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pro vyhledávání: '"DÍAZ, CLAUDIA"'
Continuous-time decryption mixnets can anonymously route data packets with end to end latency that can be as low as a second, making them usable for a variety of applications. Such mixnets however lack verifiable reliability properties that ensure th
Externí odkaz:
http://arxiv.org/abs/2406.06760
Cryptocurrency systems can be subject to deanonimization attacks by exploiting the network-level communication on their peer-to-peer network. Adversaries who control a set of colluding node(s) within the peer-to-peer network can observe transactions
Externí odkaz:
http://arxiv.org/abs/2201.11860
Autor:
Kohls, Katharina, Diaz, Claudia
We tackle the challenge of reliably determining the geo-location of nodes in decentralized networks, considering adversarial settings and without depending on any trusted landmarks. In particular, we consider active adversaries that control a subset
Externí odkaz:
http://arxiv.org/abs/2105.11928
Autor:
Berdugo-Díaz, Claudia E., Manetsch, Melissa T., Lee, Jieun, Sik Yun, Yang, Yancey, David F., Rozeveld, Steve J., Luo, Jing, Chen, Xue, Flaherty, David W.
Publikováno v:
In Journal of Catalysis February 2024 430
In this paper we present LiM ("Less is More"), a malware classification framework that leverages Federated Learning to detect and classify malicious apps in a privacy-respecting manner. Information about newly installed apps is kept locally on users'
Externí odkaz:
http://arxiv.org/abs/2007.08319
Akademický článek
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Autor:
Ruiz-Diaz, Claudia Patricia, Verle Rodrigues, José C., Miro-Rivera, Erick, Diaz-Vazquez, Liz M.
Publikováno v:
In Food Chemistry Advances October 2023 2