101 citations · 535 across the 27 of their papers we have counts for
5 papers · 1 filter
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans +5
Deploying machine learning models in production may allow adversaries to infer sensitive information about training data. There is a vast literature analyzing different types of in…
Bayesian Estimation of Differential Privacy
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople +6
Algorithms such as Differentially Private SGD enable training machine learning models with formal privacy guarantees. However, there is a discrepancy between the protection that su…
Dropbear: Machine Learning Marketplaces made Trustworthy with Byzantine Model Agreement
Alex Shamis, Peter Pietzuch, Antoine Delignat-Lavaud +2
Marketplaces for machine learning (ML) models are emerging as a way for organizations to monetize models. They allow model owners to retain control over hosted models by using clou…
CTR: Checkpoint, Transfer, and Restore for Secure Enclaves
Yoshimichi Nakatsuka, Ercan Ozturk, Alex Shamis +2
Hardware-based Trusted Execution Environments (TEEs) are becoming increasingly prevalent in cloud computing, forming the basis for confidential computing. However, the security goa…
Pre-hijacked accounts: An Empirical Study of Security Failures in User Account Creation on the Web
Avinash Sudhodanan, Andrew Paverd
The ubiquity of user accounts in websites and online services makes account hijacking a serious security concern. Although previous research has studied various techniques through…