The Empirical Evaluation of Artificial Intelligence-based Techniques for Improving Cyber Security

Chhaya Nayak, Chintala Lakshmana Rao, Tanweer Alam, Shalini Singh, Shaziya Islam, Umme Habiba Maginmani
{"title":"The Empirical Evaluation of Artificial Intelligence-based Techniques for Improving Cyber Security","authors":"Chhaya Nayak, Chintala Lakshmana Rao, Tanweer Alam, Shalini Singh, Shaziya Islam, Umme Habiba Maginmani","doi":"10.1109/ICEARS56392.2023.10085368","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) technologies have been recently developed, and their advantages can be observed in a wide range of domains, from image processing to face detection. AI-based approaches can assist opponents to enhance their attack strategies while also improving cyber protection technologies. The efficiency of AI techniques against cyber security issues are evaluated. Here, the primary data and a quantitative study design approach is used. The information is then obtained from software industry professionals. The sample size for this study is 549 people, and it included confirmatory factor analysis, discriminant validity testing, model fundamental analysis, and hypothesis evaluation. All variables' P-values were found to be statistical, with the exception of intelligent agents, which had no meaningful relationship to AI or cyber security. The main issues were availability, geographical locations, study population, and other related variables.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEARS56392.2023.10085368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) technologies have been recently developed, and their advantages can be observed in a wide range of domains, from image processing to face detection. AI-based approaches can assist opponents to enhance their attack strategies while also improving cyber protection technologies. The efficiency of AI techniques against cyber security issues are evaluated. Here, the primary data and a quantitative study design approach is used. The information is then obtained from software industry professionals. The sample size for this study is 549 people, and it included confirmatory factor analysis, discriminant validity testing, model fundamental analysis, and hypothesis evaluation. All variables' P-values were found to be statistical, with the exception of intelligent agents, which had no meaningful relationship to AI or cyber security. The main issues were availability, geographical locations, study population, and other related variables.
基于人工智能的网络安全提升技术的实证评价
人工智能(AI)技术是近年来发展起来的,其优势可以在从图像处理到人脸检测的广泛领域中观察到。基于人工智能的方法可以帮助对手增强他们的攻击策略,同时也可以改进网络保护技术。评估了人工智能技术应对网络安全问题的效率。在这里,使用了原始数据和定量研究设计方法。然后从软件行业的专业人员那里获得这些信息。本研究的样本量为549人,包括验证性因子分析、判别效度检验、模型基础分析和假设评估。所有变量的p值都是统计性的,除了智能代理,它与人工智能或网络安全没有意义的关系。主要问题是可用性、地理位置、研究人群和其他相关变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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