[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_227":228},"routes/_layout",{"_11":154},"routes/entity.$type.$id",{"_11":12,"_13":14,"_15":16,"_17":18,"_19":20,"_21":22,"_23":24,"_25":26,"_27":28},"dehydratedState",{"_75":76,"_77":78},"type","paper","id","paper_W2885030880","section","articles","entity",{"_15":16,"_29":30,"_31":-5,"_32":-5,"_33":-5,"_34":-5,"_35":36,"_37":38,"_39":-5,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_50":51,"_52":30,"_53":54,"_55":56,"_57":58,"_59":60,"_61":62,"_63":-5,"_64":65,"_66":67,"_68":69,"_70":30,"_71":-5},"canonical","https://www.hugmap.com/entity/paper/paper_W2885030880/articles","siteBaseUrl","https://www.hugmap.com","sectionCount",0,"jsonLd","{\"@context\":\"https://schema.org\",\"@graph\":[{\"name\":\"SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities\",\"url\":\"https://www.hugmap.com/entity/paper/paper_W2885030880/articles\",\"@type\":\"ScholarlyArticle\",\"headline\":\"SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities\",\"datePublished\":\"2021-02-09\",\"isPartOf\":{\"@type\":\"Periodical\",\"name\":\"IEEE Transactions on Dependable and Secure Computing\"}},{\"@type\":\"CollectionPage\",\"name\":\"SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities 相关文章\",\"description\":\"SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities 在 HugMap 中的相关文章，含结构化关联信息与详情链接。\",\"url\":\"https://www.hugmap.com/entity/paper/paper_W2885030880/articles\",\"inLanguage\":\"zh-CN\"},{\"@type\":\"BreadcrumbList\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"首页\",\"item\":\"https://www.hugmap.com/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"论文\",\"item\":\"https://www.hugmap.com/search?type=paper\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities\",\"item\":\"https://www.hugmap.com/entity/paper/paper_W2885030880\"},{\"@type\":\"ListItem\",\"position\":4,\"name\":\"相关文章\",\"item\":\"https://www.hugmap.com/entity/paper/paper_W2885030880/articles\"}]}]}","name","SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities","nameZh","aliases","description","descriptionZh","status","active","externalIds","{\"arxiv\":\"1807.06756\",\"openalex\":\"W2885030880\",\"doi\":\"10.1109/tdsc.2021.3051525\"}","properties","source","openalex","createdAt","2026-05-15T19:08:19.247850652","updatedAt","2026-05-21T13:55:50.196034859","doi","10.1109/tdsc.2021.3051525","arxivId","1807.06756","openalexId","W2885030880","title","abstractText","The detection of software vulnerabilities (or vulnerabilities for short) is an important problem that has yet to be tackled, as manifested by the many vulnerabilities reported on a daily basis. This calls for machine learning methods for vulnerability detection. Deep learning is attractive for this purpose because it alleviates the requirement to manually define features. Despite the tremendous success of deep learning in other application domains, its applicability to vulnerability detection is not systematically understood. In order to fill this void, we propose the first systematic framework for using deep learning to detect vulnerabilities in C/C++ programs with source code. The framework, dubbed Syntax-based, Semantics-based, and Vector Representations (SySeVR), focuses on obtaining program representations that can accommodate syntax and semantic information pertinent to vulnerabilities. Our experiments with four software products demonstrate the usefulness of the framework: we detect 15 vulnerabilities that are not reported in the National Vulnerability Database. Among these 15 vulnerabilities, seven are unknown and have been reported to the vendors, and the other eight have been “silently” patched by the vendors when releasing newer versions of the pertinent software products.","publishedDate","2021-02-09","publishedYear",2021,"venue","IEEE Transactions on Dependable and Secure Computing","citationCount",553,"authors","keywords",[72,73,74],"pdfUrl","https://arxiv.org/pdf/1807.06756","topVenue",false,"displayName","displayDescription","Information and Cyber Security","Web Application Security Vulnerabilities","Software Engineering Research","mutations",[],"queries",[79],{"_80":81,"_82":83,"_84":85,"_86":87},"dehydratedAt",1784408125982,"state",{"_89":90,"_91":92,"_93":94,"_95":-5,"_96":26,"_97":26,"_98":26,"_99":-5,"_100":-5,"_101":69,"_35":102,"_103":104},"queryKey",[88,19,14,16],"queryHash","[\"portal\",\"entity\",\"paper\",\"paper_W2885030880\"]","portal","data",{"_19":20,"_105":106,"_107":108,"_109":110,"_18":111,"_112":113,"_63":114},"dataUpdateCount",1,"dataUpdatedAt",1784408125981,"error","errorUpdateCount","errorUpdatedAt","fetchFailureCount","fetchFailureReason","fetchMeta","isInvalidated","success","fetchStatus","idle","entityType","Paper","taxonomies",[115,116,117,118],"events",[],[],"technologies",[],[],{"_15":147,"_29":148,"_31":-5,"_32":-5,"_33":149,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