{"id":"https://openalex.org/W3119157379","doi":"https://doi.org/10.1109/ieem45057.2020.9309965","title":"Efficient Detection of Shilling\u2019s Attacks in Collaborative Filtering Recommendation Systems Using Deep Learning Models","display_name":"Efficient Detection of Shilling\u2019s Attacks in Collaborative Filtering Recommendation Systems Using Deep Learning Models","publication_year":2020,"publication_date":"2020-12-14","ids":{"openalex":"https://openalex.org/W3119157379","doi":"https://doi.org/10.1109/ieem45057.2020.9309965","mag":"3119157379"},"language":"en","primary_location":{"id":"doi:10.1109/ieem45057.2020.9309965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem45057.2020.9309965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-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/A5034758163","display_name":"Mahsa Ebrahimian","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Mahsa Ebrahimian","raw_affiliation_strings":["Ryerson University,Electrical, Computer, and Biomedical Engineering,Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University,Electrical, Computer, and Biomedical Engineering,Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058900041","display_name":"Rasha Kashef","orcid":"https://orcid.org/0000-0003-3448-1079"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rasha Kashef","raw_affiliation_strings":["Ryerson University,Electrical, Computer, and Biomedical Engineering,Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University,Electrical, Computer, and Biomedical Engineering,Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034758163"],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":3.2028,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9352759,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"460","last_page":"464"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9811999797821045,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9645000100135803,"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/movielens","display_name":"MovieLens","score":0.89300137758255},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8542724847793579},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.82262122631073},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7181801795959473},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6871309876441956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6151733994483948},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5493341684341431},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48324164748191833},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37672412395477295}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.89300137758255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8542724847793579},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.82262122631073},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7181801795959473},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6871309876441956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6151733994483948},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5493341684341431},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48324164748191833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37672412395477295}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem45057.2020.9309965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem45057.2020.9309965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W281665770","https://openalex.org/W1989279326","https://openalex.org/W2022613648","https://openalex.org/W2025605741","https://openalex.org/W2044831856","https://openalex.org/W2048590193","https://openalex.org/W2071099735","https://openalex.org/W2122114437","https://openalex.org/W2140113562","https://openalex.org/W2340119171","https://openalex.org/W2413004790","https://openalex.org/W2509678028","https://openalex.org/W2783819197","https://openalex.org/W2791170775","https://openalex.org/W2794121917","https://openalex.org/W2805055069","https://openalex.org/W2944887360","https://openalex.org/W2971193433","https://openalex.org/W3007805702","https://openalex.org/W3012231004","https://openalex.org/W3029742830","https://openalex.org/W6751950039"],"related_works":["https://openalex.org/W2402445420","https://openalex.org/W1570823782","https://openalex.org/W2075040002","https://openalex.org/W937687500","https://openalex.org/W2978419074","https://openalex.org/W3119157379","https://openalex.org/W2964316708","https://openalex.org/W3170046637","https://openalex.org/W2900416585","https://openalex.org/W2967807570"],"abstract_inverted_index":{"Recommendation":[0],"systems,":[1],"especially":[2],"collaborative":[3],"filtering":[4],"recommenders,":[5],"are":[6,31],"vulnerable":[7],"to":[8,22,45,56,83,117],"shilling":[9,27,85],"attacks":[10,101],"as":[11],"some":[12],"profit-driven":[13],"users":[14],"may":[15],"inject":[16],"fake":[17],"profiles":[18],"into":[19],"the":[20,43,66,76,91],"system":[21],"alter":[23],"recommendation":[24],"outputs.":[25],"Current":[26],"attack":[28],"detection":[29,62],"methods":[30,82],"mostly":[32],"based":[33],"on":[34,68,90],"feature":[35],"extraction":[36],"techniques.":[37],"The":[38],"hand-designed":[39],"features":[40],"can":[41,111],"confine":[42],"model":[44],"specific":[46],"domains":[47],"or":[48],"datasets":[49,70],"while":[50],"deep":[51,80,108],"learning":[52,81,109],"techniques":[53],"enable":[54],"us":[55],"derive":[57],"deeper":[58],"level":[59],"features,":[60],"enhance":[61],"performance,":[63],"and":[64,71,94,102],"generalize":[65],"solution":[67],"various":[69],"domains.":[72],"This":[73],"paper":[74],"illustrates":[75],"application":[77],"of":[78,100,115],"two":[79],"detect":[84],"attacks.":[86],"We":[87],"conducted":[88],"experiments":[89],"MovieLens":[92],"100K":[93],"Netflix":[95],"Dataset":[96],"with":[97],"different":[98],"levels":[99],"types.":[103],"Experimental":[104],"results":[105],"show":[106],"that":[107],"models":[110],"achieve":[112],"an":[113],"accuracy":[114],"up":[116],"99%.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}