27 citations · 44 across the 8 of their papers we have counts for
8 papers
TAPFixer: Automatic Detection and Repair of Home Automation Vulnerabilities based on Negated-property Reasoning
Yinbo Yu, Yuanqi Xu, Kepu Huang +1
Trigger-Action Programming (TAP) is a popular end-user programming framework in the home automation (HA) system, which eases users to customize home automation and control devices…
zPROBE: Zero Peek Robustness Checks for Federated Learning
Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani +3
Privacy-preserving federated learning allows multiple users to jointly train a model with coordination of a central server. The server only learns the final aggregation result, thu…
A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning
Yinbo Yu, Jiajia Liu, Shouqing Li +2
Deep reinforcement learning (DRL) has made significant achievements in many real-world applications. But these real-world applications typically can only provide partial observatio…
AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection
Huili Chen, Xinqiao Zhang, Ke Huang +1
This paper proposes AdaTest, a novel adaptive test pattern generation framework for efficient and reliable Hardware Trojan (HT) detection. HT is a backdoor attack that tampers with…
An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks
Xinqiao Zhang, Huili Chen, Ke Huang +1
With the surge of Machine Learning (ML), An emerging amount of intelligent applications have been developed. Deep Neural Networks (DNNs) have demonstrated unprecedented performance…
FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes
Paarth Neekhara, Shehzeen Hussain, Xinqiao Zhang +3
Deepfakes and manipulated media are becoming a prominent threat due to the recent advances in realistic image and video synthesis techniques. There have been several attempts at co…
Assessing Post-Disaster Damage from Satellite Imagery using Semi-Supervised Learning Techniques
Jihyeon Lee, Joseph Z. Xu, Kihyuk Sohn +8
To respond to disasters such as earthquakes, wildfires, and armed conflicts, humanitarian organizations require accurate and timely data in the form of damage assessments, which in…
AgileNet: Lightweight Dictionary-based Few-shot Learning
Mohammad Ghasemzadeh, Fang Lin, Bita Darvish Rouhani +2
The success of deep learning models is heavily tied to the use of massive amount of labeled data and excessively long training time. With the emergence of intelligent edge applicat…