YARWEB:基于网络的雅苒通用规则生成器

Mr. Shreyas Biju Nair, Mr. Laalas Tadavarthy, Mr. Kailas M K, Mr. Gowrishankar T O
{"title":"YARWEB:基于网络的雅苒通用规则生成器","authors":"Mr. Shreyas Biju Nair, Mr. Laalas Tadavarthy, Mr. Kailas M K, Mr. Gowrishankar T O","doi":"10.36713/epra15953","DOIUrl":null,"url":null,"abstract":"In the modern 21st century, surfing the internet has become difficult due to the rise of malware and adware. Sensitive information is often a risk to be stored without encryption. If malware does infiltrate, devising a solution to mitigate the risks is difficult and tiresome. The proposed framework presents a web-based approach to automatically generate a YARA rule for a malicious file uploaded by the user. Since it is a search engine-based model, it becomes extremely portable and useful. The testing of this prototype depicts that it is fully capable of detecting malicious samples with an average accuracy of 0.80.\nKEYWORDS—Malware Analysis, YARA Rules, Generic Rules, Malicious Strings, Fully Automated.","PeriodicalId":114964,"journal":{"name":"EPRA International Journal of Research & Development (IJRD)","volume":"17 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"YARWEB: WEB-BASED GENERIC YARA RULE GENERATOR\",\"authors\":\"Mr. Shreyas Biju Nair, Mr. Laalas Tadavarthy, Mr. Kailas M K, Mr. Gowrishankar T O\",\"doi\":\"10.36713/epra15953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the modern 21st century, surfing the internet has become difficult due to the rise of malware and adware. Sensitive information is often a risk to be stored without encryption. If malware does infiltrate, devising a solution to mitigate the risks is difficult and tiresome. The proposed framework presents a web-based approach to automatically generate a YARA rule for a malicious file uploaded by the user. Since it is a search engine-based model, it becomes extremely portable and useful. The testing of this prototype depicts that it is fully capable of detecting malicious samples with an average accuracy of 0.80.\\nKEYWORDS—Malware Analysis, YARA Rules, Generic Rules, Malicious Strings, Fully Automated.\",\"PeriodicalId\":114964,\"journal\":{\"name\":\"EPRA International Journal of Research & Development (IJRD)\",\"volume\":\"17 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EPRA International Journal of Research & Development (IJRD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36713/epra15953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPRA International Journal of Research & Development (IJRD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36713/epra15953","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

在 21 世纪的今天,由于恶意软件和广告软件的兴起,上网变得越来越困难。敏感信息在没有加密的情况下存储往往存在风险。如果恶意软件真的渗透进来,要想设计出降低风险的解决方案既困难又令人厌烦。拟议的框架提出了一种基于网络的方法,可针对用户上传的恶意文件自动生成 YARA 规则。由于它是一个基于搜索引擎的模型,因此具有极高的可移植性和实用性。对该原型的测试表明,它完全能够检测出恶意样本,平均准确率为 0.80。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
YARWEB: WEB-BASED GENERIC YARA RULE GENERATOR
In the modern 21st century, surfing the internet has become difficult due to the rise of malware and adware. Sensitive information is often a risk to be stored without encryption. If malware does infiltrate, devising a solution to mitigate the risks is difficult and tiresome. The proposed framework presents a web-based approach to automatically generate a YARA rule for a malicious file uploaded by the user. Since it is a search engine-based model, it becomes extremely portable and useful. The testing of this prototype depicts that it is fully capable of detecting malicious samples with an average accuracy of 0.80. KEYWORDS—Malware Analysis, YARA Rules, Generic Rules, Malicious Strings, Fully Automated.
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:604180095
Book学术官方微信