2019 15th European Dependable Computing Conference (EDCC)最新文献_第2页

Enabling Security-by-Design in Smart Grids: An Architecture-Based Approach 在智能电网中实现设计安全:一种基于体系结构的方法

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00042

Helder Aranha, M. Masi, Tanja Pavleska, G. Sellitto

{"title":"Enabling Security-by-Design in Smart Grids: An Architecture-Based Approach","authors":"Helder Aranha, M. Masi, Tanja Pavleska, G. Sellitto","doi":"10.1109/EDCC.2019.00042","DOIUrl":"https://doi.org/10.1109/EDCC.2019.00042","url":null,"abstract":"Energy Distribution Grids are considered critical infrastructure, hence the Distribution System Operators (DSOs) have developed sophisticated engineering practices to improve their resilience. Over the last years, due to the \"Smart Grid\" evolution, this infrastructure has become a distributed system where prosumers (the consumers who produce and share surplus energy through the grid) can plug in distributed energy resources (DERs) and manage a bi-directional flow of data and power enabled by an advanced IT and control infrastructure. This introduces new challenges, as the prosumers possess neither the skills nor the knowledge to assess the risk or secure the environment from cyber-threats. We propose a simple and usable approach based on the Reference Model of Information Assurance & Security (RMIAS), to support the prosumers in the selection of cybesecurity measures. The purpose is to reduce the risk of being directly targeted and to establish collective responsibility among prosumers as grid gatekeepers. The framework moves from a simple risk analysis based on security goals to providing guidelines for the users for adoption of adequate security countermeasures. One of the greatest advantages of the approach is that it does not constrain the user to a specific threat model.","PeriodicalId":334498,"journal":{"name":"2019 15th European Dependable Computing Conference (EDCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128365481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Copyright 版权

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/edcc.2019.00003

引用次数: 0

Exploiting MDE for Platform-Independent Testing of Service Orchestrations 利用MDE进行服务编排的平台独立测试

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00037

Lucas Leal, Leonardo Montecchi, A. Ceccarelli, E. Martins

引用次数: 1

Model-Free Detection of Cyberattacks on Voltage Control in Distribution Grids 配电网电压控制网络攻击的无模型检测

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00041

Mohammed S. Kemal, Wissam Aoudi, R. Olsen, M. Almgren, H. Schwefel

引用次数: 5

FailViz: A Tool for Visualizing Fault Injection Experiments in Distributed Systems FailViz:分布式系统故障注入实验可视化工具

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00036

Domenico Cotroneo, L. Simone, Pietro Liguori, R. Natella, N. Bidokhti

引用次数: 6

Assessment of a Method for Detecting Process Anomalies Using Digital-Twinning 一种利用数字孪生检测过程异常的方法的评估

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00031

Gayathri Sugumar, A. Mathur

引用次数: 3

A Fast and Efficient Fault Tree Analysis Using Approximate Computing 基于近似计算的快速高效故障树分析

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00019

S. Hashemi, Amir M. Hajisadeghi, H. Zarandi, S. Pour-Mozafari

{"title":"A Fast and Efficient Fault Tree Analysis Using Approximate Computing","authors":"S. Hashemi, Amir M. Hajisadeghi, H. Zarandi, S. Pour-Mozafari","doi":"10.1109/EDCC.2019.00019","DOIUrl":"https://doi.org/10.1109/EDCC.2019.00019","url":null,"abstract":"Fault tree analysis is one of the most widely used methods in reliability calculation and failure probability analysis. Although fault tree analysis is a popular method, its simulation is time-consuming. Therefore, speeding up fault tree simulations is essential for designers to calculate reliability. Several studies that reduced the mentioned simulation time just considered run-time and accuracy as effective parameters; however, power consumption and area efficiency are key parameters in most of the analyses. In this paper, we present a new method which utilizes approximate computing to mitigate the fault tree analysis simulation time, while considering accuracy, area efficiency, and power consumption as effective parameters. This method is capable of analyzing not only static fault trees but also dynamic fault trees. To do so, first, we describe a fault tree model by hardware description language (VHDL), then substitute its time-consuming arithmetic components including adders and multipliers with fast approximate hardware and eventually measure its reliability through Monte Carlo simulation. Experimental results reveal that compared to the best-related works, on average, we have decreased the emulation time by 15.2% and improved power consumption and circuit area by 61.9%, 68.8%, respectively with negligible inaccuracy.","PeriodicalId":334498,"journal":{"name":"2019 15th European Dependable Computing Conference (EDCC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125239656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Towards Quantification of Assurance for Learning-Enabled Components 面向可学习组件的量化保证

