Survey on static software vulnerability detection for source code

Static software vulnerability detection is mainly divided into two types according to different analysis objects:vulnerability detection for binary code and vulnerability detection for source code.Because the source codecontains more semantic information,it is more favored by code auditors.The exist...

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Main Authors: Zhen LI, Deqing ZOU, Zeli WANG, Hai JIN
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2019-02-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019001
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author Zhen LI
Deqing ZOU
Zeli WANG
Hai JIN
author_facet Zhen LI
Deqing ZOU
Zeli WANG
Hai JIN
author_sort Zhen LI
collection DOAJ
description Static software vulnerability detection is mainly divided into two types according to different analysis objects:vulnerability detection for binary code and vulnerability detection for source code.Because the source codecontains more semantic information,it is more favored by code auditors.The existing vulnerability detection research works for source code are summarized from four aspects:code similarity-based vulnerability detection,symbolic execution-based vulnerability detection,rule-based vulnerability detection,and machine learning-based vulnerability detection.The vulnerability detection system based on source code similarity and the intelligent software vulnerability detection system for source code are taken as two examples to introduce the process of vulnerability detection in detail.
format Article
id doaj-art-a2b4682ea8cc4eac8b52b93b3501dbcd
institution Kabale University
issn 2096-109X
language English
publishDate 2019-02-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-a2b4682ea8cc4eac8b52b93b3501dbcd2025-01-15T03:13:15ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2019-02-01511459555152Survey on static software vulnerability detection for source codeZhen LIDeqing ZOUZeli WANGHai JINStatic software vulnerability detection is mainly divided into two types according to different analysis objects:vulnerability detection for binary code and vulnerability detection for source code.Because the source codecontains more semantic information,it is more favored by code auditors.The existing vulnerability detection research works for source code are summarized from four aspects:code similarity-based vulnerability detection,symbolic execution-based vulnerability detection,rule-based vulnerability detection,and machine learning-based vulnerability detection.The vulnerability detection system based on source code similarity and the intelligent software vulnerability detection system for source code are taken as two examples to introduce the process of vulnerability detection in detail.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019001software vulnerabilityvulnerability detection for source codecode similaritydeep learning
spellingShingle Zhen LI
Deqing ZOU
Zeli WANG
Hai JIN
Survey on static software vulnerability detection for source code
网络与信息安全学报
software vulnerability
vulnerability detection for source code
code similarity
deep learning
title Survey on static software vulnerability detection for source code
title_full Survey on static software vulnerability detection for source code
title_fullStr Survey on static software vulnerability detection for source code
title_full_unstemmed Survey on static software vulnerability detection for source code
title_short Survey on static software vulnerability detection for source code
title_sort survey on static software vulnerability detection for source code
topic software vulnerability
vulnerability detection for source code
code similarity
deep learning
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019001
work_keys_str_mv AT zhenli surveyonstaticsoftwarevulnerabilitydetectionforsourcecode
AT deqingzou surveyonstaticsoftwarevulnerabilitydetectionforsourcecode
AT zeliwang surveyonstaticsoftwarevulnerabilitydetectionforsourcecode
AT haijin surveyonstaticsoftwarevulnerabilitydetectionforsourcecode