":153,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":148,"_71":149},{"_15":142,"_29":74,"_31":-5,"_32":-5,"_33":-5,"_34":-5,"_35":36,"_37":143,"_39":-5,"_40":41,"_42":144,"_44":145,"_123":124,"_125":-5,"_126":127,"_128":129,"_130":146,"_132":26,"_133":134,"_135":26,"_136":-5,"_70":74,"_71":-5},{"_15":137,"_29":72,"_31":-5,"_32":-5,"_33":-5,"_34":-5,"_35":36,"_37":138,"_39":-5,"_40":41,"_42":139,"_44":140,"_123":124,"_125":-5,"_126":127,"_128":129,"_130":141,"_132":26,"_133":134,"_135":26,"_136":-5,"_70":72,"_71":-5},{"_15":119,"_29":73,"_31":-5,"_32":-5,"_33":-5,"_34":-5,"_35":36,"_37":120,"_39":-5,"_40":41,"_42":121,"_44":122,"_123":124,"_125":-5,"_126":127,"_128":129,"_130":131,"_132":26,"_133":134,"_135":26,"_136":-5,"_70":73,"_71":-5},"tax_rd_T12479","{\"openalex_topic\":\"T12479\"}","2026-05-14T08:42:40.317024047","2026-05-23T11:59:29.284173639","taxonomyType","RESEARCH_DOMAIN","code","level",3,"parentId","tax_rd_1710","path","Physical Sciences/Computer Science/Information Systems/Web Application Security Vulnerabilities","sortOrder","isLeaf",true,"entityCount","children","tax_rd_T10734","{\"openalex_topic\":\"T10734\"}","2026-05-14T01:15:33.419053145","2026-05-23T12:35:15.298838149","Physical Sciences/Computer Science/Information Systems/Information and Cyber Security","tax_rd_T10260","{\"openalex_topic\":\"T10260\"}","2026-05-14T00:28:34.279333119","2026-05-23T12:39:10.380010709","Physical Sciences/Computer Science/Information Systems/Software Engineering Research","tax_ind_security","网络安全","Cybersecurity","manual","INDUSTRY","tax_ind_root","科技行业/网络安全",{"_75":155,"_77":156},[],[157],{"_80":158,"_82":159,"_84":160,"_86":161},1784408118362,{"_89":163,"_91":92,"_93":158,"_95":-5,"_96":26,"_97":26,"_98":26,"_99":-5,"_100":-5,"_101":69,"_35":102,"_103":104},[88,162],"[\"portal\",\"industries\"]","industries",[164,165,166,167,168,169,170,171,172,173,174,175],{"_15":220,"_29":221,"_31":-5,"_32":222,"_33":223,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":224,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":221,"_71":223},{"_15":216,"_29":217,"_31":-5,"_32":-5,"_33":218,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":219,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":217,"_71":218},{"_15":210,"_29":211,"_31":-5,"_32":212,"_33":213,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":214,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":211,"_71":213},{"_15":147,"_29":148,"_31":-5,"_32":-5,"_33":149,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":153,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":148,"_71":149},{"_15":206,"_29":207,"_31":-5,"_32":-5,"_33":208,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":209,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":207,"_71":208},{"_15":200,"_29":201,"_31":-5,"_32":202,"_33":203,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":204,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":201,"_71":203},{"_15":196,"_29":197,"_31":-5,"_32":-5,"_33":198,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":199,"_132":26,"_133":134,"_135":26,"_136":-5,"_70":197,"_71":198},{"_15":192,"_29":193,"_31":-5,"_32":-5,"_33":194,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":195,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":193,"_71":194},{"_15":188,"_29":189,"_31":-5,"_32":-5,"_33":190,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":191,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":189,"_71":190},{"_15":184,"_29":185,"_31":-5,"_32":-5,"_33":186,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":187,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":185,"_71":186},{"_15":180,"_29":181,"_31":-5,"_32":-5,"_33":182,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":183,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":181,"_71":182},{"_15":176,"_29":177,"_31":-5,"_32":-5,"_33":178,"_34":-5,"_35":36,"_37":-5,"_39":-5,"_40":150,"_42":-5,"_44":-5,"_123":151,"_125":-5,"_126":92,"_128":152,"_130":179,"_132":26,"_133":69,"_135":26,"_136":-5,"_70":177,"_71":178},"tax_ind_smartphone","智能手机","Smartphone","科技行业/智能手机","tax_ind_robot","机器人","Robotics","科技行业/机器人","tax_ind_wearable","智能穿戴","Smart Wearables","科技行业/智能穿戴","tax_ind_energy","新能源与智能制造","New Energy & Smart Manufacturing","科技行业/新能源与智能制造","tax_ind_biotech","生物科技","Biotech","科技行业/生物科技","tax_ind_quantum","量子计算","Quantum Computing","科技行业/量子计算","tax_ind_blockchain","区块链",[205],"Blockchain","科技行业/区块链","Web3","tax_ind_enterprise","企业软件","Enterprise Software","科技行业/企业软件","tax_ind_semi","半导体",[215],"Semiconductor","科技行业/半导体","芯片","tax_ind_cloud","云计算","Cloud Computing","科技行业/云计算","tax_ind_ai","人工智能",[225,226],"Artificial Intelligence","科技行业/人工智能","AI","AI 技术","env",{"_229":24},"SITE_BASE_URL"]

SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities 论文

SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities · 相关文章