2,414 research outputs found

    Simulation-based testing of highly configurable cyber-physical systems: automation, optimization and debugging

    Get PDF
    Sistema Ziber-Fisikoek sistema ziber digitalak sistema fisikoekin uztartzen dituzte. Sistema hauen aldakortasuna handitzen ari da erabiltzaileen hainbat behar betetzeko. Ondorioz, sistema ziber-fisikoa aldakorrak edota produktu lerroak ari dira garatzen eta sistema hauek milaka edo milioika konfiguraziotan konfiguratu daitezke. Sistema ziber-fisiko aldakorren test eta balidazioa prozesua garestia da, batez ere probatu beharreko konfigurazio kopuruaren ondorioz. Konfigurazio kopuru altuak sistemaren prototipo bat erabiltzea ezinezkoa egiten du. Horregatik, sistema ziber-fisiko aldagarriak simulazio modeloak erabilita probatzen dira. Hala ere, simulazio bidez sistema ziber-fisikoak probatzea erronka izaten jarraitzen du. Hasteko, simulazio denbora altua izaten da normalki, software-az aparte, sistema fisikoa simulatu behar delako. Sistema fisiko hau normalean modelo matematiko konplexuen bitartez modelatzen da, konputazionalki garestia delarik. Jarraitzeko, sistema ziber-fisikoek ingeniaritzaren domeinu ezberdinak dituzte tartean, adibidez mekanika edo elektronika. Domeinu bakoitzak bere simulazio erremienta erabiltzen du, eta erremienta guzti hauek interkonektatzeko ko-simulazioa erabiltzen da. Nahiz eta ko-simulazioa abantaila bat izan ematen duen flexibilitateagatik, simulagailu ezberdinen erabilerak simulazio denbora handiagotzen du. Azkenik, sistema ziber-fisikoak simulaziopean probatzean, probak maila ezberdinetan egin behar dira (adb., Model, Software eta Hardware-in-the-Loop mailak), eta honek, proba-kasuak exekutatzeko denbora handitzen du. Tesi honen helburua sistema ziber-fisiko aldakorren test jardunbideak hobetzea da, horretarako automatizazio, optimizazio eta arazketa metodoak proposatzen ditu. Automatizazioari dagokionez, lehenengo, erremienta-bidezko metodologia bat proposatzen da. Metodologia hau test sistema instantziak automatikoki sortzeko gai da, test sistema hauek sistema ziber-fisiko aldagarrien konfigurazioak automatikoki probatzeko gai dira (adb., test orakuluen bitartez). Bigarren, test frogak automatikoki sortzeko planteamendu bat proposatzen da helburu anitzeko bilaketa algoritmoak erabilita. Optimizazioari dagokionez, test frogen aukeraketarako planteamendu bat eta test frogen priorizaziorako beste planteamendu bat proposatzen dira, biak bilaketa alix goritmoak erabiliz, sistema ziber-fisiko aldakorrak test maila ezberdinetan probatzeko helburuarekin. Arazketari dagokionez, “espektroan oinarritutako falten lokalizazioa” izeneko teknika bat produktu lerroen testuingurura adaptatu da, eta faltak isolatzeko metodo bat proposatzen da. Honek, falta ezberdinak lokalizatzea errezten du ez bakarrik sistema ziber-fisiko aldakorretan, baizik eta edozein produktu lerrotan non “feature model” delako modeloak erabiltzen diren aldakortasuna kudeatzeko.Los sistemas cyber-físicos (CPSs) integran tecnologías digitales con procesos físicos. La variabilidad de estos sistemas está creciendo para responder a la demanda de diferentes clientes. Como consecuencia de ello, los CPSs están volviéndose configurables e incluso líneas de producto, lo que significa que pueden ser configurados en miles y millones de configuraciones. El testeo de sistemas cyber-físicos configurables es un proceso costoso, en general debido a la cantidad de configuraciones que han de ser testeadas. El número de configuraciones a testear hace imposible el uso de un prototipo del sistema. Por ello, los sistemas CPSs configurables están siendo testeadas utilizando modelos de simulación. Sin embargo, el testeo de sistemas cyber-físicos bajo simulación sigue siendo un reto. Primero, el tiempo de simulación es normalmente largo, ya que, además del software, la capa física del CPS ha de ser testeada. Esta capa física es típicamente modelada con modelos matemáticos complejos, lo cual es computacionalmente caro. Segundo, los sistemas cyber-físicos implican el uso de diferentes dominios de la ingeniería, como por ejemplo la mecánica o la electrónica. Por ello, para interconectar diferentes herramientas de modelado y simulación