News

Undetectable Backdoors in Machine-Learning Models

New paper: “Planting Undetectable Backdoors in Machine Learning Models“:

Abstract: Given the computational cost and technical expertise required to train machine learning models, users may delegate the task of learning to a service provider. We show how a malicious learner can plant an undetectable backdoor into a classifier. On the surface, such a backdoored classifier behaves normally, but in reality, the learner maintains a mechanism for changing the classification of any input, with only a slight perturbation. Importantly, without the appropriate “backdoor key”, the mechanism is hidden and cannot be detected by any computationally-bounded observer. We demonstrate two frameworks for planting undetectable backdoors, with incomparable guarantees. …

Conti’s Ransomware Toll on the Healthcare Industry

Conti — one of the most ruthless and successful Russian ransomware groups — publicly declared during the height of the COVID-19 pandemic that it would refrain from targeting healthcare providers. But new information confirms this pledge was always a lie, and that Conti has launched more than 200 attacks against hospitals and other healthcare facilities since first surfacing in 2018 under the name “Ryuk.”