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00021

Erfan Asaadi, E. Denney, Ganesh J. Pai

{"title":"Towards Quantification of Assurance for Learning-Enabled Components","authors":"Erfan Asaadi, E. Denney, Ganesh J. Pai","doi":"10.1109/EDCC.2019.00021","DOIUrl":"https://doi.org/10.1109/EDCC.2019.00021","url":null,"abstract":"Perception, localization, planning, and control, high-level functions often organized in a so-called pipeline, are amongst the core building blocks of modern autonomous (ground, air, and underwater) vehicle architectures. These functions are increasingly being implemented using learning-enabled components (LECs), i.e., (software) components leveraging knowledge acquisition and learning processes such as deep learning. Providing quantified component-level assurance as part of a wider (dynamic) assurance case can be useful in supporting both pre-operational approval of LECs (e.g., by regulators), and runtime hazard mitigation, e.g., using assurance-based failover configurations. This paper develops a notion of assurance for LECs based on i) identifying the relevant dependability attributes, and ii) quantifying those attributes and the associated uncertainty, using probabilistic techniques. We give a practical grounding for our work using an example from the aviation domain: an autonomous taxiing capability for an unmanned aircraft system (UAS), focusing on the application of LECs as sensors in the perception function. We identify the applicable quantitative measures of assurance, and characterize the associated uncertainty using a non-parametric Bayesian approach, namely Gaussian process regression. We additionally discuss the relevance and contribution of LEC assurance to system-level assurance, the generalizability of our approach, and the associated challenges.","PeriodicalId":334498,"journal":{"name":"2019 15th European Dependable Computing Conference (EDCC)","volume":"1 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131847023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

On the Evaluation Measures for Machine Learning Algorithms for Safety-Critical Systems 安全关键系统机器学习算法评价方法研究

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00035

M. Gharib, A. Bondavalli

{"title":"On the Evaluation Measures for Machine Learning Algorithms for Safety-Critical Systems","authors":"M. Gharib, A. Bondavalli","doi":"10.1109/EDCC.2019.00035","DOIUrl":"https://doi.org/10.1109/EDCC.2019.00035","url":null,"abstract":"The ability of Machine Learning (ML) algorithms to learn and work with incomplete knowledge has motivated many system manufacturers to include such algorithms in their products. However, some of these systems can be described as Safety-Critical Systems (SCS) since their failure may cause injury or even death to humans. Therefore, the performance of ML algorithms with respect to the safety requirements of such systems must be evaluated before they are used in their operational environment. Although there exist several measures that can be used for evaluating the performance of ML algorithms, most of these measures focus mainly on some properties of interest in the domains where they were developed. For example, Recall, Precision and F-Factor are, usually, used in Information Retrieval (IR) domain, and they mainly focus on correct predictions with less emphasis on incorrect predictions, which are very important in SCS. Accordingly, such measures need to be tuned to fit the needs for evaluating the safe performance of ML algorithms. This position paper presents the authors’ view on the inadequacy of existing measures, and it proposes a new set of measures to be used for the evaluation of the safe performance of ML algorithms.","PeriodicalId":334498,"journal":{"name":"2019 15th European Dependable Computing Conference (EDCC)","volume":"600 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116290345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Facing Cyber-Physical Security Threats by PSIM-SIEM Integration PSIM-SIEM集成应对网络物理安全威胁

2019 15th European Dependable Computing Conference (EDCC) Pub Date : 2019-09-01 DOI: 10.1109/EDCC.2019.00026

Flavio Frattini, Ugo Giordano, V. Conti

引用次数: 5