Liang Wang, Hyojoon Kim, Prateek Mittal, Jennifer Rexford (Princeton University)

In conventional DNS, or Do53, requests and responses are sent in cleartext. Thus, DNS recursive resolvers or any on-path adversaries can access privacy-sensitive information. To address this issue, several encryption-based approaches (e.g., DNS-over-HTTPS) and proxy-based approaches (e.g., Oblivious DNS) were proposed. However, encryption-based approaches put too much trust in recursive resolvers. Proxy-based approaches can help hide the client’s identity, but sets a higher deployment barrier while also introducing noticeable performance overhead. We propose PINOT, a packet-header obfuscation system that runs entirely in the data plane of a programmable network switch, which provides a lightweight, low-deployment-barrier anonymization service for clients sending and receiving DNS packets. PINOT does not require any modification to the DNS protocol or additional client software installation or proxy setup. Yet, it can also be combined with existing approaches to provide stronger privacy guarantees. We implement a PINOT prototype on a commodity switch, deploy it in a campus network, and present results on protecting user identity against public DNS services.

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The Nuts and Bolts of Building FlowLens

Diogo Barradas (Instituto Superior Técnico, Universidade de Lisboa)

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Detecting Tor Bridge from Sampled Traffic in Backbone Networks

Hua Wu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration Southeast University, Ministry of Education, Jiangsu Nanjing, Purple Mountain Laboratories for Network and Communication Security (Nanjing, Jiangsu)), Shuyi Guo, Guang Cheng, Xiaoyan Hu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration…

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Demo #10: Security of Deep Learning based Automated Lane...

Takami Sato, Junjie Shen, Ningfei Wang (UC Irvine), Yunhan Jia (ByteDance), Xue Lin (Northeastern University), and Qi Alfred Chen (UC Irvine)

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Доверя́й, но проверя́й: SFI safety for native-compiled Wasm

Evan Johnson (University of California San Diego), David Thien (University of California San Diego), Yousef Alhessi (University of California San Diego), Shravan Narayan (University Of California San Diego), Fraser Brown (Stanford University), Sorin Lerner (University of California San Diego), Tyler McMullen (Fastly Labs), Stefan Savage (University of California San Diego), Deian Stefan (University of California…

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