{"id":"https://openalex.org/W4388430301","doi":"https://doi.org/10.1109/access.2023.3330208","title":"GPU-Accelerated Deep Learning-Based Correlation Attack on Tor Networks","display_name":"GPU-Accelerated Deep Learning-Based Correlation Attack on Tor Networks","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388430301","doi":"https://doi.org/10.1109/access.2023.3330208"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3330208","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3330208","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10309127.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10309127.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081419126","display_name":"Muhammad Asfand Hafeez","orcid":"https://orcid.org/0000-0002-8881-8231"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Muhammad Asfand Hafeez","raw_affiliation_strings":["Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647847","display_name":"Yasir Ali","orcid":"https://orcid.org/0009-0005-1791-388X"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yasir Ali","raw_affiliation_strings":["Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0009-0005-1791-388X","affiliations":[{"raw_affiliation_string":"Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016402299","display_name":"KyungHyun Han","orcid":"https://orcid.org/0000-0002-7987-0441"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyung Hyun Han","raw_affiliation_strings":["Department of Computer Engineering, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-7987-0441","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086844518","display_name":"Seong Oun Hwang","orcid":"https://orcid.org/0000-0003-4240-6255"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong Oun Hwang","raw_affiliation_strings":["Department of Computer Engineering, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4240-6255","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I12832649"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.3226,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66060394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"11","issue":null,"first_page":"124139","last_page":"124149"},"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":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9962999820709229,"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/computer-science","display_name":"Computer science","score":0.7968481779098511},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6226462125778198},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5189926028251648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.513046383857727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33185434341430664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7968481779098511},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6226462125778198},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5189926028251648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.513046383857727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33185434341430664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3330208","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3330208","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10309127.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:11717a979ce042c9a5e9bc874b3148b6","is_oa":true,"landing_page_url":"https://doaj.org/article/11717a979ce042c9a5e9bc874b3148b6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 124139-124149 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3330208","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3330208","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10309127.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8763694050","display_name":null,"funder_award_id":"UI220040XD","funder_id":"https://openalex.org/F4320323103","funder_display_name":"Agency for Defense Development"}],"funders":[{"id":"https://openalex.org/F4320323103","display_name":"Agency for Defense Development","ror":"https://ror.org/05fhe0r85"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388430301.pdf","grobid_xml":"https://content.openalex.org/works/W4388430301.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W138886706","https://openalex.org/W1587894427","https://openalex.org/W1590765731","https://openalex.org/W1593719721","https://openalex.org/W1655958391","https://openalex.org/W1869319442","https://openalex.org/W1993568446","https://openalex.org/W2031925412","https://openalex.org/W2048142551","https://openalex.org/W2146096861","https://openalex.org/W2150248082","https://openalex.org/W2156410527","https://openalex.org/W2478767595","https://openalex.org/W2574779184","https://openalex.org/W2602462840","https://openalex.org/W2888125116","https://openalex.org/W2889117834","https://openalex.org/W2932175062","https://openalex.org/W2982542479","https://openalex.org/W3010954760","https://openalex.org/W3025003062","https://openalex.org/W3037647661","https://openalex.org/W3089115757","https://openalex.org/W3104102522","https://openalex.org/W4205940254","https://openalex.org/W4281945976","https://openalex.org/W4288057717","https://openalex.org/W6668254450","https://openalex.org/W6676104933","https://openalex.org/W6767623935"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W4387369504","https://openalex.org/W3046775127"],"abstract_inverted_index":{"The":[0,101],"Tor":[1,63,110],"network,":[2],"renowned":[3],"for":[4,66],"its":[5,81],"provision":[6],"of":[7,16,71,98,105,127,173,186],"online":[8],"privacy":[9],"and":[10,94,115,129,147,203],"anonymity,":[11],"faces":[12],"the":[13,68,99,122,171,177,184,223,228],"constant":[14],"threat":[15],"correlation":[17,30,43,60,76,88,107,145,197],"attacks":[18,31,44,61,73],"that":[19],"aim":[20],"to":[21,48,56,154,161,207,230],"compromise":[22],"user":[23],"identities.":[24],"For":[25,119],"almost":[26],"two":[27,191],"decades,":[28],"these":[29,190],"were":[32],"based":[33],"on":[34,62,109,168],"statistical":[35],"methods.":[36,163,209],"However,":[37],"in":[38,54,79,87,176],"recent":[39],"years,":[40],"deep":[41],"learning-based":[42],"have":[45],"been":[46],"introduced":[47,194],"make":[49],"them":[50],"more":[51],"accurate.":[52],"Nevertheless,":[53],"addition":[55],"being":[57],"accurate,":[58],"fast":[59,149,204],"are":[64],"crucial":[65],"assessing":[67],"real-world":[69],"viability":[70],"such":[72],"because":[74],"reduced":[75],"time":[77,89,156],"aids":[78],"estimating":[80],"practical":[82,96],"implications.":[83],"Moreover,":[84,210],"a":[85,106,142,148],"reduction":[86],"also":[90],"helps":[91],"improve":[92],"efficiency":[93],"ensures":[95],"relevance":[97],"attack.":[100],"existing":[102,162],"state-of-the-art":[103,208],"implementation":[104],"attack":[108],"suffers":[111],"from":[112],"slow":[113],"performance":[114,205],"large":[116],"memory":[117,218],"requirements.":[118],"instance,":[120],"training":[121,224],"model":[123,229],"required":[124],"133":[125],"GB":[126],"memory,":[128],"correlating":[130],"10,000":[131],"flows":[132],"takes":[133],"about":[134],"976":[135],"seconds.":[136],"In":[137],"this":[138],"paper,":[139],"we":[140,193,211],"present":[141],"novel":[143],"GPU-based":[144],"strategy":[146],"traffic":[150],"flow":[151],"loading":[152],"technique":[153],"reduce":[155],"complexity":[157],"by":[158,216,220],"7.12\u00d7":[159],"compared":[160,206],"Our":[164],"computational":[165],"approach,":[166],"reliant":[167],"PyCUDA,":[169],"facilitates":[170],"parallelization":[172],"operations":[174],"used":[175],"attack,":[178,198],"thereby":[179],"enabling":[180],"efficient":[181],"execution":[182],"through":[183],"utilization":[185],"GPU":[187],"architecture.":[188],"Leveraging":[189],"approaches,":[192],"an":[195],"improved":[196],"which":[199,226],"shows":[200],"high":[201],"accuracy":[202],"address":[212],"resource":[213],"limitation":[214],"issues":[215],"reducing":[217],"consumption":[219],"47.37%":[221],"during":[222],"phase,":[225],"allows":[227],"be":[231],"trained":[232],"with":[233],"much":[234],"fewer":[235],"resources.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
