Fingerprinting Deep Packet Inspection Devices by their Ambiguities

Users around the world face escalating network interference such as censorship, throttling, and interception, largely driven by the commoditization and growing availability of Deep Packet Inspection (DPI) devices. Once reserved for a few well-resourced nation-state actors, the ability to interfere with traffic at scale is now within reach of nearly any network operator. Despite this proliferation, our understanding of DPIs and their deployments on the Internet remains limited---being network intermediary leaves DPI unresponsive to conventional host-based scanning tools, and DPI vendors actively obscuring their products further complicates measurement efforts.

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Publication Details

Published
2025-11-19
DOI
https://doi.org/10.1145/3719027.3765145
Primary Topic
Network Packet Processing and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Fingerprinting Deep Packet Inspection Devices by their Ambiguities

Ram Sundara Raman, Diwen Xue, Wayne Wang, Roya Ensafi et al.
Network Packet Processing and Optimization
article

Fingerprinting Deep Packet Inspection Devices by their Ambiguities

Ram Sundara Raman, Diwen Xue, Wayne Wang, Roya Ensafi, Armin Huremagic
article en

Abstract

Users around the world face escalating network interference such as censorship, throttling, and interception, largely driven by the commoditization and growing availability of Deep Packet Inspection (DPI) devices. Once reserved for a few well-resourced nation-state actors, the ability to interfere with traffic at scale is now within reach of nearly any network operator. Despite this proliferation, our understanding of DPIs and their deployments on the Internet remains limited---being network intermediary leaves DPI unresponsive to conventional host-based scanning tools, and DPI vendors actively obscuring their products further complicates measurement efforts.

University of California, Santa Cruz (US), University of Michigan (US)
National Science Foundation
Openalex Percentile: Top 60%
Network Packet Processing and Optimization
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Fingerprinting Deep Packet Inspection Devices by their Ambiguities — Ram Sundara Raman, Diwen Xue, et al. · (2025) | TGRS Research Map | TGRS