49 citations · 60 across the 11 of their papers we have counts for
12 papers
Conflict Extraction in Probabilistic Datalog Analyses
Siyu Chen, Chungha Sung, Xuyang Li +1
Probabilistic extensions of Datalog enable static analyses such as pointer analysis, data race detection, and side-channel analysis to rank alarms by likelihood, but this added exp…
Probabilistic Inference for Datalog with Correlated Inputs
Jingbo Wang, Shashin Halalingaiah, Weiyi Chen +2
Probabilistic extensions of logic programming languages, such as ProbLog, integrate logical reasoning with probabilistic inference to evaluate probabilities of output relations; ho…
Efficient Symbolic Execution of Software under Fault Attacks
Yuzhou Fang, Chenyu Zhou, Jingbo Wang +1
We propose a symbolic execution method for analyzing the safety of software under fault attacks both accurately and efficiently. Fault attacks leverage physically injected hardware…
An Incremental Algorithm for Algebraic Program Analysis
Chenyu Zhou, Yuzhou Fang, Jingbo Wang +1
We propose a method for conducting algebraic program analysis (APA) incrementally in response to changes of the program under analysis. APA is a program analysis paradigm that cons…
FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks
Brian Hyeongseok Kim, Jingbo Wang, Chao Wang
We propose a method for formally certifying and quantifying individual fairness of deep neural networks (DNN). Individual fairness guarantees that any two individuals who are ident…
Certifying the Fairness of KNN in the Presence of Dataset Bias
Yannan Li, Jingbo Wang, Chao Wang
We propose a method for certifying the fairness of the classification result of a widely used supervised learning algorithm, the k-nearest neighbors (KNN), under the assumption tha…
Systematic Testing of the Data-Poisoning Robustness of KNN
Yannan Li, Jingbo Wang, Chao Wang
Data poisoning aims to compromise a machine learning based software component by contaminating its training set to change its prediction results for test inputs. Existing methods f…
Data-Driven Synthesis of Provably Sound Side Channel Analyses
Jingbo Wang, Chungha Sung, Mukund Raghothaman +1
We propose a data-driven method for synthesizing a static analyzer to detect side-channel information leaks in cryptographic software. Compared to the conventional way of manually…
NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation
Brandon Paulsen, Jingbo Wang, Jiawei Wang +1
As neural networks make their way into safety-critical systems, where misbehavior can lead to catastrophes, there is a growing interest in certifying the equivalence of two structu…
ReluDiff: Differential Verification of Deep Neural Networks
Brandon Paulsen, Jingbo Wang, Chao Wang
As deep neural networks are increasingly being deployed in practice, their efficiency has become an important issue. While there are compression techniques for reducing the network…
Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems
Meng Wu, Jingbo Wang, Jyotirmoy Deshmukh +1
Cyber-physical systems are often safety-critical in that violations of safety properties may lead to catastrophes. We propose a method to enforce the safety of systems with real-va…
Mitigating Power Side Channels during Compilation
Jingbo Wang, Chungha Sung, Chao Wang
The code generation modules inside modern compilers such as GCC and LLVM, which use a limited number of CPU registers to store a large number of program variables, may introduce si…