228 citations · 329 across the 13 of their papers we have counts for
4 papers · 1 filter
Adversarial Examples and Metrics
Nico Döttling, Kathrin Grosse, Michael Backes +1
Adversarial examples are a type of attack on machine learning (ML) systems which cause misclassification of inputs. Achieving robustness against adversarial examples is crucial to…
Reaching Data Confidentiality and Model Accountability on the CalTrain
Zhongshu Gu, Hani Jamjoom, Dong Su +5
Distributed collaborative learning (DCL) paradigms enable building joint machine learning models from distrusting multi-party participants. Data confidentiality is guaranteed by re…
Confidential Inference via Ternary Model Partitioning
Zhongshu Gu, Heqing Huang, Jialong Zhang +5
Today's cloud vendors are competing to provide various offerings to simplify and accelerate AI service deployment. However, cloud users always have concerns about the confidentiali…
IDIoT: Securing the Internet of Things like it's 1994
David Barrera, Ian Molloy, Heqing Huang
Over 20 billion Internet of Things devices are set to come online by 2020. Protecting such a large number of underpowered, UI-less, network-connected devices will require a new sec…