27 citations · 34 across the 6 of their papers we have counts for
11 papers
VerIDeep: Verifying Integrity of Deep Neural Networks through Sensitive-Sample Fingerprinting
Zecheng He, Tianwei Zhang, Ruby B. Lee
Deep learning has become popular, and numerous cloud-based services are provided to help customers develop and deploy deep learning applications. Meanwhile, various attack techniqu…
Privacy-preserving Machine Learning through Data Obfuscation
Tianwei Zhang, Zecheng He, Ruby B. Lee
As machine learning becomes a practice and commodity, numerous cloud-based services and frameworks are provided to help customers develop and deploy machine learning applications.…
Practical and Scalable Security Verification of Secure Architectures
Jakub Szefer, Tianwei Zhang, Ruby B. Lee
We present a new and practical framework for security verification of secure architectures. Specifically, we break the verification task into external verification and internal ver…
Time Series Segmentation through Automatic Feature Learning
Wei-Han Lee, Jorge Ortiz, Bongjun Ko +1
Internet of things (IoT) applications have become increasingly popular in recent years, with applications ranging from building energy monitoring to personal health tracking and ac…
Blind De-anonymization Attacks using Social Networks
Wei-Han Lee, Changchang Liu, Shouling Ji +2
It is important to study the risks of publishing privacy-sensitive data. Even if sensitive identities (e.g., name, social security number) were removed and advanced data perturbati…
Implicit Smartphone User Authentication with Sensors and Contextual Machine Learning
Wei-Han Lee, Ruby B. Lee
Authentication of smartphone users is important because a lot of sensitive data is stored in the smartphone and the smartphone is also used to access various cloud data and service…