Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Matthew Jagielski"'
Publikováno v:
Proceedings on Privacy Enhancing Technologies. 2023:211-232
A large body of research has shown that machine learning models are vulnerable to membership inference (MI) attacks that violate the privacy of the participants in the training data. Most MI research focuses on the case of a single standalone model,
Publikováno v:
CCS
Machine learning systems are deployed in critical settings, but they might fail in unexpected ways, impacting the accuracy of their predictions. Poisoning attacks against machine learning induce adversarial modification of data used by a machine lear
Publikováno v:
Journal of Cryptology. 34
Secure channel establishment protocols such as Transport Layer Security (TLS) are some of the most important cryptographic protocols, enabling the encryption of Internet traffic. Reducing latency (the number of interactions between parties before enc
Publikováno v:
Advances in Cryptology – CRYPTO 2020 ISBN: 9783030568764
CRYPTO (3)
CRYPTO (3)
We argue that the machine learning problem of model extraction is actually a cryptanalytic problem in disguise, and should be studied as such. Given oracle access to a neural network, we introduce a differential attack that can efficiently steal the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5340d452785ab9d68861fe9fec7811fc
https://doi.org/10.1007/978-3-030-56877-1_7
https://doi.org/10.1007/978-3-030-56877-1_7
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030299583
ESORICS (1)
ESORICS (1)
Secure channel establishment protocols such as TLS are some of the most important cryptographic protocols, enabling the encryption of Internet traffic. Reducing the latency (the number of interactions between parties) in such protocols has become an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::068c9446d7a481b15ad6d272c5f3cc9a
https://doi.org/10.1007/978-3-030-29959-0_20
https://doi.org/10.1007/978-3-030-29959-0_20
Autor:
Eunsuk Kang, Chung-Wei Lin, Shinichi Shiraishi, Matthew Jagielski, Qi Zhu, Cristina Nita-Rotaru, Bowen Zheng, Hengyi Liang
Publikováno v:
ICCAD
Connected vehicle applications such as autonomous intersections and intelligent traffic signals have shown great promises in improving transportation safety and efficiency. However, security is a major concern in these systems, as vehicles and surrou
Publikováno v:
2018 IEEE Symposium on Security and Privacy (SP)
IEEE Symposium on Security and Privacy
IEEE Symposium on Security and Privacy
As machine learning becomes widely used for automated decisions, attackers have strong incentives to manipulate the results and models generated by machine learning algorithms. In this paper, we perform the first systematic study of poisoning attacks