乐胖代购免代理版

{"id":"https://openalex.org/W4225125221","doi":"https://doi.org/10.48550/arxiv.2204.13172","title":"An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework","display_name":"An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4225125221","doi":"https://doi.org/10.48550/arxiv.2204.13172"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.13172","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2204.13172","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014302355","display_name":"Ehsan Nowroozi","orcid":"https://orcid.org/0000-0002-5714-8378"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nowroozi, Ehsan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728747","display_name":"Abhishek Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abhishek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091829885","display_name":"Mohammadreza Mohammadi","orcid":"https://orcid.org/0000-0002-8470-3277"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammadi, Mohammadreza","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063847107","display_name":"Mauro Conti","orcid":"https://orcid.org/0000-0002-3612-1934"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Conti, Mauro","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":59},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998,"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":0.9998,"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":0.9978,"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":0.9977,"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/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.5656432},{"id":"https://openalex.org/keywords/obfuscation","display_name":"Obfuscation","score":0.4637587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.84568334},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.5656432},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5430311},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5395673},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5245971},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.4637587},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.45707378},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43615597},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43329686},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4210387},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.41951603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41140968},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2961173},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.13172","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.13172","pdf_url":"http://arxiv.org/pdf/2204.13172","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2204.13172","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.13172","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4384648009","https://openalex.org/W4383468834","https://openalex.org/W4287851288","https://openalex.org/W4287828318","https://openalex.org/W4283221438","https://openalex.org/W3048732067","https://openalex.org/W2930249865","https://openalex.org/W2900159906","https://openalex.org/W2899811703","https://openalex.org/W2406556600"],"abstract_inverted_index":{"Malicious":[0],"advertisement":[1,44,110],"URLs":[2,111],"pose":[3],"a":[4,56,91,187,204],"security":[5],"risk":[6],"since":[7],"they":[8],"are":[9,72],"the":[10,15,29,36,124,162,177,216,222,229,236,247],"source":[11],"of":[12,40,50,94,116,120,164,199,224],"cyber-attacks,":[13],"and":[14,26,52,63,74,96,99,144,154,174,239],"need":[16],"to":[17,35,55,59,64,75,83,104],"address":[18],"this":[19,87,158],"issue":[20],"is":[21],"growing":[22],"in":[23,126,176],"both":[24],"industry":[25],"academia.":[27],"Generally,":[28],"attacker":[30],"delivers":[31],"an":[32,41,43],"attack":[33,232,238,245],"vector":[34],"user":[37],"by":[38],"means":[39,49],"email,":[42],"link":[45],"or":[46],"any":[47],"other":[48],"communication":[51],"directs":[53],"them":[54],"malicious":[57,68],"website":[58],"steal":[60],"sensitive":[61],"information":[62],"defraud":[65],"them.":[66],"Existing":[67],"URL":[69,128],"detection":[70,178,248],"techniques":[71],"limited":[73,230],"handle":[76],"unseen":[77],"features":[78,98,121],"as":[79,81,191,193],"well":[80],"generalize":[82],"test":[84],"data.":[85],"In":[86],"study,":[88],"we":[89,135,160,184,202],"extract":[90],"novel":[92,205],"set":[93,105,115],"lexical":[95],"web-scrapped":[97],"employ":[100],"machine":[101,166],"learning":[102,167],"technique":[103,207],"up":[106],"system":[107],"for":[108,141,152,208,215],"fraudulent":[109,127],"detection.":[112],"The":[113],"combination":[114],"six":[117],"different":[118,132,138],"kinds":[119],"precisely":[122],"overcome":[123],"obfuscation":[125],"classification.":[129],"Based":[130],"on":[131,246],"statistical":[133],"properties,":[134],"use":[136],"twelve":[137],"formatted":[139],"datasets":[140],"detection,":[142],"prediction":[143,150],"classification":[145],"task.":[146],"We":[147,234],"extend":[148],"our":[149,181],"analysis":[151],"mismatched":[153],"unlabelled":[155],"datasets.":[156],"For":[157],"framework,":[159],"analyze":[161],"performance":[163],"four":[165],"techniques:":[168],"Random":[169],"Forest,":[170],"Gradient":[171],"Boost,":[172],"XGBoost":[173],"AdaBoost":[175],"part.":[179],"With":[180],"proposed":[182],"method,":[183],"can":[185],"achieve":[186],"false":[188],"negative":[189],"rate":[190],"low":[192],"0.0037":[194],"while":[195],"maintaining":[196],"high":[197],"accuracy":[198],"99.63%.":[200],"Moreover,":[201],"devise":[203],"unsupervised":[206],"data":[209],"clustering":[210],"using":[211,228],"K-":[212],"Means":[213],"algorithm":[214],"visual":[217],"analysis.":[218],"This":[219],"paper":[220],"analyses":[221],"vulnerability":[223],"decision":[225],"tree-based":[226],"models":[227],"knowledge":[231],"scenario.":[233],"considered":[235],"exploratory":[237],"implemented":[240],"Zeroth":[241],"Order":[242],"Optimization":[243],"adversarial":[244],"models.":[249]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4225125221","counts_by_year":[],"updated_date":"2025-03-24T09:26:29.915624","created_date":"2022-05-01"}