CalcuLatency: Leveraging Cross-Layer Network Latency Measurements to Detect Proxy-Enabled Abuse
Reethika Ramesh, Philipp Winter, Sam Korman, Roya Ensafi
摘要
Efforts from emerging technology companies aim to democratize the ad delivery ecosystem and build systems that are privacy-centric and even share ad revenue benefits with their users. Other providers offer remuneration for users on their platform for interacting with and making use of services. But these efforts may suffer from coordinated abuse efforts aiming to defraud them. Attackers can use VPNs and proxies to fabricate their geolocation and earn disproportionate rewards. Balancing proxy-enabled abuse-prevention techniques with a privacy-focused business model is a hard challenge. Can service providers use minimal connection features to infer proxy use without jeopardizing user privacy? In this paper, we build and evaluate a solution, CalcuLatency, that incorporates various network latency measurement techniques and leverage the application-layer and networklayer differences in roundtrip-times when a user connects to the service using a proxy. We evaluate our four measurement techniques individually, and as an integrated system using a two-pronged evaluation. CalcuLatency is an easy-to-deploy, open-source solution that can serve as an inexpensive firststep to label proxies.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper3
- Resident Evil: Understanding Residential IP Proxy as a Dark ServiceXianghang Mi, Xuan Feng, Xiaojing Liao, Baojun Liu 等S&P 2019 · 被引用 80 次
- "All of them claim to be the best": Multi-perspective study of VPN users and VPN providersReethika Ramesh, Anjali Vyas, Roya EnsafiUSENIX Security 2023
- OpenVPN is Open to VPN FingerprintingDiwen Xue, Reethika Ramesh, Arham Jain, Michalis Kallitsis 等USENIX Security 2022
相关 Paper
- A Global Inference and Assessment of Large Shared IP AddressesVasileios Giotsas, Loqman Salamatian, Antoine Cordelle, Nick Wood 等SIGCOMM 2026
- AdCube: WebVR Ad Fraud and Practical Confinement of Third-Party AdsHyunjoo Lee, Jiyeon Lee, Daejun Kim, Suman Jana 等USENIX Security 2021 · 被引用 34 次
- Unveiling Network Performance in the Wild: An Ad-Driven Analysis of Mobile Download SpeedsMiguel A. Bermejo-Agueda, Patricia Callejo, Rubén Cuevas, Ángel Cuevas 等WWW 2025
- CELLSHIFT: RTT-Aware Trace Transduction for Real-World Website FingerprintingRob JansenNDSS 2026 · 被引用 5 次
- A Large-scale Analysis of Content Modification by Open HTTP ProxiesGiorgos Tsirantonakis, Panagiotis Ilia, Sotiris Ioannidis, Elias Athanasopoulos 等NDSS 2018 · 被引用 38 次
