{"id":"https://openalex.org/W3209243600","doi":"https://doi.org/10.1109/itsc48978.2021.9564671","title":"Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models","display_name":"Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models","publication_year":2021,"publication_date":"2021-09-19","ids":{"openalex":"https://openalex.org/W3209243600","doi":"https://doi.org/10.1109/itsc48978.2021.9564671","mag":"3209243600"},"language":"en","primary_location":{"id":"doi:10.1109/itsc48978.2021.9564671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","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/A5054457856","display_name":"Bibek Poudel","orcid":null},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bibek Poudel","raw_affiliation_strings":["Department of Computer Science, University of Memphis, Memphis, TN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Memphis, Memphis, TN, USA","institution_ids":["https://openalex.org/I94658018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103113423","display_name":"Weizi Li","orcid":"https://orcid.org/0000-0002-0780-738X"},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weizi Li","raw_affiliation_strings":["Department of Computer Science, University of Memphis, Memphis, TN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Memphis, Memphis, TN, USA","institution_ids":["https://openalex.org/I94658018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054457856"],"corresponding_institution_ids":["https://openalex.org/I94658018"],"apc_list":null,"apc_paid":null,"fwci":0.3559,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.5921184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3652","last_page":"3658"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9940999746322632,"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":0.7568631172180176},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7130450010299683},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.7039546370506287},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.5151432752609253},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4233076274394989},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3991909623146057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23009666800498962},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12495163083076477}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7568631172180176},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7130450010299683},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.7039546370506287},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.5151432752609253},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4233076274394989},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3991909623146057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23009666800498962},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12495163083076477}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc48978.2021.9564671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W626441390","https://openalex.org/W1485459693","https://openalex.org/W1522301498","https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W1996851706","https://openalex.org/W2004353783","https://openalex.org/W2036785686","https://openalex.org/W2044725736","https://openalex.org/W2073640212","https://openalex.org/W2079662306","https://openalex.org/W2085592822","https://openalex.org/W2087854787","https://openalex.org/W2112536714","https://openalex.org/W2190353863","https://openalex.org/W2194775991","https://openalex.org/W2408141691","https://openalex.org/W2551393996","https://openalex.org/W2579495707","https://openalex.org/W2739457923","https://openalex.org/W2771027356","https://openalex.org/W2785681938","https://openalex.org/W2798302089","https://openalex.org/W2799816670","https://openalex.org/W2804811686","https://openalex.org/W2890655496","https://openalex.org/W2899771611","https://openalex.org/W2901504064","https://openalex.org/W2916286792","https://openalex.org/W2960571052","https://openalex.org/W2963207607","https://openalex.org/W2963358464","https://openalex.org/W2963389226","https://openalex.org/W2964121744","https://openalex.org/W2964153729","https://openalex.org/W2966922041","https://openalex.org/W2967400373","https://openalex.org/W2980922956","https://openalex.org/W2996451395","https://openalex.org/W3005888097","https://openalex.org/W3049596687","https://openalex.org/W3083490586","https://openalex.org/W3092539151","https://openalex.org/W3128196514","https://openalex.org/W3175292087","https://openalex.org/W3215849690","https://openalex.org/W3215871202","https://openalex.org/W4200297588","https://openalex.org/W6631190155","https://openalex.org/W6746015598","https://openalex.org/W6776120197","https://openalex.org/W6804429651"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W3009622996","https://openalex.org/W3037859390"],"abstract_inverted_index":{"Traffic":[0],"state":[1,23,145],"prediction":[2,42,83,110,170,198],"is":[3,28,48],"necessary":[4],"for":[5],"many":[6,55],"Intelligent":[7],"Transportation":[8],"Systems":[9],"applications.":[10],"Recent":[11],"developments":[12],"of":[13,24,44,92,146],"the":[14,25,41,68,82,93,105,109,120,136,141,147,163,167,212],"topic":[15],"have":[16],"focused":[17],"on":[18,135],"network-wide,":[19],"multi-step":[20],"prediction,":[21],"where":[22],"art":[26],"performance":[27],"achieved":[29],"via":[30],"deep":[31,45],"learning":[32,46],"models,":[33],"in":[34],"particular,":[35],"graph":[36,149],"neural":[37,150],"network-based":[38,151],"models.":[39],"While":[40,190],"accuracy":[43,171],"models":[47,152,181,193],"high,":[49],"these":[50,191],"models&#x0027;":[51],"robustness":[52],"has":[53],"raised":[54],"safety":[56],"concerns,":[57],"given":[58],"that":[59,104],"imperceptible":[60],"perturbations":[61],"added":[62],"to":[63,173,211],"input":[64,114],"can":[65,107,122,165],"substantially":[66],"degrade":[67,166],"model":[69,84,94,111,126],"performance.":[70],"In":[71,176],"this":[72],"work,":[73],"we":[74,102],"propose":[75],"an":[76],"adversarial":[77,132],"attack":[78,142],"framework":[79],"by":[80],"treating":[81],"as":[85],"a":[86,124,161],"black-box,":[87],"i.e.,":[88],"assuming":[89],"no":[90],"knowledge":[91],"architecture,":[95],"training":[96],"data,":[97],"and":[98,115,130,155,184],"(hyper)":[99],"parameters.":[100],"However,":[101],"assume":[103],"adversary":[106,121,164],"oracle":[108],"with":[112],"any":[113],"obtain":[116],"corresponding":[117],"output.":[118],"Next,":[119],"train":[123],"substitute":[125,137],"using":[127],"input-output":[128],"pairs":[129],"generate":[131],"signals":[133],"based":[134],"model.":[138],"To":[139],"test":[140],"effectiveness,":[143],"two":[144,178,192],"art,":[148],"(GCGRNN":[153],"[1]":[154],"DCRNN":[156],"[2])":[157],"are":[158,187,201,209],"examined.":[159,189],"As":[160],"result,":[162],"target":[168],"model&#x0027;s":[169],"up":[172],"54":[174],"&#x0025;.":[175],"comparison,":[177],"conventional":[179],"statistical":[180],"(linear":[182],"regression":[183],"historical":[185],"average)":[186],"also":[188],"do":[194],"not":[195],"produce":[196],"high":[197],"accuracy,":[199],"they":[200],"either":[202],"influenced":[203],"negligibly":[204],"(less":[205],"than":[206],"3&#x0025;)":[207],"or":[208],"immune":[210],"adversary&#x0027;s":[213],"attack.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
