{"id":"https://openalex.org/W4406461149","doi":"https://doi.org/10.1109/bigdata62323.2024.10826115","title":"Detecting Fraud in a Large Anonymized Voter Registration Dataset","display_name":"Detecting Fraud in a Large Anonymized Voter Registration Dataset","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461149","doi":"https://doi.org/10.1109/bigdata62323.2024.10826115"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10826115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5027527322","display_name":"Norizan Anwar","orcid":"https://orcid.org/0000-0003-1104-1724"},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nahid Anwar","raw_affiliation_strings":["Boise State University,Computer Science,Boise,Idaho,USA"],"affiliations":[{"raw_affiliation_string":"Boise State University,Computer Science,Boise,Idaho,USA","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109127361","display_name":"Amit Jain","orcid":"https://orcid.org/0000-0003-2022-9104"},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Jain","raw_affiliation_strings":["Boise State University,Computer Science,Boise,Idaho,USA"],"affiliations":[{"raw_affiliation_string":"Boise State University,Computer Science,Boise,Idaho,USA","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009094578","display_name":"Edoardo Serra","orcid":"https://orcid.org/0000-0003-0689-5063"},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edoardo Serra","raw_affiliation_strings":["Boise State University,Computer Science,Boise,Idaho,USA"],"affiliations":[{"raw_affiliation_string":"Boise State University,Computer Science,Boise,Idaho,USA","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001041113","display_name":"Chad Houck","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150572","display_name":"Idaho State Department of Agriculture","ror":"https://ror.org/03t6zfb73","country_code":"US","type":"government","lineage":["https://openalex.org/I4210150572"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chad Houck","raw_affiliation_strings":["Former Idaho Chief Deputy Secretary of State,Boise,Idaho,USA"],"affiliations":[{"raw_affiliation_string":"Former Idaho Chief Deputy Secretary of State,Boise,Idaho,USA","institution_ids":["https://openalex.org/I4210150572"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027527322"],"corresponding_institution_ids":["https://openalex.org/I120156002"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23811369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2275","last_page":"2282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9980000257492065,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9980000257492065,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.984000027179718,"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/T13720","display_name":"Benford\u2019s Law and Fraud Detection","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6512851119041443},{"id":"https://openalex.org/keywords/voter-registration","display_name":"Voter registration","score":0.46761903166770935},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.37643373012542725},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.09147793054580688},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.07906824350357056},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.07825571298599243}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6512851119041443},{"id":"https://openalex.org/C2780030507","wikidata":"https://www.wikidata.org/wiki/Q1980404","display_name":"Voter registration","level":4,"score":0.46761903166770935},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.37643373012542725},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.09147793054580688},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.07906824350357056},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.07825571298599243},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10826115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W3093492988","https://openalex.org/W3094451405","https://openalex.org/W3124364749","https://openalex.org/W3197264344","https://openalex.org/W4287123803","https://openalex.org/W4360994592","https://openalex.org/W4365505842","https://openalex.org/W4387846225","https://openalex.org/W4387848818","https://openalex.org/W4387854274","https://openalex.org/W4399597252","https://openalex.org/W6790079454","https://openalex.org/W6796801894","https://openalex.org/W6870115499"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2514425666","https://openalex.org/W1498590566","https://openalex.org/W3125358347","https://openalex.org/W2805287516","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433"],"abstract_inverted_index":{"Voter":[0,41,95],"registration":[1,27,42,76,128,157,276],"in":[2,154,261,288],"the":[3,21,37,48,51,93,109,172,186,205,221,242,265,272],"United":[4,52],"States":[5,53],"involves":[6],"maintaining":[7],"state-controlled":[8],"lists":[9],"that":[10,278],"record":[11],"all":[12,280],"legally":[13],"eligible":[14],"voters.":[15],"Election":[16,97],"fraud":[17,129],"often":[18],"centers":[19],"around":[20],"manipulation":[22],"and":[23,70,114,132,198,247],"misuse":[24],"of":[25,47,50,104,112,118,126,188,193,207,223,244,267],"voter":[26,75,106,127,156,225,275],"data,":[28,43],"potentially":[29],"allowing":[30],"ineligible":[31],"votes":[32],"or":[33],"denying":[34],"legitimate":[35],"voters":[36],"right":[38],"to":[39,56,82,134,140,228,251,258,293],"participate.":[40],"therefore,":[44],"is":[45,271],"part":[46],"backbone":[49],"democratic":[54],"system":[55],"ensure":[57],"election":[58,253,263,289],"integrity.":[59],"In":[60],"today\u2019s":[61],"dynamic":[62],"political":[63],"landscape,":[64],"sharing":[65],"this":[66,89,270],"data":[67,107,158],"promotes":[68],"transparency":[69],"accountability.":[71],"However,":[72],"accessing":[73],"real":[74,105,124],"records":[77,103,226],"can":[78],"be":[79,141,160],"challenging":[80],"due":[81],"privacy":[83],"concerns":[84],"about":[85],"personally":[86],"identifiable":[87],"information.In":[88],"paper,":[90],"we":[91,149,162],"present":[92],"Idaho":[94,110],"Registration":[96],"Dataset":[98],"(IVRED),":[99],"which":[100,155,255],"contains":[101],"anonymized":[102,183],"from":[108],"Secretary":[111],"State":[113],"a":[115,164,189],"curated":[116],"set":[117],"synthetically":[119],"generated":[120],"fraudulent":[121,224],"records.":[122],"Although":[123],"instances":[125],"are":[130,138],"rare":[131],"difficult":[133],"identify,":[135],"potential":[136,250],"vulnerabilities":[137],"yet":[139],"thoroughly":[142],"explored.":[143],"By":[144],"consulting":[145],"with":[146,181,236],"domain":[147],"experts,":[148],"have":[150],"identified":[151],"various":[152],"scenarios":[153],"could":[159],"manipulated.Additionally,":[161],"provide":[163],"similarity":[165,179],"graph":[166,214],"for":[167,204],"each":[168],"significant":[169],"attribute,":[170],"illustrating":[171],"inter-relationships":[173],"between":[174],"attribute":[175],"values.":[176],"Combining":[177],"these":[178],"graphs":[180],"our":[182,245,262,268],"dataset":[184,246,277],"enables":[185],"construction":[187],"comprehensive":[190],"graph,":[191],"consisting":[192],"over":[194],"2.1":[195],"million":[196,200],"nodes":[197],"22":[199],"edges.":[201],"This":[202,240,282],"allows":[203],"application":[206],"advanced":[208],"machine":[209,230,299],"learning":[210,231,300],"techniques,":[211],"including":[212],"spectral":[213],"positioning\u2014also":[215],"known":[216],"as":[217],"positional":[218],"embedding\u2014which":[219],"improves":[220],"classification":[222,234],"compared":[227],"baseline":[229],"experiments":[232],"(a":[233],"model":[235],"no":[237],"embedding":[238],"features).":[239],"demonstrates":[241],"utility":[243],"highlights":[248],"its":[249],"detect":[252],"fraud,":[254],"will":[256,284],"lead":[257],"increased":[259],"confidence":[260],"process.To":[264],"best":[266],"knowledge,":[269],"first":[273],"released":[274],"includes":[279],"fields.":[281],"resource":[283],"hopefully":[285],"stimulate":[286],"research":[287],"security,":[290],"enabling":[291],"researchers":[292],"develop":[294],"new":[295],"analytical":[296],"tools":[297],"using":[298],"techniques.":[301]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}