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In this paper, we present a side-channel resilient moving target defense mechanism against power-/electromagnetic-based side-channel attacks. Recent countermeasures use fresh rekeying after every encryption/decryption process; this causes major overhead in synchronizing the communicating parties. In contrast to previous work, our mechanism integrates fresh rekeying and masking techniques at an interval, where these techniques are driven by the maximum number of side-channel leakage traces required toward a successful embedded attack. Hence, the mechanism tracks the effect of attacks on the number of traces, and consequently applies rekeying at suitable intervals to reduce the computational/communication overhead, while increasing the attack cost. The mechanism scalability was evaluated against an advanced attack model based on machine learning methods that reduces significantly the number of traces required for a successful attack under masking implementation.

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. QC 20170906 CERCES

In this paper, we present a side-channel resilient moving target defence mechanism against power-/electromagnetic-based side-channel attacks. Recent countermeasures use fresh re-keying after every encryption/decryption process; this causes major overhead in synchronizing the communicating parties. In contrast to prior work, our mechanism integrates fresh re-keying and masking techniques at an interval, where these techniques are driven by the maximum number of side-channel leakage traces required towards a successful embedded attack. Hence, the mechanism tracks the effect of attacks on the number of traces, and consequently applies re-keying at suitable intervals to reduce the computational/communication overhead, while increasing the attack cost. The mechanism scalability was evaluated against an advanced attack model based on machine learning methods that reduces significantly the number of traces required for a successful attack under masking implementation.

Smart cities offer a variety of services to provide citizens with efficient transport, water distribution, crime prevention, and traffic control. Such services are personalized by automatically capturing, storing, and processing personally identifiable data. The disclosure of such data to a service provider raises privacy concerns for application users. As a result, research has recognized the need for privacy aware services in smart cities. In this paper we present PrivacyZones, a privacy awareness framework which requires the service provider to share meaningful features of the data collected by their application (such as the number of users in proximity to a location). Using this information an application user will know the potential privacy risk prior to sharing their data. The framework can also recommend the actions a user can take to mitigate privacy risks, such as when, where and what data to share with a service provider. We demonstrate how PrivacyZones could work for two services. First, a Hail-A-Taxi service, with real cell phone and taxi-cab GPS data from the Chinese city, Shenzhen. Second, a Get-A-Discount service with census-income data where inferred income level determines the type of discounts offered to users as they explore a city.

Fan-coil units are widely used as terminal units in Heating, Ventilation and Air-Conditioning (HVAC) systems in buildings. Fault Detection and Diagnosis of HVAC systems has been an active area of research for several decades. However, the focus has mostly been on central units such as Air Handling Units, Chillers and Boilers, and Variable Air Volume (VAV) terminal units. In this work we propose a diagnosis scheme for fan-coil units based on a grey-box model based approach. The main contribution of this work is a systematic sub-system level diagnosis case study of the Fan Coil Unit. A systematic procedure to obtain a simplified model of a heat exchanger coil based on polynomial regression is described. The model is used to generate residuals. The results show that the residuals from this model facilitate accurate fault isolation by means of simple rules. The model is characterised by a small set of parameters and is computationally light-weight, thereby making it suitable for embedded diagnosis. For the control problem, the zone thermostat is sufficient. However, for facilitating diagnosis, additional sensors are required. We also examine the role played by different sensors in the fault detection and isolation.

We describe a validation approach for Simulink models of industrial cyber-physical systems (CPS), based on an adaptation of a coverage-guided test generation method for hybrid systems. Modelling an industrial CPS requires integrating heterogeneous components, which introduces high complexity in model verification. Using Simulink, which has become a de-facto industrial tool, heterogeneity comes from combining different formalisms (Simulink blocks, Stateflow diagrams, Matlab and C functions, etc.) and mixing different types of dynamics (discrete, continuous). Since the interactions between such components are often too complex to be faithfully captured in an existing mathematical modelling paradigm, we resort to treating them as black box systems while trying to exploit as much as possible a-priori knowledge about them. We first describe our approach: extracting from a Simulink model the information to define the main ingredients of the test generation framework, in particular environment inputs in which faults could be injected and critical states that require good coverage. We then illustrate the approach with an industrial model of an HVAC (Heating, Ventilation and Air Conditioning) system.