hace falta el uso de la co-simulación. A pesar de que la co-simulación es una ventaja en términos de flexibilidad para los ingenieros, el uso de diferentes simuladores hace que el tiempo de simulación sea más largo. Por último, al testear sistemas cyberfísicos haciendo uso de simulación, existen diferentes niveles (p.ej., Model, Software y Hardware-in-the-Loop), lo cual incrementa el tiempo para ejecutar casos de test. Esta tesis tiene como objetivo avanzar en la práctica actual del testeo de sistemas cyber-físicos configurables, proponiendo métodos para la automatización, optimización y depuración. En cuanto a la automatización, primero, se propone una metodología soportada por una herramienta para generar automáticamente instancias de sistemas de test que permiten testear automáticamente configuraciones del sistema CPS configurable (p.ej., haciendo uso de oráculos de test). Segundo, se propone un enfoque para generación de casos de test basado en algoritmos de búsqueda multiobjetivo, los cuales generan un conjunto de casos de test. En cuanto a la optimización, se propone un enfoque para selección y otro para priorización de casos de test, ambos basados en algoritmos de búsqueda, de cara a testear eficientemente sistemas cyberfísicos configurables en diferentes niveles de test. En cuanto a la depuración, se adapta una técnica llamada “Localización de Fallos Basada en Espectro” al contexto de líneas de productos y proponemos un método de aislamiento de fallos. Esto permite localizar bugs no solo en sistemas cyber-físicos configurables sino también en cualquier línea de producto donde se utilicen modelos de características para gestionar la variabilidad.Cyber-Physical Systems (CPSs) integrate digital cyber technologies with physical processes. The variability of these systems is increasing in order to give solution to the different customers demands. As a result, CPSs are becoming configurable or even product lines, which means that they can be set into thousands or millions of configurations. Testing configurable CPSs is a time consuming process, mainly due to the large amount of configurations that need to be tested. The large amount of configurations that need to be tested makes it infeasible to use a prototype of the system. As a result, configurable CPSs are being tested using simulation. However, testing CPSs under simulation is still challenging. First, the simulation time is usually long, since apart of the software, the physical layer needs to be simulated. This physical layer is typically modeled with complex mathematical models, which is computationally very costly. Second, CPSs involve different domains, such as, mechanical and electrical. Engineers of different domains typically employ different tools for modeling their subsystems. As a result, co-simulation is being employed to interconnect different modeling and simulation tools. Despite co-simulation being an advantage in terms of engineers flexibility, the use of different simulation tools makes the simulation time longer. Lastly, when testing CPSs employing simulation, different test levels exist (i.e., Model, Software and Hardware-in-the-Loop), what increases the time for executing test cases. This thesis aims at advancing the current practice on testing configurable CPSs by proposing methods for automation, optimization and debugging. Regarding automation, first, we propose a tool supported methodology to automatically generate test system instances that permit automatically testing configurations of the configurable CPS (e.g., by employing test oracles). Second, we propose a test case generation approach based on multi-objective search algorithms that generate cost-effective test suites. As for optimization, we propose a test case selection and a test case prioritization approach, both of them based on search algorithms, to cost-effectively test configurable CPSs at different test levels. Regarding debugging, we adapt a technique named Spectrum-Based Fault Localization to the product line engineering context and propose a fault isolation method. This permits localizing bugs not only in configurable CPSs but also in any product line where feature models are employed to model variability

