{"id":"https://openalex.org/W4364297077","doi":"https://doi.org/10.1109/aipr57179.2022.10092211","title":"Detecting Software Code Vulnerabilities Using 2D Convolutional Neural Networks with Program Slicing Feature Maps","display_name":"Detecting Software Code Vulnerabilities Using 2D Convolutional Neural Networks with Program Slicing Feature Maps","publication_year":2022,"publication_date":"2022-10-11","ids":{"openalex":"https://openalex.org/W4364297077","doi":"https://doi.org/10.1109/aipr57179.2022.10092211"},"language":"en","primary_location":{"id":"doi:10.1109/aipr57179.2022.10092211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr57179.2022.10092211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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/A5103760589","display_name":"Anne Watson","orcid":null},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anne Watson","raw_affiliation_strings":["University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091262324","display_name":"Ekincan Ufuktepe","orcid":"https://orcid.org/0000-0002-0156-4321"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ekincan Ufuktepe","raw_affiliation_strings":["University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025286899","display_name":"Kannappan Palaniappan","orcid":"https://orcid.org/0000-0003-2663-1380"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kannappan Palaniappan","raw_affiliation_strings":["University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103760589"],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":null,"apc_paid":null,"fwci":1.2736,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85672574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9995999932289124,"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/T10260","display_name":"Software Engineering Research","score":0.9995999932289124,"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":0.9994999766349792,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.8590171337127686},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6979196071624756},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6681477427482605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5424962043762207},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5083627104759216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44094857573509216},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4342958927154541},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12779191136360168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8590171337127686},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6979196071624756},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6681477427482605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5424962043762207},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5083627104759216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44094857573509216},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4342958927154541},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12779191136360168}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr57179.2022.10092211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr57179.2022.10092211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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":27,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W2026417691","https://openalex.org/W2056944867","https://openalex.org/W2144344516","https://openalex.org/W2147088720","https://openalex.org/W2293624369","https://openalex.org/W2312579046","https://openalex.org/W2781491433","https://openalex.org/W2885030880","https://openalex.org/W2885739832","https://openalex.org/W2972135640","https://openalex.org/W2976184969","https://openalex.org/W3008227126","https://openalex.org/W3101228802","https://openalex.org/W3104849875","https://openalex.org/W3138417868","https://openalex.org/W3142439607","https://openalex.org/W3201163019","https://openalex.org/W4226507742","https://openalex.org/W4283820151","https://openalex.org/W4284667406","https://openalex.org/W4285137371","https://openalex.org/W4309346268","https://openalex.org/W4309675192","https://openalex.org/W6636510571","https://openalex.org/W6767260250","https://openalex.org/W7030290986"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4375867731","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Throughout":[0],"the":[1,24,70,77,99,185,199,262,269,273,281,286,297,301],"post-PC":[2],"world,":[3],"IoT":[4],"devices":[5],"and":[6,29,45,84,128,162,215,258,285],"real-time":[7],"embedded":[8],"systems":[9],"have":[10,36,80],"integrated":[11],"themselves":[12],"into":[13,201,228],"every":[14],"aspect":[15],"of":[16,26,60,73,101,115,226,248,275,280,296],"our":[17],"lives.":[18],"However,":[19],"as":[20],"technology":[21],"integrates":[22],"itself,":[23],"risk":[25],"security":[27,64,121,156],"vulnerabilities":[28,65,108,157,174],"their":[30,58],"impact":[31],"also":[32],"grows.":[33],"Different":[34],"languages":[35],"different":[37],"susceptibilities":[38],"to":[39,50,57,92,105,133,154,159,222,271,291],"cyberattacks.":[40],"Programs":[41],"based":[42,124],"on":[43,125,184,268],"C":[44],"C++":[46],"are":[47,66,182,289],"particularly":[48],"vulnerable":[49,170],"cyberattacks":[51],"through":[52,204,305],"buffer":[53],"overflow":[54],"errors":[55],"due":[56,158],"lack":[59],"memory":[61],"management.":[62],"While":[63],"well-studied":[67],"areas,":[68],"with":[69],"increasing":[71],"popularity":[72],"deep":[74,103,117,136,176],"learning":[75,104,118,137],"applications,":[76],"attack":[78],"scenarios":[79],"become":[81,110],"more":[82],"sophis-ticated,":[83],"traditional":[85],"techniques":[86],"may":[87],"no":[88],"longer":[89],"be":[90],"enough":[91],"detect":[93,106,155],"attacks":[94],"or":[95],"potential":[96],"vulnerabilities.":[97],"Therefore,":[98],"application":[100],"using":[102,116,175,253],"such":[107],"has":[109],"a":[111,149,209,238,293,306],"trend.":[112],"The":[113,278],"appeal":[114],"in":[119],"software":[120],"is":[122,250,303],"usually":[123],"graphical":[126],"models":[127],"data,":[129],"which":[130],"encourages":[131],"researchers":[132],"use":[134,148],"graphical-based":[135],"methods":[138],"like":[139],"Graph":[140],"Neural":[141,151,308],"Networks":[142],"(GNN).":[143],"In":[144],"this":[145],"study,":[146],"we":[147,196,236],"Convolutional":[150,307],"Network":[152],"(CNN)":[153],"its":[160],"scalability":[161],"lower":[163],"computation":[164],"need.":[165],"This":[166],"paper":[167],"proposes":[168],"scanning":[169],"C/C++":[171],"functions":[172],"for":[173,243],"learning-based":[177],"image":[178,203,295,302],"classification.":[179],"Our":[180],"experiments":[181],"performed":[183],"NIST":[186],"SARD":[187],"dataset.":[188],"Inspired":[189],"by":[190,265],"existing":[191],"high-level":[192],"language":[193],"vulnerability":[194],"detection,":[195],"propose":[197],"converting":[198],"function":[200],"an":[202,229],"three":[205,254],"steps:":[206],"sentence":[207,220],"embedding,":[208],"statically":[210],"created":[211],"program":[212,239],"dependency":[213,240],"graph,":[214],"social":[216],"network":[217],"analysis.We":[218],"employ":[219],"embedding":[221],"convert":[223],"each":[224,244,276],"line":[225,247],"code":[227,249],"equally":[230,282],"sized":[231,283],"representative":[232,294],"vector.":[233],"Following":[234],"this,":[235],"produce":[237],"graph":[241],"(PDG)":[242],"function.":[245],"Each":[246],"then":[251],"analyzed":[252],"metrics:":[255],"Katz,":[256],"closeness,":[257],"destructibility.":[259],"We":[260],"compute":[261],"destructibility":[263],"metric":[264],"employing":[266],"forward-slicing":[267],"PDG":[270],"determine":[272],"reachability":[274],"line.":[277],"combination":[279],"vectors":[284],"analysis":[287],"metrics":[288],"used":[290],"create":[292],"source":[298],"code.":[299],"Finally,":[300],"classified":[304],"Network.":[309]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