Current approaches to building Cyber Physical systems including Energy Management Systems (EMS) design often rely on large monolithic models to represent the EMS. These models are typically abstract and simple to aid with performance. However, they can lack fidelity and detail, particularly with regards to physical aspects. This makes it challenging to extract valuable and accurate data from these models, such as sustainability metrics. Our approach to this problem is to employ a Cyber-Physical Systems Model-Based Design methodology that enables the use of various specialised multi-disciplinary models through Functional Mock-up Interface (FMI) and a common integration platform based on SysML. We apply the approach to a heating, ventilation and air conditioning case study and show how the resulting data can be used to evaluate a design. In addition, we discuss how the approach supports the inclusion of dedicated models for the generation of precise sustainability metrics.

We describe an approach to the model-based engineering of cyber-physical systems that permits the coupling of diverse discrete-event and continuous-time models and their simulators. A case study in the building automation domain demonstrates how such co-models and co-simulation can promote early cooperation between disciplines within a systems engineering process before the expensive commitment is made to integration in physical prototypes. We identify areas for future advances in foundations, methods and tools to realise the potential of a co-modelling approach within established systems engineering processes.

This paper describes a low-energy test-bed installed in a building that integrates an electrical microgrid and a thermal system. The test-bed is controlled by following a hierarchical control strategy ranging from local controllers of subsystems to power system coordination and energy optimization. Experimental results of the test-bed operation (both electrical and thermal side) are presented and some challenges for proper system operation (such as stability and seamless transition) are described.

A modern Building Automation System (BAS) aims to enhance the functionality of interactive control strategies leading towards energy efficiency and enhanced user comfort. Typically, it is cheaper to embed the BAS within a Wireless Sensor/Actuator Network (WSAN) rather than rewire legacy. However, the cost of a WSAN deployment is a critical factor for the new buildings. In this context, we develop a co-design approach for assessing the cost of a WSAN deployment while achieving particular control performance. We apply the developed co-design strategy to a distributed control for building lighting systems. We empirically compare our developed system for building lighting control strategy with a standard PI control method to demonstrate an average of 45% reduction in energy use while maintaining the user comfort and 23% saving in the network cost.

Designing a control system over Wireless Sensor/Actuator Network (WSAN) devices increases the coupling of many aspects, and the need for a sound discipline for writing/designing embedded software becomes more apparent. Such a WSAN-based control architecture is called a Networked Control System (NCS). At present, many frameworks support some steps of the NCS design flow, however there is no end-to-end solution that considers the tight integration of hardware, software and physical environment. This chapter aims to develop a fully integrated end-to-end framework for designing an NCS, from system modelling to embedded control-code generation. This framework aims to generate embedded control code that preserves the modelled system properties, and observes the hardware/software constraints of the targeted platform.

A Building Automation System (BAS) aims to provide good user comfort within occupied zones in a building. One can enhance the functionality of a BAS through embedding advanced control strategies within a Wireless Sensor/Actuator Network (WSAN), and also make retrofit applications possible. However, control systems that are embedded in a WSAN can perform sub-optimally if the control system and WSAN are designed independently. In this context, we develop a co-design approach for embedding BAS code within a Network Control System. We compare our developed system for building lighting control with (a) a standard PI control method to empirically demonstrate a 19% reduction in energy use and 65% improvement in user comfort, and (b) an MPC strategy that uses only presence-based control, to show 25% reduction in energy use. Our approach also improves network delay and sensor battery usage by 68% over the PI baseline.

Lighting systems consume a considerable proportion of total energy budgets, particularly for retail and public-office applications, and hence their optimisation can save considerable amounts of energy. This paper proposes an intelligent control strategy to operate the office luminance in order to enhance user comfort and reduce energy consumption. The strategy is applied to an open office scenario, where the controller and the environments are modelled using a hybrid/multi-agent platform. The developed controller uses a constraint-based optimisation technique to compute the optimal settings.We describe the different modelling steps, including the optimisation technique, and outline the simulation results and potential energy benefits of the proposed controller.

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.

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.

Recently EPON has been appeared to introduce the convergence of low-cost Ethernet equipment and fiber infrastructure, it is appeared to be the best candidate for the next-generation access network. Auto-discovery process is an important process in EPON system. . Indeed, this paper provides a MAC design following the IEEE 802.3ah standard of the MPCP auto-discovery process at the ONU side. It describes as well the validation and verification steps using an OLT model and finally, the synthesis result are presented.

In order to develop an integrated system that can optimise building operations, all facets of monitoring, control and reconfiguration need to be integrated. To achieve this, we need to develop an integrated system model, together with associated sub-system interfaces. This links the low-level wireless/wired systems monitoring with multi-level control, building information management and user-preference inputs. In this paper we describe an integrated simulation platform that partially fulfils such objectives. We detail through a case study an integrated simulation platform allowing testing, refinement and optimization of the design at an early stage. The paper provides a detailed simulation results and outlines the future works.