    Building an Emulation Environment for Cyber Security Analyses of Complex Networked Systems

    Full text link
    Computer networks are undergoing a phenomenal growth, driven by the rapidly increasing number of nodes constituting the networks. At the same time, the number of security threats on Internet and intranet networks is constantly growing, and the testing and experimentation of cyber defense solutions requires the availability of separate, test environments that best emulate the complexity of a real system. Such environments support the deployment and monitoring of complex mission-driven network scenarios, thus enabling the study of cyber defense strategies under real and controllable traffic and attack scenarios. In this paper, we propose a methodology that makes use of a combination of techniques of network and security assessment, and the use of cloud technologies to build an emulation environment with adjustable degree of affinity with respect to actual reference networks or planned systems. As a byproduct, starting from a specific study case, we collected a dataset consisting of complete network traces comprising benign and malicious traffic, which is feature-rich and publicly available

    Computer Architectures to Close the Loop in Real-time Optimization

    Get PDF
    © 2015 IEEE.Many modern control, automation, signal processing and machine learning applications rely on solving a sequence of optimization problems, which are updated with measurements of a real system that evolves in time. The solutions of each of these optimization problems are then used to make decisions, which may be followed by changing some parameters of the physical system, thereby resulting in a feedback loop between the computing and the physical system. Real-time optimization is not the same as fast optimization, due to the fact that the computation is affected by an uncertain system that evolves in time. The suitability of a design should therefore not be judged from the optimality of a single optimization problem, but based on the evolution of the entire cyber-physical system. The algorithms and hardware used for solving a single optimization problem in the office might therefore be far from ideal when solving a sequence of real-time optimization problems. Instead of there being a single, optimal design, one has to trade-off a number of objectives, including performance, robustness, energy usage, size and cost. We therefore provide here a tutorial introduction to some of the questions and implementation issues that arise in real-time optimization applications. We will concentrate on some of the decisions that have to be made when designing the computing architecture and algorithm and argue that the choice of one informs the other

    A comparison study of co-simulation frameworks for multi-energy systems: the scalability problem

    Get PDF
    The transition to a low-carbon society will completely change the structure of energy systems from a standalone hierarchical centralised vision to cooperative and dis- tributed Multi-Energy Systems. The analysis of these complex systems requires the collaboration of researchers from different disciplines in the energy, ICT, social, economic, and political sectors. Combining such disparate disciplines into a single tool for modeling and analyzing such a complex environment as a Multi-Energy System requires tremendous effort. Researchers have overcome this effort by using co-simulation techniques that give the possibility of integrating existing domain-specific simulators in a single environment. Co-simulation frameworks, such as Mosaik and HELICS, have been developed to ease such integration. In this context, an additional challenge is the different temporal and spatial scales that are involved in the real world and that must be addressed during co-simulation. In particular, the huge number of heterogeneous actors populating the system makes it difficult to represent the system as a whole. In this paper, we propose a comparison of the scalability performance of two major co-simulation frameworks (i.e. HELICS and Mosaik) and a particular implementation of a well-known multi-agent systems library (i.e. AIOMAS). After describing a generic co-simulation framework infrastructure and its related challenges in managing a distributed co-simulation environment, the three selected frameworks are introduced and compared with each other to highlight their principal structure. Then, the scalability problem of co-simulation frameworks is introduced presenting four benchmark configurations to test their ability to scale in terms of a number of running instances. To carry out this comparison, a simplified multi-model energy scenario was used as a common testing environment. This work helps to understand which of the three frameworks and four configurations to select depending on the scenario to analyse. Experimental results show that a Multi-processing configuration of HELICS reaches the best performance in terms of KPIs defined to assess the scalability among the co-simu- lation frameworks

    A review of cyber-ranges and test-beds:current and future trends

    Get PDF
    Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable environments that necessitate more diligent management. The rapid proliferation in the automation of cyber-attacks is reducing the gap between information and operational technologies and the need to review the current levels of robustness against new sophisticated cyber-attacks, trends, technologies and mitigation countermeasures has become pressing. A deeper characterisation is also the basis with which to predict future vulnerabilities in turn guiding the most appropriate deployment technologies. Thus, refreshing established practices and the scope of the training to support the decision making of users and operators. The foundation of the training provision is the use of Cyber-Ranges (CRs) and Test-Beds (TBs), platforms/tools that help inculcate a deeper understanding of the evolution of an attack and the methodology to deploy the most impactful countermeasures to arrest breaches. In this paper, an evaluation of documented CR and TB platforms is evaluated. CRs and TBs are segmented by type, technology, threat scenarios, applications and the scope of attainable training. To enrich the analysis of documented CR and TB research and cap the study, a taxonomy is developed to provide a broader comprehension of the future of CRs and TBs. The taxonomy elaborates on the CRs/TBs dimensions, as well as, highlighting a diminishing differentiation between application areas
    corecore