2 research outputs found
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations
Deep learning models are widely used for image analysis. While they offer
high performance in terms of accuracy, people are concerned about if these
models inappropriately make inferences using irrelevant features that are not
encoded from the target object in a given image. To address the concern, we
propose a metamorphic testing approach that assesses if a given inference is
made based on irrelevant features. Specifically, we propose two novel
metamorphic relations to detect such inappropriate inferences. We applied our
approach to 10 image classification models and 10 object detection models, with
three large datasets, i.e., ImageNet, COCO, and Pascal VOC. Over 5.3% of the
top-5 correct predictions made by the image classification models are subject
to inappropriate inferences using irrelevant features. The corresponding rate
for the object detection models is over 8.5%. Based on the findings, we further
designed a new image generation strategy that can effectively attack existing
models. Comparing with a baseline approach, our strategy can double the success
rate of attacks
Trustworthiness in Mobile Cyber Physical Systems
Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS