This paper considers security requirements for automotive on-board networks and describes the processes used for identifying and prioritizing such requirements. The security engineering process starts from use cases for automotive on-board networks that require wireless communication interfaces and involves an investigation of security threat scenarios and the assessment of the relative risks associated with the threats
The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors. Automatically assessing the quality of face data in terms of biometric utility can thus be useful to detect low-quality data and make decisions accordingly. This survey provides an overview of the face image quality assessment literature, which predominantly focuses on visible wavelength face image input. A trend towards deep learning based methods is observed, including notable conceptual differences among the recent approaches, such as the integration of quality assessment into face recognition models. Besides image selection, face image quality assessment can also be used in a variety of other application scenarios, which are discussed herein. Open issues and challenges are pointed out, i.a. highlighting the importance of comparability for algorithm evaluations, and the challenge for future work to create deep learning approaches that are interpretable in addition to providing accurate utility predictions.
NIST Fingerprint Image Quality ( 2) is open source software that links image quality of optical and ink 500 pixel per inch fingerprints to operational recognition performance. This allows quality values to be tightly defined and then numerically calibrated, which in turn allows for the standardization needed to support a worldwide deployment of fingerprint sensors with universally interpretable image qualities.2 quality features are formally standardized as part of ISO/IEC 29794-4 and serve as the reference implementation of the standard.
Abstract. In this paper, we present an algorithm for generating test purpose descriptions in form of MSC's from a given labeled event structure that represents the behavior of a system of asynchronously communicating extended finite state machines. The labeled event structure is a non-interleaving behavior model describing the behavior of a system in terms of the partial ordering of events.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.