移动应用程序安全风险评分:基于敏感用户输入的方法

Trishla Shah, Raghav V. Sampangi, Angela Siegel
{"title":"移动应用程序安全风险评分:基于敏感用户输入的方法","authors":"Trishla Shah, Raghav V. Sampangi, Angela Siegel","doi":"10.1109/ICAIC60265.2024.10433828","DOIUrl":null,"url":null,"abstract":"This research paper introduces a Hierarchical Weighted Risk Scoring Model specifically designed to assess the risk levels of mobile applications based on user inputs. Through an extensive review of literature on risk score calculation models and term sensitivity identification techniques, this study categorizes terms based on their sensitivity, particularly in relation to sensitive user inputs that may potentially lead to data leaks. The sensitivity of user terms are defined based on the guidelines from PIPEDA. By integrating these terms, along with test outcomes and weights, the model accurately calculates risk scores. The resulting risk assessments provide users with valuable insights, empowering them to make informed decisions and effectively manage risks associated with mobile application usage. This research contributes to the field by offering a user-centric framework that combines various risk score calculation models and term sensitivity identification techniques, tailored specifically for mobile applications and addressing the potential risks arising from sensitive user inputs.","PeriodicalId":517265,"journal":{"name":"2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC)","volume":"23 1","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobile Application Security Risk Score: A sensitive user input-based approach\",\"authors\":\"Trishla Shah, Raghav V. Sampangi, Angela Siegel\",\"doi\":\"10.1109/ICAIC60265.2024.10433828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research paper introduces a Hierarchical Weighted Risk Scoring Model specifically designed to assess the risk levels of mobile applications based on user inputs. Through an extensive review of literature on risk score calculation models and term sensitivity identification techniques, this study categorizes terms based on their sensitivity, particularly in relation to sensitive user inputs that may potentially lead to data leaks. The sensitivity of user terms are defined based on the guidelines from PIPEDA. By integrating these terms, along with test outcomes and weights, the model accurately calculates risk scores. The resulting risk assessments provide users with valuable insights, empowering them to make informed decisions and effectively manage risks associated with mobile application usage. This research contributes to the field by offering a user-centric framework that combines various risk score calculation models and term sensitivity identification techniques, tailored specifically for mobile applications and addressing the potential risks arising from sensitive user inputs.\",\"PeriodicalId\":517265,\"journal\":{\"name\":\"2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC)\",\"volume\":\"23 1\",\"pages\":\"1-10\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIC60265.2024.10433828\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIC60265.2024.10433828","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

本研究论文介绍了一种分层加权风险评分模型,专门用于根据用户输入评估移动应用程序的风险等级。通过广泛查阅有关风险评分计算模型和术语敏感性识别技术的文献,本研究根据术语的敏感性,尤其是与可能导致数据泄漏的敏感用户输入相关的敏感性,对术语进行了分类。用户术语的敏感性是根据 PIPEDA 的指导方针定义的。通过整合这些术语以及测试结果和权重,模型可以准确计算出风险分数。由此得出的风险评估结果为用户提供了有价值的见解,使他们能够做出明智的决定,并有效管理与移动应用使用相关的风险。这项研究提供了一个以用户为中心的框架,该框架结合了各种风险分数计算模型和术语敏感性识别技术,专门为移动应用量身定制,可解决敏感用户输入带来的潜在风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile Application Security Risk Score: A sensitive user input-based approach
This research paper introduces a Hierarchical Weighted Risk Scoring Model specifically designed to assess the risk levels of mobile applications based on user inputs. Through an extensive review of literature on risk score calculation models and term sensitivity identification techniques, this study categorizes terms based on their sensitivity, particularly in relation to sensitive user inputs that may potentially lead to data leaks. The sensitivity of user terms are defined based on the guidelines from PIPEDA. By integrating these terms, along with test outcomes and weights, the model accurately calculates risk scores. The resulting risk assessments provide users with valuable insights, empowering them to make informed decisions and effectively manage risks associated with mobile application usage. This research contributes to the field by offering a user-centric framework that combines various risk score calculation models and term sensitivity identification techniques, tailored specifically for mobile applications and addressing the potential risks arising from sensitive user inputs.
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