26 citations · 58 across the 7 of their papers we have counts for
7 papers
D-Box: DMA-enabled Compartmentalization for Embedded Applications
Alejandro Mera, Yi Hui Chen, Ruimin Sun +2
Embedded and Internet-of-Things (IoT) devices have seen an increase in adoption in many domains. The security of these devices is of great importance as they are often used to cont…
Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles
Luiz Giovanini, Fabrício Ceschin, Mirela Silva +11
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…
ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks
Zhichuang Sun, Ruimin Sun, Changming Liu +3
With the increased usage of AI accelerators on mobile and edge devices, on-device machine learning (ML) is gaining popularity. Thousands of proprietary ML models are being deployed…
SoK: Attacks on Industrial Control Logic and Formal Verification-Based Defenses
Ruimin Sun, Alejandro Mera, Long Lu +1
Programmable Logic Controllers (PLCs) play a critical role in the industrial control systems. Vulnerabilities in PLC programs might lead to attacks causing devastating consequences…
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps
Zhichuang Sun, Ruimin Sun, Long Lu +1
On-device machine learning (ML) is quickly gaining popularity among mobile apps. It allows offline model inference while preserving user privacy. However, ML models, considered as…
A Praise for Defensive Programming: Leveraging Uncertainty for Effective Malware Mitigation
Ruimin Sun, Marcus Botacin, Nikolaos Sapountzis +6
A promising avenue for improving the effectiveness of behavioral-based malware detectors would be to combine fast traditional machine learning detectors with high-accuracy, but tim…
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection
Ruimin Sun, Xiaoyong Yuan, Pan He +5
Existing malware detectors on safety-critical devices have difficulties in runtime detection due to the performance overhead. In this paper, we introduce PROPEDEUTICA, a framework…