Xiaofei Xie

TL;DR: DeepHunter, an automated fuzz testing framework for hunting potential defects of general-purpose DNNs, performs metamorphic mutation to generate new semantically preserved tests, and leverages multiple plugable coverage criteria as feedback to guide the test generation from different perspectives.

TL;DR: The method reveals the potential threats to the DNN-based DR automated diagnosis and can definitely benefit the development of exposure-robust automated DR diagnosis method in the future.

TL;DR: Wang et al. as mentioned in this paper proposed principled guidelines to assess the quality of five explanation approaches by designing three critical quantitative metrics to measure their stability, robustness, and effectiveness, and collected five widely-used malware datasets and applied the explanation approaches on them in two tasks, including malware detection and familial identification.

TL;DR: A loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest as inputs and summarizes path-sensitive loop effects on the variables ofinterest, and can significantly outperform the state-of-the-art tools for loop program verification.

TL;DR: This paper proposes the adversarial denoise attack aiming to simultaneously denoise input images while fooling DNNs and identifies a totally new task that stealthily embeds attacks inside image denoising module widely deployed in multimedia devices as an image post-processing operation.