Criminal clickbait: a panel data analysis on the attractiveness of online advertisements offering stolen data

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Frontiers in Big Data Pub Date : 2023-12-22 DOI:10.3389/fdata.2023.1320569
Renushka Madarie, Christianne J. de Poot, Marleen Weulen Kranenbarg
{"title":"Criminal clickbait: a panel data analysis on the attractiveness of online advertisements offering stolen data","authors":"Renushka Madarie, Christianne J. de Poot, Marleen Weulen Kranenbarg","doi":"10.3389/fdata.2023.1320569","DOIUrl":null,"url":null,"abstract":"Few studies have examined the sales of stolen account credentials on darkweb markets. In this study, we tested how advertisement characteristics affect the popularity of illicit online advertisements offering account credentials. Unlike previous criminological research, we take a novel approach by assessing the applicability of knowledge on regular consumer behaviours instead of theories explaining offender behaviour.We scraped 1,565 unique advertisements offering credentials on a darkweb market. We used this panel data set to predict the simultaneous effects of the asking price, endorsement cues and title elements on advertisement popularity by estimating several hybrid panel data models.Most of our findings disconfirm our hypotheses. Asking price did not affect advertisement popularity. Endorsement cues, including vendor reputation and cumulative sales and views, had mixed and negative relationships, respectively, with advertisement popularity.Our results might suggest that account credentials are not simply regular products, but high-risk commodities that, paradoxically, become less attractive as they gain popularity. This study highlights the necessity of a deeper understanding of illicit online market dynamics to improve theories on illicit consumer behaviours and assist cybersecurity experts in disrupting criminal business models more effectively. We propose several avenues for future experimental research to gain further insights into these illicit processes.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"1 11","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Big Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdata.2023.1320569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Few studies have examined the sales of stolen account credentials on darkweb markets. In this study, we tested how advertisement characteristics affect the popularity of illicit online advertisements offering account credentials. Unlike previous criminological research, we take a novel approach by assessing the applicability of knowledge on regular consumer behaviours instead of theories explaining offender behaviour.We scraped 1,565 unique advertisements offering credentials on a darkweb market. We used this panel data set to predict the simultaneous effects of the asking price, endorsement cues and title elements on advertisement popularity by estimating several hybrid panel data models.Most of our findings disconfirm our hypotheses. Asking price did not affect advertisement popularity. Endorsement cues, including vendor reputation and cumulative sales and views, had mixed and negative relationships, respectively, with advertisement popularity.Our results might suggest that account credentials are not simply regular products, but high-risk commodities that, paradoxically, become less attractive as they gain popularity. This study highlights the necessity of a deeper understanding of illicit online market dynamics to improve theories on illicit consumer behaviours and assist cybersecurity experts in disrupting criminal business models more effectively. We propose several avenues for future experimental research to gain further insights into these illicit processes.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
犯罪点击诱饵:关于提供被盗数据的在线广告吸引力的面板数据分析
很少有研究对暗网市场上被盗账户凭据的销售情况进行调查。在本研究中,我们测试了广告特征如何影响提供账户凭证的非法网络广告的受欢迎程度。与以往的犯罪学研究不同,我们采用了一种新颖的方法,即评估常规消费者行为知识的适用性,而不是解释犯罪者行为的理论。我们利用这个面板数据集,通过估计几个混合面板数据模型,预测要价、认可线索和标题元素对广告受欢迎程度的同时影响。要价并不影响广告受欢迎程度。我们的研究结果可能表明,账户凭证并不是简单的常规产品,而是高风险商品,随着其受欢迎程度的提高,其吸引力也会随之降低。本研究强调了深入了解非法网络市场动态的必要性,以完善有关非法消费者行为的理论,并协助网络安全专家更有效地破坏犯罪商业模式。我们为未来的实验研究提出了几条途径,以进一步深入了解这些非法过程。
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 去求助
来源期刊
CiteScore
5.20
自引率
3.20%
发文量
122
审稿时长
13 weeks
期刊最新文献
Cybermycelium: a reference architecture for domain-driven distributed big data systems. Cognitive warfare: a conceptual analysis of the NATO ACT cognitive warfare exploratory concept. An enhanced whale optimization algorithm for task scheduling in edge computing environments. Promoting fairness in link prediction with graph enhancement. Exploring code portability solutions for HEP with a particle tracking test code.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1