一种提高自动生成库存质量的半自动方法

Silvia Bonomi, Marco Cuoci, S. Lenti
{"title":"一种提高自动生成库存质量的半自动方法","authors":"Silvia Bonomi, Marco Cuoci, S. Lenti","doi":"10.1109/CSR57506.2023.10225003","DOIUrl":null,"url":null,"abstract":"Inventories are precious sources of information for security-related processes. As a consequence, the quality of the data in the inventories plays a crucial role in the overall quality of the fed processes. This paper takes this challenge and provides heuristics to improve the accuracy of automatically generated inventories through a semi-automatic approach leveraging user knowledge.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Semi-automatic Approach for Enhancing the Quality of Automatically Generated Inventories\",\"authors\":\"Silvia Bonomi, Marco Cuoci, S. Lenti\",\"doi\":\"10.1109/CSR57506.2023.10225003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inventories are precious sources of information for security-related processes. As a consequence, the quality of the data in the inventories plays a crucial role in the overall quality of the fed processes. This paper takes this challenge and provides heuristics to improve the accuracy of automatically generated inventories through a semi-automatic approach leveraging user knowledge.\",\"PeriodicalId\":354918,\"journal\":{\"name\":\"2023 IEEE International Conference on Cyber Security and Resilience (CSR)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Cyber Security and Resilience (CSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSR57506.2023.10225003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSR57506.2023.10225003","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

清单是与安全相关的流程的宝贵信息来源。因此,库存数据的质量在美联储流程的整体质量中起着至关重要的作用。本文接受了这一挑战,并提供了启发式方法,通过利用用户知识的半自动方法来提高自动生成库存的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Semi-automatic Approach for Enhancing the Quality of Automatically Generated Inventories
Inventories are precious sources of information for security-related processes. As a consequence, the quality of the data in the inventories plays a crucial role in the overall quality of the fed processes. This paper takes this challenge and provides heuristics to improve the accuracy of automatically generated inventories through a semi-automatic approach leveraging user knowledge.
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