Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles

no code implementations • 20 May 2021 • Luiz Giovanini, Fabrício Ceschin, Mirela Silva, Aokun Chen, Ramchandra Kulkarni, Sanjay Banda, Madison Lysaght, Heng Qiao, Nikolaos Sapountzis, Ruimin Sun, Brandon Matthews, Dapeng Oliver Wu, André Grégio, Daniela Oliveira

This paper investigates whether computer usage profiles comprised of process-, network-, mouse-, and keystroke-related events are unique and consistent over time in a naturalistic setting, discussing challenges and opportunities of using such profiles in applications of continuous authentication.

valid

ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks

no code implementations • 11 Nov 2020 • Zhichuang Sun, Ruimin Sun, Changming Liu, Amrita Roy Chowdhury, Long Lu, Somesh Jha

ShadowNet protects the model privacy with Trusted Execution Environment (TEE) while securely outsourcing the heavy linear layers of the model to the untrusted hardware accelerators.

Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps

1 code implementation • 18 Feb 2020 • Zhichuang Sun, Ruimin Sun, Long Lu, Alan Mislove

We found that, alarmingly, 41% of ML apps do not protect their models at all, which can be trivially stolen from app packages.

Face Recognition Malware Detection

Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection

no code implementations • 4 Dec 2017 • Ruimin Sun, Xiaoyong Yuan, Pan He, Qile Zhu, Aokun Chen, Andre Gregio, Daniela Oliveira, Xiaolin Li

Existing malware detectors on safety-critical devices have difficulties in runtime detection due to the performance overhead.

General Classification Malware Detection