Trevor Smith (Brigham Young University), Luke Dickenson (Brigham Young University), Kent Seamons (Brigham Young University)

Current revocation strategies have numerous issues that prevent their widespread adoption and use, including scalability, privacy, and new infrastructure requirements. Consequently, revocation is often ignored, leaving clients vulnerable to man-in-the-middle attacks.

This paper presents Let's Revoke, a scalable global revocation strategy that addresses the concerns of current revocation checking. Let's Revoke introduces a new unique identifier to each certificate that serves as an index to a dynamically-sized bit vector containing revocation status information. The bit vector approach enables significantly more efficient revocation checking for both clients and certificate authorities. We compare Let's Revoke to existing revocation schemes and show that it requires less storage and network bandwidth than other systems, including those that only cover a fraction of the global certificate space. We further demonstrate through simulations that Let's Revoke scales linearly up to ten billion certificates, even during mass revocation events.

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SymTCP: Eluding Stateful Deep Packet Inspection with Automated Discrepancy...

Zhongjie Wang (University of California, Riverside), Shitong Zhu (University of California, Riverside), Yue Cao (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside), Kevin S. Chan (U.S. Army Research Lab), Tracy D. Braun (U.S. Army Research Lab)

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Adversarial Classification Under Differential Privacy

Jairo Giraldo (University of Utah), Alvaro Cardenas (UC Santa Cruz), Murat Kantarcioglu (UT Dallas), Jonathan Katz (George Mason University)

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A Practical Approach for Taking Down Avalanche Botnets Under...

Victor Le Pochat (imec-DistriNet, KU Leuven), Tim Van hamme (imec-DistriNet, KU Leuven), Sourena Maroofi (Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG), Tom Van Goethem (imec-DistriNet, KU Leuven), Davy Preuveneers (imec-DistriNet, KU Leuven), Andrzej Duda (Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG), Wouter Joosen (imec-DistriNet, KU Leuven), Maciej Korczyński (Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG)

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DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing

Yue Duan (Cornell University), Xuezixiang Li (UC Riverside), Jinghan Wang (UC Riverside), Heng Yin (UC Riverside)

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