基于遗传算法和模型约束的漏洞挖掘方法

Jun Yang, Guojun Mei, Chen Chen
{"title":"基于遗传算法和模型约束的漏洞挖掘方法","authors":"Jun Yang, Guojun Mei, Chen Chen","doi":"10.1109/ICCCN.2018.8487461","DOIUrl":null,"url":null,"abstract":"The fuzzy technology based on model constraint is lack of guidance in variation process, and the fuzzy technology based on coverage information has a weak code penetration ability when meeting a complex logic verification, what's more, these two methods' code coverage are deeply dependent on the initial samples, if there are no specific file structure types in the initial samples, the possibility of covering the corresponding code blocks will be very low. This paper proposes a vulnerability mining method based on genetic algorithm and constraint model. The method uses the model constraint technology to create test samples, and uses the fuzzy technology based on coverage information feedback to guide the direction of data variation. Besides that, using genetic algorithm to enrich the diversity of file structure types and combinations among test samples, and generate high-quality test samples gradually at the same time, which can greatly improve the efficiency of fuzzing test.","PeriodicalId":399145,"journal":{"name":"2018 27th International Conference on Computer Communication and Networks (ICCCN)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vulnerability Mining Method Based on Genetic Algorithm and Model Constraint\",\"authors\":\"Jun Yang, Guojun Mei, Chen Chen\",\"doi\":\"10.1109/ICCCN.2018.8487461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The fuzzy technology based on model constraint is lack of guidance in variation process, and the fuzzy technology based on coverage information has a weak code penetration ability when meeting a complex logic verification, what's more, these two methods' code coverage are deeply dependent on the initial samples, if there are no specific file structure types in the initial samples, the possibility of covering the corresponding code blocks will be very low. This paper proposes a vulnerability mining method based on genetic algorithm and constraint model. The method uses the model constraint technology to create test samples, and uses the fuzzy technology based on coverage information feedback to guide the direction of data variation. Besides that, using genetic algorithm to enrich the diversity of file structure types and combinations among test samples, and generate high-quality test samples gradually at the same time, which can greatly improve the efficiency of fuzzing test.\",\"PeriodicalId\":399145,\"journal\":{\"name\":\"2018 27th International Conference on Computer Communication and Networks (ICCCN)\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 27th International Conference on Computer Communication and Networks (ICCCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCN.2018.8487461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 27th International Conference on Computer Communication and Networks (ICCCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2018.8487461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于模型约束的模糊技术在变型过程中缺乏指向性,基于覆盖信息的模糊技术在满足复杂逻辑验证时代码穿透能力较弱,并且这两种方法的代码覆盖深度依赖于初始样本,如果初始样本中没有特定的文件结构类型,覆盖相应代码块的可能性会很低。提出了一种基于遗传算法和约束模型的漏洞挖掘方法。该方法采用模型约束技术创建测试样本,并采用基于覆盖率信息反馈的模糊技术指导数据变化方向。此外,利用遗传算法丰富测试样本之间文件结构类型和组合的多样性,同时逐步生成高质量的测试样本,可以大大提高模糊测试的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vulnerability Mining Method Based on Genetic Algorithm and Model Constraint
The fuzzy technology based on model constraint is lack of guidance in variation process, and the fuzzy technology based on coverage information has a weak code penetration ability when meeting a complex logic verification, what's more, these two methods' code coverage are deeply dependent on the initial samples, if there are no specific file structure types in the initial samples, the possibility of covering the corresponding code blocks will be very low. This paper proposes a vulnerability mining method based on genetic algorithm and constraint model. The method uses the model constraint technology to create test samples, and uses the fuzzy technology based on coverage information feedback to guide the direction of data variation. Besides that, using genetic algorithm to enrich the diversity of file structure types and combinations among test samples, and generate high-quality test samples gradually at the same time, which can greatly improve the efficiency of fuzzing test.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信