{"id":"https://openalex.org/W4413385704","doi":"https://doi.org/10.29007/s3f6","title":"A Lightweight and Accurate Classification Framework for Traffic Log Analysis Based on an Effective Feature Representation Method","display_name":"A Lightweight and Accurate Classification Framework for Traffic Log Analysis Based on an Effective Feature Representation Method","publication_year":2025,"publication_date":"2025-08-21","ids":{"openalex":"https://openalex.org/W4413385704","doi":"https://doi.org/10.29007/s3f6"},"language":"en","primary_location":{"id":"doi:10.29007/s3f6","is_oa":true,"landing_page_url":"https://doi.org/10.29007/s3f6","pdf_url":"https://easychair.org/publications/paper/zZlP/download","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://easychair.org/publications/paper/zZlP/download","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017439242","display_name":"Ayako Sasaki","orcid":"https://orcid.org/0000-0002-9261-2359"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ayako Sasaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029032117","display_name":"Takeshi Takahashi","orcid":"https://orcid.org/0000-0002-6477-7770"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takeshi Takahashi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078486804","display_name":"Keisuke Furumoto","orcid":"https://orcid.org/0000-0002-0699-5884"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keisuke Furumoto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014245712","display_name":"Chun\u2010I Fan","orcid":"https://orcid.org/0000-0002-7512-1291"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chun-I Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101610047","display_name":"Tomohiro Morikawa","orcid":"https://orcid.org/0000-0002-7822-3672"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomohiro Morikawa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017439242"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20901298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"106","issue":null,"first_page":"210","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9704999923706055,"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":0.9704999923706055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7200173139572144},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6407142281532288},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6382907032966614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5324788093566895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4543648362159729},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4508993327617645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4216383397579193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7200173139572144},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6407142281532288},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6382907032966614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5324788093566895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4543648362159729},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4508993327617645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4216383397579193},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.29007/s3f6","is_oa":true,"landing_page_url":"https://doi.org/10.29007/s3f6","pdf_url":"https://easychair.org/publications/paper/zZlP/download","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.29007/s3f6","is_oa":true,"landing_page_url":"https://doi.org/10.29007/s3f6","pdf_url":"https://easychair.org/publications/paper/zZlP/download","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413385704.pdf","grobid_xml":"https://content.openalex.org/works/W4413385704.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278","https://openalex.org/W2886173746","https://openalex.org/W4200043248"],"abstract_inverted_index":{"As":[0],"cyberattacks":[1],"become":[2,31],"increasingly":[3],"sophisticated,":[4],"organizations":[5],"face":[6],"an":[7],"urgent":[8],"need":[9],"for":[10,33,95,134],"timely":[11],"and":[12,37,68,79,90,128],"accurate":[13,91],"incident":[14],"response":[15],"to":[16,47,75],"reduce":[17],"their":[18],"impact":[19],"on":[20,58,119],"critical":[21],"systems.":[22],"Automating":[23],"the":[24,96],"analysis":[25,98,132],"of":[26,64,99],"network":[27,100],"traffic":[28,101,130],"logs":[29],"has":[30],"essential":[32],"supporting":[34],"security":[35],"analysts":[36],"specialists.":[38],"Although":[39],"many":[40],"previous":[41],"studies":[42],"have":[43],"applied":[44],"machine":[45,65,92],"learning":[46,66],"address":[48],"this":[49],"task,":[50],"they":[51],"often":[52],"encounter":[53],"challenges":[54],"such":[55],"as":[56],"dependence":[57],"large-scale":[59],"analytics":[60],"platforms,":[61],"limited":[62],"exploration":[63],"algorithms,":[67],"difficulties":[69],"in":[70],"deploying":[71],"distributed":[72],"systems":[73],"due":[74],"high":[76],"costs,":[77],"complexity,":[78],"privacy":[80],"concerns.":[81],"To":[82],"tackle":[83],"these":[84],"limitations,":[85],"we":[86],"propose":[87],"a":[88,112],"lightweight":[89],"learning-based":[93],"framework":[94],"automatic":[97],"logs.":[102],"Our":[103],"approach":[104],"transforms":[105],"log":[106,131],"data":[107],"into":[108],"feature":[109,114],"vectors":[110],"using":[111],"document-based":[113],"representation":[115],"method.":[116],"Experimental":[117],"results":[118],"benchmark":[120],"datasets":[121],"demonstrate":[122],"that":[123],"our":[124],"method":[125],"enables":[126],"efficient":[127],"effective":[129],"suitable":[133],"practical":[135],"deployment.":[136]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}