Efficient Cooperative Anycasting for AMI Mesh Networks

We have, in recent years, witnessed an increased interest towards enabling a Smart Grid which will be a corner stone to build sustainable energy efficient communities. An integral part of the future Smart Grid will be the communications infrastructure which will make real time control of the grid components possible. Automated Metering Infrastructure (AMI) is thought to be a key enabler for monitoring and controlling the customer loads. %RPL is a connectivity enabling mechanism for low power and lossy networks currently being standardized by the IETF ROLL working group. RPL is deemed to be a suitable candidate for AMI networks where the meters are connected to a concentrator over multi hop low power and lossy links. This paper proposes an efficient cooperative anycasting approach for wireless mesh networks with the aim of achieving reduced traffic and increased utilisation of the network resources. The proposed cooperative anycasting has been realised as an enhancement on top of the Routing Protocol for Low Power and Lossy Networks (RPL), a connectivity enabling mechanism in wireless AMI mesh networks. In this protocol, smart meter nodes utilise an anycasting approach to facilitate efficient transport of metering data to the concentrator node. Moreover, it takes advantage of a distributed approach ensuring scalability

Chameleon: a Blind Double Trapdoor Hash Function for Securing AMI Data Aggregation

Data aggregation is an integral part of Advanced Metering Infrastructure (AMI) deployment that is implemented by the concentrator. Data aggregation reduces the number of transmissions, thereby reducing communication costs and increasing the bandwidth utilization of AMI. However, the concentrator poses a great risk of being tampered with, leading to erroneous bills and possible consumer disputes. In this paper, we propose an end-to-end integrity protocol using elliptic curve based chameleon hashing to provide data integrity and authenticity. The concentrator generates and sends a chameleon hash value of the aggregated readings to the Meter Data Management System (MDMS) for verification, while the smart meter with the trapdoor key computes and sends a commitment value to the MDMS so that the resulting chameleon hash value calculated by the MDMS is equivalent to the previous hash value sent by the concentrator. By comparing the two hash values, the MDMS can validate the integrity and authenticity of the data sent by the concentrator. Compared with the discrete logarithm implementation, the ECC implementation reduces the computational cost of MDMS, concentrator and smart meter by approximately 36.8%, 80%, and 99% respectively. We also demonstrate the security soundness of our protocol through informal security analysis

6LoPLC for smart grid applications

© 2015 IEEE. Reliable monitoring, intelligence and control achieved through Information and Communication Technology (ICT) will determine the success of next generation power grid. This paper proposes a Low Power transmission of Internet Protocol version 6 in PLC (6LoPLC) to provide network reliability with acceptable latency in Advanced Metering Infrastructure (AMI). The analysis presented here are preliminary results from an ongoing research that attempts to leverage existing wireless techniques to achieve energy efficiency in PLC. A model was developed using NS-3 to measure and analyze the performance of low-power Narrow Band PLC (NBPLC) in AMI services. Simulation results obtained so far are quite promising

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78–0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1–6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI

Cyber-Security in Smart Grid: Survey and Challenges

Smart grid uses the power of information technology to intelligently deliver energy to customers by using a two-way communication, and wisely meet the environmental requirements by facilitating the integration of green technologies. Although smart grid addresses several problems of the traditional grid, it faces a number of security challenges. Because communication has been incorporated into the electrical power with its inherent weaknesses, it has exposed the system to numerous risks. Several research papers have discussed these problems. However, most of them classified attacks based on confidentiality, integrity, and availability, and they excluded attacks which compromise other security criteria such as accountability. In addition, the existed security countermeasures focus on countering some specific attacks or protecting some specific components, but there is no global approach which combines these solutions to secure the entire system. The purpose of this paper is to provide a comprehensive overview of the relevant published works. First, we review the security requirements. Then, we investigate in depth a number of important cyber-attacks in smart grid to diagnose the potential vulnerabilities along with their impact. In addition, we proposed a cyber security strategy as a solution to address breaches, counter attacks, and deploy appropriate countermeasures. Finally, we provide some future research directions

MOSAIC vision and scenarios for mobile collaborative work related to health and wellbeing

The main objective of the MOSAIC project is to accelerate innovation in Mobile Worker Support Environments by shaping future research and innovation activities in Europe. The modus operandi of MOSAIC is to develop visions and illustrative scenarios for future collaborative workspaces involving mobile and location-aware working. Analysis of the scenarios is input to the process of road mapping with the purpose of developing strategies for R&D leading to deployment of innovative mobile work technologies and applications across different domains. This paper relates to one specific domain, that of Health and Wellbeing. The focus is therefore is on mobile working environments which enable mobile collaborative working related to the domain of healthcare and wellbeing services for citizens. This paper reports the work of MOSAIC T2.2 on the vision and scenarios for mobile collaborative work related to this domain. This work was also an input to the activity of developing the MOSAIC roadmap for future research and development targeted at realization of the future Health and Wellbeing vision. The MOSAIC validation process for the Health and Wellbeing scenarios is described and one scenario – the Major Incident Scenario - is presented in detail