Secure Data Management and Transmission Infrastructure for the Future Smart Grid

Power grid has played a crucial role since its inception in the Industrial Age. It has evolved from a wide network supplying energy for incorporated multiple areas to the largest cyber-physical system. Its security and reliability are crucial to any country’s economy and stability [1]. With the emergence of the new technologies and the growing pressure of the global warming, the aging power grid can no longer meet the requirements of the modern industry, which leads to the proposal of ‘smart grid’. In smart grid, both electricity and control information communicate in a massively distributed power network. It is essential for smart grid to deliver real-time data by communication network. By using smart meter, AMI can measure energy consumption, monitor loads, collect data and forward information to collectors. Smart grid is an intelligent network consists of many technologies in not only power but also information, telecommunications and control. The most famous structure of smart grid is the three-layer structure. It divides smart grid into three different layers, each layer has its own duty. All these three layers work together, providing us a smart grid that monitor and optimize the operations of all functional units from power generation to all the end-customers [2]. To enhance the security level of future smart grid, deploying a high secure level data transmission scheme on critical nodes is an effective and practical approach. A critical node is a communication node in a cyber-physical network which can be developed to meet certain requirements. It also has firewalls and capability of intrusion detection, so it is useful for a time-critical network system, in other words, it is suitable for future smart grid. The deployment of such a scheme can be tricky regarding to different network topologies. A simple and general way is to install it on every node in the network, that is to say all nodes in this network are critical nodes, but this way takes time, energy and money. Obviously, it is not the best way to do so. Thus, we propose a multi-objective evolutionary algorithm for the searching of critical nodes. A new scheme should be proposed for smart grid. Also, an optimal planning in power grid for embedding large system can effectively ensure every power station and substation to operate safely and detect anomalies in time. Using such a new method is a reliable method to meet increasing security challenges. The evolutionary frame helps in getting optimum without calculating the gradient of the objective function. In the meanwhile, a means of decomposition is useful for exploring solutions evenly in decision space. Furthermore, constraints handling technologies can place critical nodes on optimal locations so as to enhance system security even with several constraints of limited resources and/or hardware. The high-quality experimental results have validated the efficiency and applicability of the proposed approach. It has good reason to believe that the new algorithm has a promising space over the real-world multi-objective optimization problems extracted from power grid security domain. In this thesis, a cloud-based information infrastructure is proposed to deal with the big data storage and computation problems for the future smart grid, some challenges and limitations are addressed, and a new secure data management and transmission strategy regarding increasing security challenges of future smart grid are given as well

Architecture for satellite services over cryptographically heterogeneous networks with application into smart grid

The rapid growth in the demand for Future Internet services with many emerging group applications has driven the development of satellite, which is the preferred delivery mechanism due to its wide area coverage, multicasting capability and speed to deliver affordable future services. Nevertheless, security has been one of the obstacles for both satellite services as well as smart grid group applications, especially with logical/geographical/cryptographic domains spanning heterogeneous networks and regions. In this paper, adaptive security architecture is implemented to protect satellite services for smart grid group applications. The focus is on key management and policy provisioning. Leveraging Group Domain of Interpretation (GDOI) as the standard for smart grid centralized key/policy management architecture, a single Domain of Interpretation (DOI) is deployed and evaluated critically in terms of the added protocol signaling overhead on the satellite system for a fixed-network scenario. This also partially realizes the growing trend towards the use of TCP/IP technology for smart grid applications

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

A cloud-based smart metering infrastructure for distribution grid services and automation

© 2017 The Authors The evolution of the power systems towards the smart grid paradigm is strictly dependent on the modernization of distribution grids. To achieve this target, new infrastructures, technologies and applications are increasingly required. This paper presents a smart metering infrastructure that unlocks a large set of possible services aimed at the automation and management of distribution grids. The proposed architecture is based on a cloud solution, which allows the communication with the smart meters from one side and provides the needed interfaces to the distribution grid services on the other one. While a large number of applications can be designed on top of the cloud, in this paper the focus will be on a real-time distributed state estimation algorithm that enables the automatic reconfiguration of the grid. The paper will present the key role of the cloud solution for obtaining scalability, interoperability and flexibility, and for enabling the integration of different services for the automation of the distribution system. The distributed state estimation algorithm and the automatic network reconfiguration will be presented as an example of coordinated operation of different distribution grid services through the cloud

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017