133 citations · 274 across the 15 of their papers we have counts for
15 papers
An Empirical Study of Malicious Code In PyPI Ecosystem
Wenbo Guo, Zhengzi Xu, Chengwei Liu +3
PyPI provides a convenient and accessible package management platform to developers, enabling them to quickly implement specific functions and improve work efficiency. However, the…
Inferring Private Personal Attributes of Virtual Reality Users from Head and Hand Motion Data
Vivek Nair, Christian Rack, Wenbo Guo +8
Motion tracking "telemetry" data lies at the core of nearly all modern virtual reality (VR) and metaverse experiences. While generally presumed innocuous, recent studies have demon…
In Search of netUnicorn: A Data-Collection Platform to Develop Generalizable ML Models for Network Security Problems
Roman Beltiukov, Wenbo Guo, Arpit Gupta +1
The remarkable success of the use of machine learning-based solutions for network security problems has been impeded by the developed ML models' inability to maintain efficacy when…
Unique Identification of 50,000+ Virtual Reality Users from Head & Hand Motion Data
Vivek Nair, Wenbo Guo, Justus Mattern +4
With the recent explosive growth of interest and investment in virtual reality (VR) and the so-called "metaverse," public attention has rightly shifted toward the unique security a…
Metal-bonded perovskite lead hydride with phonon-mediated superconductivity up to 46 K under atmospheric pressure
Yong He, Juan Du, Shi-ming Liu +7
In the search for high-temperature superconductivity in hydrides, a plethora of multi-hydrogen superconductors have been theoretically predicted, and some have been synthesized exp…
QPanda: high-performance quantum computing framework for multiple application scenarios
Menghan Dou, Tianrui Zou, Yuan Fang +8
With the birth of Noisy Intermediate Scale Quantum (NISQ) devices and the verification of "quantum supremacy" in random number sampling and boson sampling, more and more fields hop…
Are Shortest Rationales the Best Explanations for Human Understanding?
Hua Shen, Tongshuang Wu, Wenbo Guo +1
Existing self-explaining models typically favor extracting the shortest possible rationales - snippets of an input text "responsible for" corresponding output - to explain the mode…
BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning
Lun Wang, Zaynah Javed, Xian Wu +3
Recent research has confirmed the feasibility of backdoor attacks in deep reinforcement learning (RL) systems. However, the existing attacks require the ability to arbitrarily modi…
Data-driven analysis of the electronic-structure factors controlling the work functions of perovskite oxides
Yihuang Xiong, Weinan Chen, Wenbo Guo +2
Tuning the work functions of materials is of practical interest for maximizing the performance of microelectronic and (photo)electrochemical devices, as the efficiency of these sys…
TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems
Wenbo Guo, Lun Wang, Xinyu Xing +2
A trojan backdoor is a hidden pattern typically implanted in a deep neural network. It could be activated and thus forces that infected model behaving abnormally only when an input…
Explaining Deep Learning Models - A Bayesian Non-parametric Approach
Wenbo Guo, Sui Huang, Yunzhe Tao +2
Understanding and interpreting how machine learning (ML) models make decisions have been a big challenge. While recent research has proposed various technical approaches to provide…
Towards Interrogating Discriminative Machine Learning Models
Wenbo Guo, Kaixuan Zhang, Lin Lin +2
It is oftentimes impossible to understand how machine learning models reach a decision. While recent research has proposed various technical approaches to provide some clues as to…
Learning Adversary-Resistant Deep Neural Networks
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Deep neural networks (DNNs) have proven to be quite effective in a vast array of machine learning tasks, with recent examples in cyber security and autonomous vehicles. Despite the…
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks
Qinglong Wang, Wenbo Guo, Alexander G. Ororbia +6
Deep neural networks have proven to be quite effective in a wide variety of machine learning tasks, ranging from improved speech recognition systems to advancing the development of…
Adversary Resistant Deep Neural Networks with an Application to Malware Detection
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Beyond its highly publicized victories in Go, there have been numerous successful applications of deep learning in information retrieval, computer vision and speech recognition. In…