Most existing industrial control systems (ICSs), such as building energy management systems (EMSs), were installed when potential security threats were only physical. With advances in connectivity, ICSs are now, typically, connected to communications networks and, as a result, can be accessed remotely. This extends the attack surface to include the potential for sophisticated cyber attacks, which can adversely impact ICS operation, resulting in service interruption, equipment damage, safety concerns, and associated financial implications. In this work, a novel cyber-physical security framework for ICSs is proposed, which incorporates an analytics tool for attack detection and executes a reliable estimation-based attack-resilient control policy, whenever an attack is detected. The proposed framework is adaptable to already implemented ICS and the stability and optimal performance of the controlled system under attack has been proved. The performance of the proposed framework is evaluated using a reduced order model of a real EMS site and simulated attacks.

Physical access control policies define sets of rulesthat govern people's access to physical resources such asrooms and buildings. While simple decision-precedence can be used to reconcile different rules that result in conflicting access decisions, the presence of rule conflicts and other rule anomalies can make it difficult for a policy-administrator to comprehend and effectively manage complex policies. In this paper we are concerned with discovering conflicts and computing relaxations of access policies in order to eliminate conflicting rule instances. We propose several SAT based encodings in which these rule conflicts and anomalies areexpressed as explanation style problems. Relaxation techniques are in turn used to eliminate these anomalies by recommending what rules have to be revoked or what permissions have to beremoved from which rules. Moreover, we discuss a relaxation strategy that preserves most of the access constraints of theoriginal policy. Finally we provide a preliminary performancestudy of our techniques. Our approach is applicable to access control policies in general.

This paper provides an overview of the architecture for self-organizing, co-operative and robust Building Automation Systems (BAS) proposed by the EC funded FP7 SCUBA1project. We describe the current situation in monitoring and control systems and outline the typical stakeholders involved in the case of building automation systems. We derive seven typical use cases which will be demonstrated and evaluated on pilot sites. From these use cases the project designed an architecture relying on six main modules that realize the design, commissioning and operation of self-organizing, co-operative, robust BAS.

Building Automation usually involves a large number of systems that should cooperate in order to improve e.g. the user comfort, security, but also decrease the overall energy consumption. One aim of the EU funded SCUBA project is to improve the coordination among devices and systems installed in a building. This paper deals with the extension of a framework dedicated to Building Automation and built on top of the LINC resource-based middleware. Two particular tools developed in SCUBA and that make use of the middleware are also presented together with the encapsulation of the ontology-based Building Automation System model named BASOnt.

We propose a methodology for overcoming the current approach of writing diagnostics code for industrial automation applications after the system is designed, which results in significant extra effort/cost, and potential discrepancies between design and diagnostics output. We show how we can automatically generate diagnostics from a more complex simulation model. We show how a model-transformation framework can transform a hybrid-systems simulation model into a propositional-logic diagnostics model with appropriate transformation rules. We illustrate our approach with an example from the domain of control for building lighting systems.

In embedded software development, model-driven design is well recognized. In this article we describe a compositional model-driven approach for auto-generating embedded code for improving the energy efficiency of building automation applications. We show how we can use a component-based hybrid-systems modelling framework to generate models for simulation and verification. Then, we auto-generate embeddable code from these models. We empirically demonstrate this approach using the hybrid-systems tool Charon, for the domain of energy-efficient lighting control for smart buildings. The paper provides a detailed description of the code generation steps and outlines some results obtained through a simple lighting example.

This work addresses the analysis and validation of CHP specifications for asynchronous circuits, using property Verification tools. CHP semantics, initially given in terms of Petri Nets, are reformulated as labeled transition systems. Circuit specifications are translated into an intermediate format (IF) based on communicating extended finite state machines. They are then validated using the IF environment, which provides model checking and bi-simulation tools. The direct translation must be optimized to delay state explosion. Performance studies are reported. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.