I141591182"]},{"raw_affiliation_string":"Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066098631","display_name":"Peng Li","orcid":"https://orcid.org/0000-0002-5303-0700"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Peng Li","raw_affiliation_strings":["Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5303-0700","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Systems , University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006,","institution_ids":["https://openalex.org/I141591182"]},{"raw_affiliation_string":"Department of Computer and Information Systems, University of Aizu, 90 Kami-iawase, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-0006, Japan","institution_ids":["https://openalex.org/I141591182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5066098631"],"corresponding_institution_ids":["https://openalex.org/I141591182"],"apc_list":{"value":2635,"currency":"GBP","value_usd":3232},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06021915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"68","issue":"9","first_page":"1197","last_page":"1207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9984999895095825,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973999857902527,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7063186168670654},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45333725214004517}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7063186168670654},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45333725214004517}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comjnl/bxaf031","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaf031","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1992365371","https://openalex.org/W2160485179","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2605242105","https://openalex.org/W2734314755","https://openalex.org/W2768412495","https://openalex.org/W2963311299","https://openalex.org/W2985940692","https://openalex.org/W3034831783","https://openalex.org/W3114989277","https://openalex.org/W3134911507","https://openalex.org/W3137684744","https://openalex.org/W3158296418","https://openalex.org/W3174868646","https://openalex.org/W3175270254","https://openalex.org/W3175988580","https://openalex.org/W3202838631","https://openalex.org/W3214586949","https://openalex.org/W3214742003","https://openalex.org/W4224254040","https://openalex.org/W4226167551","https://openalex.org/W4280654230","https://openalex.org/W4281622133","https://openalex.org/W4286893914","https://openalex.org/W4298053029","https://openalex.org/W4309865439","https://openalex.org/W4385890182","https://openalex.org/W6770880833","https://openalex.org/W6778253692","https://openalex.org/W6802936884","https://openalex.org/W6803363973","https://openalex.org/W6804505112","https://openalex.org/W6843630375","https://openalex.org/W6855737893","https://openalex.org/W6973623264"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"Machine":[1],"unlearning":[2,39,47,102],"in":[3,175,182],"the":[4,12,71,87,99,108,189,194],"context":[5],"of":[6,14,75,110,166,188],"cybersecurity":[7,160],"and":[8,64,73,103,128,152,161,178],"privacy":[9,74,162],"protection":[10],"facilitates":[11],"removal":[13],"specific":[15],"training":[16],"data":[17,124,195],"impacts":[18,66],"from":[19,49],"deep":[20],"learning":[21,105],"(DL)":[22],"models,":[23],"adhering":[24],"to":[25,54,60,116,126,144,185],"security,":[26],"privacy,":[27],"or":[28],"compliance":[29],"demands.":[30],"However,":[31],"traditional":[32],"methods":[33,52],"can":[34],"only":[35],"handle":[36],"short-term,":[37],"independent":[38],"tasks.":[40],"Conversely,":[41],"real-world":[42],"scenarios":[43],"often":[44],"involve":[45],"extensive":[46],"demands":[48,58],"users.":[50],"Current":[51],"fail":[53],"adequately":[55],"address":[56],"these":[57,82],"due":[59],"substantial":[61,169],"computational":[62,118,146,183],"overhead":[63,184],"adverse":[65],"on":[67],"inference":[68,130,154,176],"accuracy,":[69],"leaving":[70],"security":[72,196],"many":[76],"users":[77],"at":[78],"risk.":[79],"To":[80],"navigate":[81],"challenges":[83],"adeptly,":[84],"we":[85],"introduce":[86],"Multi-Agent":[88,135],"Reinforcement":[89,136],"Learning":[90,137],"Data":[91],"Lifecycle":[92],"Management":[93],"(MADLM)":[94],"strategy.":[95],"MADLM":[96,139,167],"intricately":[97],"examines":[98],"interactions":[100],"between":[101],"continuous":[104],"processes,":[106],"enabling":[107],"postponement":[109],"certain":[111],"tasks":[112],"for":[113,157],"combined":[114],"execution":[115],"optimize":[117],"resources.":[119],"Concurrently,":[120],"it":[121],"employs":[122],"strategic":[123],"management":[125],"maintain":[127],"enhance":[129],"accuracy.":[131],"Furthermore,":[132],"by":[133],"utilizing":[134],"(MARL),":[138],"dynamically":[140],"orchestrates":[141],"task":[142,149],"scheduling":[143],"minimize":[145],"demands,":[147,191],"improve":[148],"response":[150],"times,":[151],"bolster":[153],"reliability,":[155],"crucial":[156],"upholding":[158],"stringent":[159],"standards.":[163],"Our":[164],"evaluations":[165],"reveal":[168],"enhancements,":[170],"including":[171],"a":[172,179],"6%":[173],"uplift":[174],"accuracy":[177],"dramatic":[180],"reduction":[181],"merely":[186],"12%":[187],"original":[190],"effectively":[192],"expanding":[193],"protections.":[197]},"counts_by_year":[],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}
