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Articles

PrivacyGo: Privacy-Preserving Ad Measurement with Multidimensional Intersection

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By Shikun Zhang, Wen-jie Lu, Donghang Lu, Haohao Qian
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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RPM: Robust Anonymity at Scale

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By Donghang Lu, Aniket Kate
| eprint.iacr.org
Paper 2022/1037 RPM: Robust Anonymity at Scale , Purdue University West Lafayette , Purdue University West Lafayette Abstract This work presents RPM, a scalable anonymous communication protocol suite using secure multiparty computation (MPC) with the offline-online model.
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SIM: Secure Interval Membership Testing and Applications to Secure Comparison

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By Albert Yu, Hemanta K. Maji, Donghang Lu, Aniket Kate
| eprint.iacr.org
Paper 2022/1023 SIM: Secure Interval Membership Testing and Applications to Secure Comparison , Purdue University West Lafayette , Purdue University West Lafayette , Purdue University West Lafayette , Purdue University West Lafayette Abstract The offline-online model is a leading paradigm for practical secure multi-party computation (MPC) protocol design that has successfully reduced the overhead for several prevalent privacy-preserving computation functionalities common to diverse...
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