{"id":"https://openalex.org/W4291907972","doi":"https://doi.org/10.1109/icccs55155.2022.9846237","title":"A Practical Website Fingerprinting Defense Approach with Universal Adversarial Perturbations","display_name":"A Practical Website Fingerprinting Defense Approach with Universal Adversarial Perturbations","publication_year":2022,"publication_date":"2022-04-22","ids":{"openalex":"https://openalex.org/W4291907972","doi":"https://doi.org/10.1109/icccs55155.2022.9846237"},"language":"en","primary_location":{"id":"doi:10.1109/icccs55155.2022.9846237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846237","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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/A5001002772","display_name":"Boyu Sun","orcid":"https://orcid.org/0000-0001-8638-6159"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Boyu Sun","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China","School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101619232","display_name":"Wenyuan Yang","orcid":"https://orcid.org/0000-0003-0046-5994"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyuan Yang","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China","School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000634144","display_name":"Mengqi Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengqi Yan","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China","School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China","School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016849571","display_name":"Zhiqiang Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Bai","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China","School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001002772"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.3122,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50002694,"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":"752","last_page":"760"},"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":0.9993000030517578,"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":0.9993000030517578,"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":0.9977999925613403,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8687258958816528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7905279397964478},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7079927325248718},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.6333382725715637},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.6009254455566406},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5388201475143433},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4399245083332062},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.39523038268089294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3663637042045593},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32960769534111023},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.20794403553009033}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8687258958816528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7905279397964478},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7079927325248718},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6333382725715637},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.6009254455566406},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5388201475143433},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4399245083332062},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.39523038268089294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3663637042045593},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32960769534111023},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.20794403553009033},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccs55155.2022.9846237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846237","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320330944","display_name":"Nature","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1932198206","https://openalex.org/W2012210084","https://openalex.org/W2027177092","https://openalex.org/W2108217512","https://openalex.org/W2135579486","https://openalex.org/W2149280729","https://openalex.org/W2170085959","https://openalex.org/W2180612164","https://openalex.org/W2272516773","https://openalex.org/W2408141691","https://openalex.org/W2485000773","https://openalex.org/W2543927648","https://openalex.org/W2557890466","https://openalex.org/W2752949934","https://openalex.org/W2783301790","https://openalex.org/W2896133229","https://openalex.org/W2901645129","https://openalex.org/W2963115223","https://openalex.org/W2963165363","https://openalex.org/W2963448658","https://openalex.org/W2963560523","https://openalex.org/W2963704216","https://openalex.org/W2963857521","https://openalex.org/W2964602598","https://openalex.org/W2969841870","https://openalex.org/W2997502936","https://openalex.org/W3015990833","https://openalex.org/W3019195326","https://openalex.org/W3047194494","https://openalex.org/W3049399107","https://openalex.org/W3084424094","https://openalex.org/W3089115757","https://openalex.org/W3093946892","https://openalex.org/W3094227091","https://openalex.org/W3103367901","https://openalex.org/W3106813043","https://openalex.org/W3107803931","https://openalex.org/W3122216659","https://openalex.org/W3134441556","https://openalex.org/W3193903060","https://openalex.org/W4294065829","https://openalex.org/W4295312788","https://openalex.org/W4320013936","https://openalex.org/W6682188453","https://openalex.org/W6693724512","https://openalex.org/W6714069269","https://openalex.org/W6730169306","https://openalex.org/W6744119509","https://openalex.org/W6766978945","https://openalex.org/W6781761031"],"related_works":["https://openalex.org/W4313479464","https://openalex.org/W3024390022","https://openalex.org/W3156291593","https://openalex.org/W4367722749","https://openalex.org/W4229008806","https://openalex.org/W4205705013","https://openalex.org/W3198184493","https://openalex.org/W3214552351","https://openalex.org/W4287116584","https://openalex.org/W3174891612"],"abstract_inverted_index":{"Website":[0],"Fingerprinting":[1],"(WF)":[2],"can":[3,128],"be":[4],"used":[5,92],"by":[6,70],"network":[7,41,102],"eavesdroppers":[8],"to":[9,25,35,45,76,88,100,121,149,171],"infer":[10],"information":[11],"about":[12],"the":[13,27,90,106,123,133,139,162,165,182,188],"content":[14],"of":[15,29,125,164,187],"encrypted":[16],"and":[17,137,142,191],"anonymous":[18],"connections.":[19],"Several":[20],"defenses":[21,184],"leverage":[22],"adversarial":[23,47,84,140],"examples":[24,85],"mitigate":[26],"threat":[28],"WF":[30,63,80,94,167],"attacks,":[31,81],"but":[32],"they":[33],"require":[34],"get":[36],"entire":[37],"traffic":[38,103,144],"traces":[39,141,145],"after":[40],"sessions":[42],"have":[43],"concluded":[44],"produce":[46],"examples,":[48],"thus":[49],"offer":[50],"users":[51],"little":[52],"protection":[53],"in":[54,82,93,105,185],"practical":[55,62],"settings.":[56],"In":[57],"this":[58],"paper,":[59],"a":[60,112,155],"novel":[61],"defense":[64,189],"method":[65],"called":[66],"WF-UAP":[67,160],"is":[68,135],"proposed":[69],"crafting":[71],"Universal":[72],"Adversarial":[73,114],"Perturbations":[74],"(UAP)":[75],"fight":[77],"back":[78],"against":[79],"which":[83,180],"are":[86,98,146],"produced":[87],"fool":[89],"classifiers":[91],"attacks":[95,168],"when":[96],"UAPs":[97,131],"added":[99],"any":[101],"trace":[104],"target":[107],"domain.":[108],"We":[109],"further":[110],"present":[111],"Generative":[113],"Network":[115],"(GAN)":[116],"based":[117],"UAP":[118],"generation":[119],"approach":[120],"enhance":[122],"performance":[124,190],"UAPs.":[126],"It":[127],"efficiently":[129],"generate":[130],"once":[132],"generator":[134],"trained":[136],"make":[138],"original":[143],"more":[147],"difficult":[148],"distinguish.":[150],"Our":[151],"experimental":[152],"results":[153],"over":[154],"public":[156],"dataset":[157],"demonstrate":[158],"that":[159],"reduces":[161],"accuracy":[163],"state-of-the-art":[166],"from":[169],"98%":[170],"15%":[172],"with":[173],"at":[174],"most":[175],"20%":[176],"increased":[177],"bandwidth":[178],"overhead,":[179],"outperforms":[181],"previous":[183],"terms":[186],"overhead.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}