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procd: A Privacy-preserving Robust Implementation to ...
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由 F Deifuß 著作2021 — procd: A Privacy-preserving Robust Implementation to Discover Contacts in Social Networks · Fabian Deifuß, Cornelius Ihle, Moritz Schubotz, Bela ...
procd: A Privacy-preserving Robust Implementation to ...
Universität Regensburg
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Universität Regensburg
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由 F Deifuß 著作2021 — procd is a trustless solution that requires neither plaintext numbers nor hashes of single phone num- bers to retrieve contacts. Instead, we ...
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procd: A Privacy-preserving Robust Implementation to Discover ...
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We present a privacy-preserving protocol to anonymously collect information about a social graph. The typical application of our protocol is Bluetooth-enabled “ ...
procd: A Privacy-preserving Robust Implementation to ...
Georg-August Universität Göttingen
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Georg-August Universität Göttingen
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由 F Deifuß 著作2021 — In case of a server's corruption, all contacts are either directly available in plaintext or can be unmasked using a simple dictionary attack. To solve this ...
Fabian Deifuß
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To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active.
Cornelius Ihle
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Incentive mechanisms in peer-to-peer networks—a systematic ... procd: A privacy-preserving robust implementation to discover contacts in social networks.
Cornelius Ihle
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Incentive mechanisms in peer-to-peer networks—a systematic ... procd: A privacy-preserving robust implementation to discover contacts in social networks.
Dr. Moritz Schubotz | GRO.publications
Georg-August Universität Göttingen
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Georg-August Universität Göttingen
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"procd: A Privacy-preserving Robust Implementation to Discover Contacts in Social Networks." In Information between Data and Knowledge, edited by Werner ...
Preserving the User's Privacy in Social Networking Sites
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2024年11月21日 — Even though these privacy-preserving mechanisms represent a certain improvement with respect to the user's privacy, they have been criticized in ...
A deep decentralized privacy-preservation framework for ...
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由 SA Frimpong 著作2024 — When tested on the NSL-KDD dataset, our framework achieves 98.79% accuracy, a 10% false alarm rate, and a 98.99% detection rate, surpassing existing methods.