{"id":"https://openalex.org/W7147070294","doi":"https://doi.org/10.1109/cnml68938.2026.11453068","title":"Source Code Vulnerability Detection Technology Based on Code Semantic Contribution","display_name":"Source Code Vulnerability Detection Technology Based on Code Semantic Contribution","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147070294","doi":"https://doi.org/10.1109/cnml68938.2026.11453068"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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/A5100697900","display_name":"Chunling Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunling Liu","raw_affiliation_strings":["Information Engineering University,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University,Zhengzhou,China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132638144","display_name":"Yonghe Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghe Tang","raw_affiliation_strings":["Information Engineering University,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University,Zhengzhou,China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100627435","display_name":"Jian Lin","orcid":"https://orcid.org/0000-0003-3379-9173"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Lin","raw_affiliation_strings":["Information Engineering University,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University,Zhengzhou,China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132582983","display_name":"Le Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134540","display_name":"China Ocean Shipping (China)","ror":"https://ror.org/044gm0487","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134540"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Liu","raw_affiliation_strings":["SIPPR Engineering Group Co., Ltd.,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"SIPPR Engineering Group Co., Ltd.,Zhengzhou,China","institution_ids":["https://openalex.org/I4210134540"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100697900"],"corresponding_institution_ids":["https://openalex.org/I169689159"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93042213,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"371","last_page":"376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.3174000084400177,"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"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.3174000084400177,"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/T10260","display_name":"Software Engineering Research","score":0.05550000071525574,"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.0478999987244606,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/dependency-graph","display_name":"Dependency graph","score":0.7141000032424927},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.6101999878883362},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5031999945640564},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.46459999680519104},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4643000066280365},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4368000030517578},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4316999912261963},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41200000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7967000007629395},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.7141000032424927},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.6101999878883362},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5031999945640564},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4966000020503998},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4643000066280365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.453000009059906},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4368000030517578},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.40700000524520874},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C102379954","wikidata":"https://www.wikidata.org/wiki/Q2589940","display_name":"Call graph","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30469998717308044},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2634106992","https://openalex.org/W2779307146","https://openalex.org/W2885030880","https://openalex.org/W3091588759","https://openalex.org/W3166095789","https://openalex.org/W4284667406","https://openalex.org/W4312436517","https://openalex.org/W4313563607","https://openalex.org/W4388754067"],"related_works":[],"abstract_inverted_index":{"This":[0,198],"research":[1,22],"is":[2,211],"dedicated":[3],"to":[4,16,69,213],"developing":[5],"source":[6,24,206],"code":[7,13,25,183,207],"vulnerability":[8,180,208],"detection":[9,209],"technology":[10,199],"based":[11,114,118,122,129],"on":[12,115,119,123,130],"semantic":[14,64,137],"contribution":[15,138],"address":[17],"software":[18,86],"security":[19,217],"challenges.":[20],"The":[21,73,88,136],"preprocesses":[23],"functions":[26],"by":[27],"constructing":[28],"a":[29,151,161,201],"dictionary":[30],"library":[31],"of":[32,75,140,154,159,164,170,179,218],"common":[33],"programming":[34],"naming":[35],"conventions,":[36],"builds":[37],"data":[38,187],"dependency":[39,43],"graphs":[40,44],"and":[41,54,59,67,85,91,96,103,127,166,185,189,194,210],"control":[42],"using":[45],"the":[46,76,99,132,146,215,219],"Joern":[47],"tool,":[48],"adopts":[49],"BPE":[50],"word":[51],"segmentation":[52],"technology,":[53],"combines":[55],"sentence":[56],"embedding":[57,62,68],"variants":[58],"LSTM":[60],"graph":[61,124],"for":[63,98,205],"feature":[65],"extraction":[66],"achieve":[70],"precise":[71],"detection.":[72],"construction":[74],"experimental":[77],"environment":[78],"takes":[79],"into":[80],"account":[81],"both":[82],"hardware":[83],"performance":[84,148],"compatibility.":[87],"Big-Vul,":[89],"SARD":[90],"NVD":[92],"datasets":[93],"were":[94],"selected":[95],"used":[97],"experiment":[100],"after":[101],"cleaning":[102],"stratified":[104],"sampling":[105],"processing.":[106],"Compared":[107],"with":[108,150],"methods":[109],"such":[110],"as":[111],"Checkmarx,":[112],"SySeVR":[113],"BLSTM,":[116],"VulCNN":[117],"CNN,":[120],"Devign":[121],"neural":[125],"networks,":[126],"LineVul":[128],"Transformer,":[131],"results":[133],"show":[134],"that:":[135],"method":[139],"this":[141],"study":[142],"performed":[143],"outstandingly":[144],"in":[145],"comprehensive":[147],"indicators,":[149],"recall":[152],"rate":[153,158,163],"87.52%,":[155],"an":[156,167],"accuracy":[157],"90.13%,":[160],"precision":[162],"88.76%,":[165],"F1":[168],"value":[169],"0.881.":[171],"It":[172],"shows":[173],"obvious":[174],"advantages":[175],"under":[176],"different":[177,182],"types":[178],"detection,":[181],"scales":[184],"training":[186],"volumes,":[188],"has":[190],"lower":[191],"false":[192,195],"positive":[193],"negative":[196],"rates.":[197],"provides":[200],"more":[202],"effective":[203],"way":[204],"expected":[212],"enhance":[214],"overall":[216],"software.":[220]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}
