Hybrid performance modelling of opportunistic networks

We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modelled as discrete events. Our model describes a network of stationary video sensors with a mobile ferry which collects data from the sensors and delivers it to the base station. We consider different mobility models and different buffer sizes for the ferries. This case study illustrates the flexibility and expressive power of stochastic HYPE. We also discuss the software that enables us to describe stochastic HYPE models and simulate them.Comment: In Proceedings QAPL 2012, arXiv:1207.055

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii

Dynamic state reconciliation and model-based fault detection for chemical processes

In this paper, we present a method for the fault detection based on the residual generation. The main idea is to reconstruct the outputs of the system from the measurements using the extended Kalman filter. The estimations are compared to the values of the reference model and so, deviations are interpreted as possible faults. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. The use of this method is illustrated through an application in the field of chemical processe

Formal analysis techniques for gossiping protocols

We give a survey of formal verification techniques that can be used to corroborate existing experimental results for gossiping protocols in a rigorous manner. We present properties of interest for gossiping protocols and discuss how various formal evaluation techniques can be employed to predict them

Towards Simple Models for Energy-Performance Trade-Offs in Data Centers

In this paper we advocate the use of simple stochastic models to analyse the energy-performance trade-off in data centres. Recently such trade-offs have received increased attention, however, the tools used to make such trade-offs are largely based on simulation and real-life experiments. Although simulations studies are very helpful, we think that simple analytical models, or models based on stochastic Petri nets (or similar description techniques) can be very fruitful in guiding design processes in the early phases.\ud Similarly, we do think that experimental work is very important, however, its results come "after the fact" in the sense that the system has been built already once the experiments are being performed. Our claim is that the\ud use of simple models early in the design phase provides a very good return on investment. This short paper presents some preliminary models that can be used for early-in-design trade-off analyses

Evaluating Resilience of Cyber-Physical-Social Systems

Nowadays, protecting the network is not the only security concern. Still, in cyber security, websites and servers are becoming more popular as targets due to the ease with which they can be accessed when compared to communication networks. Another threat in cyber physical social systems with human interactions is that they can be attacked and manipulated not only by technical hacking through networks, but also by manipulating people and stealing users’ credentials. Therefore, systems should be evaluated beyond cy- ber security, which means measuring their resilience as a piece of evidence that a system works properly under cyber-attacks or incidents. In that way, cyber resilience is increas- ingly discussed and described as the capacity of a system to maintain state awareness for detecting cyber-attacks. All the tasks for making a system resilient should proactively maintain a safe level of operational normalcy through rapid system reconfiguration to detect attacks that would impact system performance. In this work, we broadly studied a new paradigm of cyber physical social systems and defined a uniform definition of it. To overcome the complexity of evaluating cyber resilience, especially in these inhomo- geneous systems, we proposed a framework including applying Attack Tree refinements and Hierarchical Timed Coloured Petri Nets to model intruder and defender behaviors and evaluate the impact of each action on the behavior and performance of the system.Hoje em dia, proteger a rede não é a única preocupação de segurança. Ainda assim, na segurança cibernética, sites e servidores estão se tornando mais populares como alvos devido à facilidade com que podem ser acessados quando comparados às redes de comu- nicação. Outra ameaça em sistemas sociais ciberfisicos com interações humanas é que eles podem ser atacados e manipulados não apenas por hackers técnicos através de redes, mas também pela manipulação de pessoas e roubo de credenciais de utilizadores. Portanto, os sistemas devem ser avaliados para além da segurança cibernética, o que significa medir sua resiliência como uma evidência de que um sistema funciona adequadamente sob ataques ou incidentes cibernéticos. Dessa forma, a resiliência cibernética é cada vez mais discutida e descrita como a capacidade de um sistema manter a consciência do estado para detectar ataques cibernéticos. Todas as tarefas para tornar um sistema resiliente devem manter proativamente um nível seguro de normalidade operacional por meio da reconfi- guração rápida do sistema para detectar ataques que afetariam o desempenho do sistema. Neste trabalho, um novo paradigma de sistemas sociais ciberfisicos é amplamente estu- dado e uma definição uniforme é proposta. Para superar a complexidade de avaliar a resiliência cibernética, especialmente nesses sistemas não homogéneos, é proposta uma estrutura que inclui a aplicação de refinamentos de Árvores de Ataque e Redes de Petri Coloridas Temporizadas Hierárquicas para modelar comportamentos de invasores e de- fensores e avaliar o impacto de cada ação no comportamento e desempenho do sistema

Petri net approaches for modeling, controlling, and validating flexible manufacturing systems

In this dissertation, we introduce the fundamental ideas and constructs of Petri net models such as ordinary, timed, colored, stochastic, control, and neural, and present some studies that emphasize Petri nets theories and applications as extended research fields that provide suitable platforms in modeling, controlling, validating, and evaluating concurrent systems, information systems, and a versatile dynamic system and manufacturing systems;We then suggest some of extensions that help make Petri nets useful for modeling and analyzing discrete event systems and manufacturing systems models based on the context of a versatile manufacturing system, and applies extended Petri nets models to several manufacturing systems such as an assembly cell, an Automated Palletized Conveyor System, and a tooling machine to show increased modeling power and efficient analysis methods;Finally, Validation methods are presented for these models and results of a performance analysis from a deterministic and stochastic model are used to reorganize and re-evaluate a manufacturing system in order to increase its flexibility

Modeling IT Availability Risks in Smart Factories

In the course of the ongoing digitalization of production, production environments have become increasingly intertwined with information and communication technology. As a consequence, physical production processes depend more and more on the availability of information networks. Threats such as attacks and errors can compromise the components of information networks. Due to the numerous interconnections, these threats can cause cascading failures and even cause entire smart factories to fail due to propagation effects. The resulting complex dependencies between physical production processes and information network components in smart factories complicate the detection and analysis of threats. Based on generalized stochastic Petri nets, the paper presents an approach that enables the modeling, simulation, and analysis of threats in information networks in the area of connected production environments. Different worst-case threat scenarios regarding their impact on the operational capability of a close-to-reality information network are investigated to demonstrate the feasibility and usability of the approach. Furthermore, expert interviews with an academic Petri net expert and two global leading companies from the automation and packaging industry complement the evaluation from a practical perspective. The results indicate that the developed artifact offers a promising approach to better analyze and understand availability risks, cascading failures, and propagation effects in information networks in connected production environments