{"id":"https://openalex.org/W4394913648","doi":"https://doi.org/10.1145/3638782.3638788","title":"Webshell Detection Based On CodeBERT And Deep Learning","display_name":"Webshell Detection Based On CodeBERT And Deep Learning","publication_year":2023,"publication_date":"2023-12-06","ids":{"openalex":"https://openalex.org/W4394913648","doi":"https://doi.org/10.1145/3638782.3638788"},"language":"en","primary_location":{"id":"doi:10.1145/3638782.3638788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638782.3638788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 13th International Conference on Communication and Network Security","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/A5063576791","display_name":"L. Liu","orcid":"https://orcid.org/0000-0003-3500-7790"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lei Liu","raw_affiliation_strings":["Beijing Rising Network Security Technology Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Beijing Rising Network Security Technology Co., Ltd., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102796868","display_name":"Ziyou He","orcid":"https://orcid.org/0009-0002-4130-2999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziyou He","raw_affiliation_strings":["Beijing Rising Network Security Technology Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Beijing Rising Network Security Technology Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063576791"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4589,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74753712,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"32","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9987000226974487,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9987000226974487,"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":0.9850000143051147,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9718999862670898,"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":0.6392646431922913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.539293646812439},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48349812626838684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6392646431922913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.539293646812439},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48349812626838684}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3638782.3638788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638782.3638788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 13th International Conference on Communication and Network Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2336291507","https://openalex.org/W2605575598","https://openalex.org/W2901745180","https://openalex.org/W4230419068","https://openalex.org/W4241566028"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Protection":[0],"against":[1],"Webshell":[2,22,42,52,135],"attacks":[3],"is":[4,64,76,84,93,114],"an":[5],"important":[6],"issue":[7],"in":[8,41,111,128],"the":[9,62,73,82,90,103,106,117,125],"field":[10],"of":[11,105],"network":[12],"security.":[13],"Attackers":[14],"often":[15],"design":[16],"various":[17],"anti-virus":[18],"techniques":[19],"when":[20],"writing":[21],"to":[23,101],"bypass":[24],"firewalls":[25],"and":[26,37,58,66,81,97,137],"evade":[27],"detection.":[28,43],"Therefore,":[29],"existing":[30],"methods":[31],"have":[32],"problems":[33],"with":[34,116],"low":[35],"accuracy":[36],"high":[38],"false":[39,139],"positives":[40],"To":[44],"address":[45],"these":[46],"issues,":[47],"this":[48,112,129],"paper":[49,113,130],"proposes":[50],"a":[51],"detection":[53,104,136],"method":[54,109,126],"based":[55],"on":[56],"CodeBERT":[57,79],"deep":[59],"learning.":[60],"Firstly,":[61],"sample":[63,75,83],"analyzed":[65],"preprocessed":[67,74],"by":[68,78],"Antlr4":[69],"syntax":[70],"analysis.":[71],"Then,":[72],"encoded":[77],"model,":[80],"converted":[85],"into":[86],"feature":[87],"vector.":[88],"Finally,":[89],"BiGRU-Attention":[91],"model":[92],"used":[94,110],"for":[95,134],"training":[96],"classification,":[98],"so":[99],"as":[100],"complete":[102],"sample.":[107],"The":[108,120],"compared":[115],"mainstream":[118],"method.":[119],"experimental":[121],"results":[122],"show":[123],"that":[124],"proposed":[127],"has":[131],"better":[132],"effect":[133],"lower":[138],"positive":[140],"rate.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
