EAGER: ISN: Detecting and Disrupting Illicit Supply Networks via Traffic Distribution Systems

EAGER：ISN：通过流量分配系统检测和破坏非法供应网络

• 批准号: 1842020
• 负责人: Nick Nikiforakis
• 金额: $ 29.99万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842020&HistoricalAwards=false
• 关键词: EAGER; ISN; Detecting; Disrupting; Illicit

This EArly-concept Grant for Exploratory Research (EAGER) will enhance national health, prosperity, and security by contributing to our understanding of and ability to disrupt the online infrastructure that supports illicit supply networks. Malicious advertising is responsible for exposing a large fraction of online users to malicious content, including content from illicit supply networks, such as those trafficking in fake luxury goods and counterfeit pharmaceuticals. These abusive services not only exfiltrate private information and cause economic harm, but can also, in the case of unlicensed pharmaceutical products, damage public health. This project focuses on developing methods to detect and disrupt these illicit supply chains by targeting the traffic distribution systems that enable them, i.e., the online hosts that are responsible for redirecting users from gateway pages to the final abusive service. Mapping these networks and ultimately taking down their hosts will increase the cost of illicit commerce, yielding positive economic and public health impact. The award will provide support to engage graduate students in research with high societal impact.The project seeks to understand, measure, model, and disrupt traffic distribution systems as well as characterize the effects of this disruption on the pricing of illicit goods and services. By devising multiple high-toxicity URL streams and automatically crawling these URLs on a daily basis from multiple geographical locations and multiple browsing agents, this project will enable the collection of a large number of traffic distribution systems as well as the abusive services that utilize them. The project includes the development of techniques for converting the collected network traces into directed graphs, the attribution and merging of nodes belonging to the same actors, and the use of these graphs for modeling the effects of takedowns in the presence of operational constraints. This research will discover and document how these illicit operations function, improve the automated detection of their abusive services, and provide data to other researchers on the operations of traffic distribution systems and their vulnerability to disruptions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

EARLY概念探索性研究补助金（EAGER）将通过促进我们对支持非法供应网络的在线基础设施的理解和破坏能力来加强国家健康，繁荣和安全。 恶意广告使很大一部分在线用户接触到恶意内容，包括来自非法供应网络的内容，例如贩运假冒奢侈品和假冒药品的网络。这些滥用服务不仅泄露私人信息，造成经济损失，而且在未经许可的药品情况下，还可能损害公共健康。该项目的重点是制定方法，以查明和破坏这些非法供应链，方法是针对使这些供应链得以实现的贩运分配系统，即，负责将用户从网关页面重定向到最终滥用服务的在线主机。绘制这些网络并最终摧毁其主机将增加非法商业的成本，产生积极的经济和公共卫生影响。 该奖项将为研究生参与具有高度社会影响力的研究提供支持。该项目旨在了解，测量，建模和破坏交通分配系统，并描述这种破坏对非法商品和服务定价的影响。通过设计多个高毒性URL流，并每天从多个地理位置和多个浏览代理自动抓取这些URL，该项目将能够收集大量的流量分配系统以及利用它们的滥用服务。该项目包括开发将收集到的网络痕迹转换为有向图的技术，归属和合并属于同一行为者的节点，以及使用这些图对存在操作限制的情况下的拆除效果进行建模。这项研究将发现和记录这些非法操作的功能，提高其滥用服务的自动检测，并为其他研究人员提供有关流量分配系统的操作及其对中断的脆弱性的数据。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Unnecessarily Identifiable: Quantifying the fingerprintability of browser extensions due to bloat

不必要的可识别：量化由于膨胀而导致的浏览器扩展的指纹识别能力

• 发表时间: 2019
• 期刊: Proceedings of the Web Conference (WWW
• 作者: Starov, Oleksii;Laperdrix, Pierre;Kapravelos, Alexandros;Nikiforakis, Nick
• 通讯作者: Nikiforakis, Nick

To Err.Is Human: Characterizing the Threat of Unintended URLs in Social Media

• DOI: 10.14722/ndss.2021.24322
• 发表时间: 2021
• 期刊: Proceedings 2021 Network and Distributed System Security Symposium
• 作者: Beliz Kaleli;Brian Kondracki;Manuel Egele;Nick Nikiforakis;G. Stringhini

Morellian Analysis for Browsers: Making Web Authentication Stronger With Canvas Fingerprinting

浏览器的 Morellian 分析：通过 Canvas 指纹识别增强 Web 身份验证

• 发表时间: 2019
• 期刊: Proceedings of the 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA
• 作者: Laperdrix, Pierre;Avoine, Gildas;Baudry, Benoit;Nikiforakis, Nick
• 通讯作者: Nikiforakis, Nick

Less is More: Quantifying the Security Benefits of Debloating Web Applications

• 发表时间: 2019
• 作者: Babak Amin Azad;Pierre Laperdrix;Nick Nikiforakis

The Droid is in the Details: Environment-aware Evasion of Android Sandboxes

• DOI: 10.14722/ndss.2022.23056
• 发表时间: 2022
• 期刊: Proceedings 2022 Network and Distributed System Security Symposium
• 作者: Brian Kondracki