6,760 research outputs found
DPN -- Dependability Priority Numbers
This paper proposes a novel model-based approach to combine the quantitative
dependability (safety, reliability, availability, maintainability and IT
security) analysis and trade-off analysis. The proposed approach is called DPN
(Dependability Priority Numbers) and allows the comparison of different actual
dependability characteristics of a systems with its target values and evaluates
them regarding trade-off analysis criteria. Therefore, the target values of
system dependability characteristics are taken as requirements, while the
actual value of a specific system design are provided by quantitative and
qualitative dependability analysis (FHA, FMEA, FMEDA, of CFT-based FTA). The
DPN approach evaluates the fulfillment of individual target requirements and
perform trade-offs between analysis objectives. We present the workflow and
meta-model of the DPN approach, and illustrate our approach using a case study
on a brake warning contact system. Hence, we demonstrate how the model-based
DPNs improve system dependability by selecting the project crucial dependable
design alternatives or measures
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Application of Advanced Early Warning Systems with Adaptive Protection
This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers
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Evaluating the resilience and security of boundaryless, evolving socio-technical Systems of Systems
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A survey on online monitoring approaches of computer-based systems
This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use
Multi-Dimensional Model Based Engineering for Performance Critical Computer Systems Using the AADL
International audienceThe Architecture Analysis & Design Language, (AADL), Society of Automotive Engineers (SAE), AS5506, was developed to support quantitative analysis of the runtime architecture of the embedded software system in computer systems with multiple critical operational properties, such as responsiveness, safety-criticality, security, and reliability by allowing a model of the system to be annotated with information relevant to each of these quality concerns and AADL to be extended with analysis-specific properties. It supports modelling of the embedded software runtime architecture, the computer system hardware, and the interface to the physical environment of embedded computer systems and system of systems. It was designed to support a full Model Based Engineering lifecycle including system specification, analysis, system tuning, integration, and upgrade by supporting modelling and analysis at multiple levels of fidelity. A system can be automatically integrated from AADL models when fully specified and when source code is provided for the software components
Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks
Despite the great achievements of deep neural networks (DNNs), the
vulnerability of state-of-the-art DNNs raises security concerns of DNNs in many
application domains requiring high reliability.We propose the fault sneaking
attack on DNNs, where the adversary aims to misclassify certain input images
into any target labels by modifying the DNN parameters. We apply ADMM
(alternating direction method of multipliers) for solving the optimization
problem of the fault sneaking attack with two constraints: 1) the
classification of the other images should be unchanged and 2) the parameter
modifications should be minimized. Specifically, the first constraint requires
us not only to inject designated faults (misclassifications), but also to hide
the faults for stealthy or sneaking considerations by maintaining model
accuracy. The second constraint requires us to minimize the parameter
modifications (using L0 norm to measure the number of modifications and L2 norm
to measure the magnitude of modifications). Comprehensive experimental
evaluation demonstrates that the proposed framework can inject multiple
sneaking faults without losing the overall test accuracy performance.Comment: Accepted by the 56th Design Automation Conference (DAC 2019
From measures to conclusions using Analytic Hierarchy Process in dependability benchmarkind
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Dependability benchmarks are aimed at comparing and selecting alternatives in application domains where faulty conditions are present. However, despite its importance and intrinsic complexity, a rigorous decision process has not been defined yet. As a result, benchmark conclusions may vary from one evaluator to another, and often, that process is vague and hard to follow, or even nonexistent. This situation affects the repeatability and reproducibility of that analysis process, making difficult the cross-comparison of results between works. To mitigate these problems, this paper proposes the integration of the analytic hierarchy process (AHP), a widely used multicriteria decision-making technique, within dependability benchmarks. In addition, an assisted pairwise comparison approach is proposed to automate those aspects of AHP that rely on judgmental comparisons, thus granting consistent, repeatable, and reproducible conclusions. Results from a dependability benchmark for wireless sensor networks are used to illustrate and validate the proposed approach.This work was supported in part by the Spanish Project ARENES under Grant TIN2012-38308-C02-01 and in part by the Programa de Ayudas de Investigacion y Desarrollo through the Universitat Politecnica de Valencia, Valencia, Spain. The Associate Editor coordinating the review process was Dr. Dario Petri.MartĂnez Raga, M.; AndrĂ©s MartĂnez, DD.; Ruiz GarcĂa, JC.; Friginal LĂłpez, J. (2014). From measures to conclusions using Analytic Hierarchy Process in dependability benchmarkind. IEEE Transactions on Instrumentation and Measurement. 63(11):2548-2556. https://doi.org/10.1109/TIM.2014.2348632S25482556631
Petri Nets for Smart Grids: The Story So Far
Since the energy domain is in a transformative shift towards sustainability,
the integration of new technologies and smart systems into traditional power
grids has emerged. As an effective approach, Petri Nets (PN) have been applied
to model and analyze the complex dynamics in Smart Grid (SG) environments.
However, we are currently missing an overview of types of PNs applied to
different areas and problems related to SGs. Therefore, this paper proposes
four fundamental research questions related to the application areas of PNs in
SGs, PNs types, aspects modelled by PNs in the identified areas, and the
validation methods in the evaluation. The answers to the research questions are
derived from a comprehensive and interdisciplinary literature analysis. The
results capture a valuable overview of PNs applications in the global energy
landscape and can offer indications for future research directions
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