Biblio

Anomaly-based detection applied in strongly interdependent systems, like Smart Grids, has become one of the most challenging research areas in recent years. Early detection of anomalies so as to detect and prevent unexpected faults or stealthy threats is attracting a great deal of attention from the scientific community because it offers potential solutions for context-awareness. These solutions can also help explain the conditions leading up to a given situation and help determine the degree of its severity. However, not all the existing approaches within the literature are equally effective in covering the needs of a particular scenario. It is necessary to explore the control requirements of the domains that comprise a Smart Grid, identify, and even select, those approaches according to these requirements and the intrinsic conditions related to the application context, such as technological heterogeneity and complexity. Therefore, this paper analyses the functional features of existing anomaly-based approaches so as to adapt them, according to the aforementioned conditions. The result of this investigation is a guideline for the construction of preventive solutions that will help improve the context-awareness in the control of Smart Grid domains in the near future.

During the last decade, the Cloud Computing paradigm has emerged as a panacea for many problems in traditional IT infrastructures. Much has been said about the potential of Cloud Computing in the Smart Grid context, but unfortunately it is still relegated to a second layer when it comes to critical systems. Although the advantages of outsourcing those kind of applications to the cloud is clear, data confidentiality and operational privacy stand as mayor drawbacks. In this paper, we try to give some hints on which security mechanisms and more specific, which cryptographic schemes, will help a better integration of Smart Grids and Clouds. We propose the use of Virtual SCADA in the Cloud (VS-Cloud) as a mean to improve reliability and efficiency whilst maintaining the same protection level as in traditional SCADA architectures.

The introduction of the Smart Grid brings with it several benefits to society, because its bi-directional communication allows both users and utilities to have better control over energy usage. However, it also has some privacy issues with respect to the privacy of the customers when analysing their consumption data. In this paper we review the main privacy-preserving techniques that have been proposed and compare their efficiency, to accurately select the most appropriate ones for undertaking control operations. Both privacy and performance are essential for the rapid adoption of Smart Grid technologies.

Most of energy control or SCADA (Supervisory Control and Data Acquisition) systems are very dependent on advanced technologies and on traditional security mechanisms for protecting the a system against anomalous events. Security mechanisms are not enough to be used in critical systems, since they can only detect anomalous events occurring at a certain moment in time. For this reason it becomes of paramount importance the usage of intelligent systems with capability for preventing anomalous situations and reacting against them on time. This type of systems are, for example, Early Warning Systems (EWS). In this paper, we propose an EWS based on Wireless Sensor Networks (WSNs) (under the ISA100.11a standard) and reputation for controling the network behaviour. The WSN are organized into clusters where a Cluster Head (CH) is designated. This CH will contain a Reputation Manager Module. The usability of this approach is also analyzed considering a Smart Grid scenario.} keywords = {Critical Information Infrastructures, Sensor Networks, Early Warning Systems, Reputation, SCADA Systems, Smart Grid.

One benefit postulated for the adoption of Electric Vehicles (EVs) is their ability to act as stabilizing entities in smart grids through bi-directional charging, allowing local or global smoothing of peaks and imbalances. This benefit, however, hinges indirectly on the reliability and security of the power flows thus achieved. Therefore this paper studies key security properties of the alreadydeployed Open Charge Point Protocol (OCPP) specifying communication between charging points and energy management systems. It is argued that possible subversion or malicious endpoints in the protocol can also lead to destabilization of power networks. Whilst reviewing these aspects, we focus, from a theoretical and practical standpoint, on attacks that interfere with resource reservation originating with the EV, which may also be initiated by a man in the middle, energy theft or fraud. Such attacks may even be replicated widely, resulting in over- or undershooting of power network provisioning, or the (total/partial) disintegration of the integrity and stability of power networks.

The smart grid is an electronically controlled electrical grid that connects power generation, transmission, distribution, and consumers using information communication technologies. One of the key characteristics of the smart grid is its support for bi-directional information flow between the consumer of electricity and the utility provider. This two-way interaction allows electricity to be generated in real-time based on consumers’ demands and power requests. As a result, consumer privacy becomes an important concern when collecting energy usage data with the deployment and adoption of smart grid technologies. To protect such sensitive information it is imperative that privacy protection mechanisms be used to protect the privacy of smart grid users. We present an analysis of recently proposed smart grid privacy solutions and identify their strengths and weaknesses in terms of their implementation complexity, efficiency, robustness, and simplicity.

Control from anywhere and at anytime is nowadays a matter of paramount importance in critical systems. This is the case of the Smart Grid and its domains which should be monitored through intelligent and dynamic mechanisms able to anticipate, detect and respond before disruptions arise within the system. Given this fact and its importance for social welfare and the economy, a model for wide-area situational awareness is proposed in this paper. The model is based on a set of current technologies such as the wireless sensor networks, the ISA100.11a standard and cloud-computing together with a set of high-level functional services. These services include global and local support for prevention through a simple forecast scheme, detection of anomalies in the observation tasks, response to incidents, tests of accuracy and maintenance, as well as recovery of states and control in crisis situations.