Voting margin: A scheme for error-tolerant k nearest neighbors classifiers for machine learning

Machine learning (ML) techniques such as classifiers are used in many applications, some of which are related to safety or critical systems. In this case, correct processing is a strict requirement and thus ML algorithms (such as for classification) must be error tolerant. A naive approach to implement error tolerant classifiers is to resort to general protection techniques such as modular redundancy. However, modular redundancy incurs in large overheads in many metrics such as hardware utilization and power consumption that may not be acceptable in applications that run on embedded or battery powered systems. Another option is to exploit the algorithmic properties of the classifier to provide protection and error tolerance at a lower cost. This paper explores this approach for a widely used classifier, the k Nearest Neighbors ( k NNs), and proposes an efficient scheme to protect it against errors. The proposed technique is based on a time-based modular redundancy (TBMR) scheme. The proposed scheme exploits the intrinsic redundancy of k NNs to drastically reduce the number of re-computations needed to detect errors. This is achieved by noting that when voting among the k nearest neighbors has a large majority, an error in one of the voters cannot change the result, hence voting margin (VM). This observation has been refined and extended in the proposed VM scheme to also avoid re-computations in some cases in which the majority vote is tight. The VM scheme has been implemented and evaluated with publicly available data sets that cover a wide range of applications and settings. The results show that by exploiting the intrinsic redundancy of the classifier, the proposed scheme is able to reduce the cost compared to modular redundancy by more than 60 percent in all configurations evaluated.Pedro Reviriego and Josée Alberto Hernández would like to acknowledge the support of the TEXEO project TEC2016-80339-R funded by the Spanish Ministry of Economy and Competitivity and of the Madrid Community research project TAPIR-CM Grant no. P2018/TCS-4496

Methodology to accelerate diagnostic coverage assessment: MADC

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2016.Os veículos da atualidade vêm integrando um número crescente de eletrônica embarcada, com o objetivo de permitir uma experiência mais segura aos motoristas. Logo, a garantia da segurança física é um requisito que precisa ser observada por completo durante o processo de desenvolvimento. O padrão ISO 26262 provê medidas para garantir que esses requisitos não sejam negligenciados. Injeção de falhas é fortemente recomendada quando da verificação do funcionamento dos mecanismos de segurança implementados, assim como sua capacidade de cobertura associada ao diagnóstico de falhas existentes. A análise exaustiva não é obrigatória, mas evidências de que o máximo esforço foi feito para acurar a cobertura de diagnóstico precisam ser apresentadas, principalmente durante a avalição dos níveis de segurança associados a arquitetura implementada em hardware. Estes níveis dão suporte às alegações de que o projeto obedece às métricas de segurança da integridade física exigida em aplicações automotivas. Os níveis de integridade variam de A à D, sendo este último o mais rigoroso. Essa Tese explora o estado-da-arte em soluções de verificação, e tem por objetivo construir uma metodologia que permita acelerar a verificação da cobertura de diagnóstico alcançado. Diferentemente de outras técnicas voltadas à aceleração de injeção de falhas, a metodologia proposta utiliza uma plataforma de hardware dedicada à verificação, com o intuito de maximizar o desempenho relativo a simulação de falhas. Muitos aspectos relativos a ISO 26262 são observados de forma que a presente contribuição possa ser apreciada no segmento automotivo. Por fim, uma arquitetura OpenRISC é utilizada para confirmar os resultados alcançados com essa solução proposta pertencente ao estado-da-arte.Abstract : Modern vehicles are integrating a growing number of electronics to provide a safer experience for the driver. Therefore, safety is a non-negotiable requirement that must be considered through the vehicle development process. The ISO 26262 standard provides guidance to ensure that such requirements are implemented. Fault injection is highly recommended for the functional verification of safety mechanisms or to evaluate their diagnostic coverage capability. An exhaustive analysis is not required, but evidence of best effort through the diagnostic coverage assessment needs to be provided when performing quantitative evaluation of hardware architectural metrics. These metrics support that the automotive safety integrity level ? ranging from A (lowest) to D (strictest) levels ? was obeyed. This thesis explores the most advanced verification solutions in order to build a methodology to accelerate the diagnostic coverage assessment. Different from similar techniques for fault injection acceleration, the proposed methodology does not require any modification of the design model to enable acceleration. Many functional safety requisites in the ISO 26262 are considered thus allowing the contribution presented to be a suitable solution for the automotive segment. An OpenRISC architecture is used to confirm the results achieved by this state-of-the-art solution

Modellbasierte Entwicklung funktional sicherer Hardware nach ISO 26262

The compliance with functional safety according to the standard ISO 26262 in context of the increasing electrification of road vehicles is a significant challenge. This work provides a concept and methodology for the model-based development of functional safe hardware. This is characterized by the description of hardware designs, annotation of failure data and performing the demanded safety evaluations

Modellbasierte Entwicklung funktional sicherer Hardware nach ISO 26262

Die Absicherung von funktionaler Sicherheit nach dem Standard ISO 26262 ist im Kontext der zunehmenden Elektrifizierung von Fahrzeugen ein herausforderndes Unterfangen. Diese Arbeit liefert ein Konzept und eine Vorgehensweise zur modellbasierten Entwicklung funktional sicherer Hardware. Diese zeichnet sich durch die Beschreibung von Hardwaredesigns, Anreicherung um Fehlerinformationen sowie Ausführung der geforderten Sicherheitsevaluationen aus