{"id":"https://openalex.org/W2782626253","doi":"https://doi.org/10.1145/3145511.3145514","title":"Fraud Detection via Coding Nominal Attributes","display_name":"Fraud Detection via Coding Nominal Attributes","publication_year":2017,"publication_date":"2017-08-13","ids":{"openalex":"https://openalex.org/W2782626253","doi":"https://doi.org/10.1145/3145511.3145514","mag":"2782626253"},"language":"en","primary_location":{"id":"doi:10.1145/3145511.3145514","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3145511.3145514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 2nd International Conference on Multimedia Systems and Signal Processing","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/A5115602505","display_name":"Jianyu Wang","orcid":"https://orcid.org/0000-0002-1668-5329"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang Jianyu","raw_affiliation_strings":["Zhejiang University, college of computer science"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, college of computer science","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078198240","display_name":"Chunming Wu","orcid":"https://orcid.org/0000-0001-7958-9687"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Chunming","raw_affiliation_strings":["Zhejiang University, college of computer science"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, college of computer science","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058611515","display_name":"Shouling Ji","orcid":"https://orcid.org/0000-0003-4268-372X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Shouling","raw_affiliation_strings":["Zhejiang University, college of computer science"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, college of computer science","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022933234","display_name":"Gu Qinchen","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gu Qinchen","raw_affiliation_strings":["Georgia Tech"],"affiliations":[{"raw_affiliation_string":"Georgia Tech","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032277491","display_name":"Zhao Li","orcid":"https://orcid.org/0000-0002-5056-0351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Zhao","raw_affiliation_strings":["Alibaba Company"],"affiliations":[{"raw_affiliation_string":"Alibaba Company","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5115602505"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.9673,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8405658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"42","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":1.0,"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/T11644","display_name":"Spam and Phishing Detection","score":1.0,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8562740087509155},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6039710640907288},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.50356525182724},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4552712142467499},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4376251697540283},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42783719301223755},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4275108575820923},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4110095202922821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.384403795003891}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8562740087509155},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6039710640907288},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.50356525182724},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4552712142467499},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4376251697540283},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42783719301223755},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4275108575820923},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4110095202922821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.384403795003891},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"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:10.1145/3145511.3145514","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3145511.3145514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 2nd International Conference on Multimedia Systems and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W91931328","https://openalex.org/W1420268584","https://openalex.org/W1835342030","https://openalex.org/W1985683032","https://openalex.org/W2021375049","https://openalex.org/W2025827699","https://openalex.org/W2174868984","https://openalex.org/W2317606158","https://openalex.org/W2964082701","https://openalex.org/W6699692158"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W2256933480","https://openalex.org/W2027854990","https://openalex.org/W2370081953","https://openalex.org/W2364428742","https://openalex.org/W3081644756"],"abstract_inverted_index":{"Research":[0],"on":[1,6,64,124],"advertisement":[2],"has":[3],"mainly":[4],"focused":[5],"how":[7,145],"to":[8,57,80,117,146],"accurately":[9],"predict":[10],"the":[11,54,59,88,93,129,138,159,163],"click-through":[12],"rate":[13],"(CTR).":[14],"Much":[15],"less":[16],"is":[17],"known":[18],"about":[19],"fraud":[20,41,97,119,131],"detection":[21,132],"and":[22,33,44,107,112,140],"malicious":[23,62],"behavior":[24,42],"defense.":[25],"Previous":[26],"studies":[27],"usually":[28],"use":[29],"statistics,":[30],"design":[31,147],"threshold":[32],"manually":[34],"make":[35,53],"strategies,":[36],"which":[37,153],"cannot":[38],"find":[39],"potential":[40],"effectively":[43],"suffer":[45],"from":[46],"new":[47],"attacks.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52,74,100,143],"first":[55],"step":[56],"understand":[58],"type":[60],"of":[61,92],"activities":[63],"large-scale":[65],"online":[66],"advertising":[67],"platforms.":[68],"By":[69],"analyzing":[70],"each":[71],"feature":[72],"comprehensively,":[73],"propose":[75],"a":[76,148],"novel":[77],"coding":[78],"approach":[79],"transform":[81],"nominal":[82],"attributes":[83],"into":[84],"numeric":[85],"while":[86],"maintaining":[87],"most":[89],"effective":[90],"information":[91],"original":[94],"data":[95],"for":[96,158],"detection.":[98],"Next,":[99],"code":[101],"important":[102],"features":[103],"such":[104],"as":[105],"IP":[106],"cookie":[108],"in":[109,162],"our":[110],"dataset":[111],"train":[113],"machine":[114],"learning":[115],"methods":[116,154],"detect":[118],"traffic":[120],"automatically.":[121],"Experimental":[122],"results":[123],"real":[125],"datasets":[126],"demonstrate":[127],"that":[128],"proposed":[130],"method":[133],"performs":[134],"well":[135],"considering":[136,152],"both":[137],"accuracy":[139],"efficiency.":[141],"Finally,":[142],"conclude":[144],"defense":[149],"system":[150],"by":[151],"could":[155],"be":[156],"used":[157],"anti-spam":[160],"gaming":[161],"future.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}