Towards Fast and Semi-Supervised Identification of Smart Meters Launching Data Falsification Attacks

Compromised smart meters sending false power consumption data in Advanced Metering Infrastructure (AMI) may have drastic consequences on the smart grid\u27s operation. Most existing defense models only deal with electricity theft from individual customers (isolated attacks) using supervised classification techniques that do not offer scalable or real time solutions. Furthermore, the cyber and interconnected nature of AMIs can also be exploited by organized adversaries who have the ability to orchestrate simultaneous data falsification attacks after compromising several meters, and also have more complex goals than just electricity theft. In this paper, we first propose a real time semi-supervised anomaly based consensus correction technique that detects the presence and type of smart meter data falsification, and then performs a consensus correction accordingly. Subsequently, we propose a semi-supervised consensus based trust scoring model, that is able to identify the smart meters injecting false data. The main contribution of the proposed approach is to provide a practical framework for compromised smart meter identification that (i) is not supervised (ii) enables quick identification (iii) scales classification error rates better for larger sized AMIs; (iv) counters threats from both isolated and orchestrated attacks; and (v) simultaneously works for a variety of data falsification types. Extensive experimental validation using two real datasets from USA and Ireland, demonstrates the ability of our proposed method to identify compromised meters in near real time across different datasets

Implementation of smart devices in the construction industry

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.The construction industry has a fragmented nature, which accounts for the highest degree of decentralisation of information and the highest mobile content access. The exchange of information made possible by smart devices. This creates an opportunity to enhance productivity and communication among stakeholders of the construction industry. Firstly, this thesis explored the concept of smart devices. Secondly, the drivers, challenges and Critical Success Factors for implementing smart devices were investigated. This study adopted a qualitative approach using semi-structured interviews. A total of Thirty-nine interviewees which includes professionals from the construction sector of the Dominican Republic (DR) and the United Kingdom (UK) were interviewed. Thematic analysis was used to analyse the collected data. The drivers for the adoption of smart devices were grouped into internal and external drivers. The challenges found in the interviews were grouped into three categories, namely, economic, cultural and technological. The Critical Success Factors (CSFs) for implementing smart devices in the construction industry are leadership, training and development, organisational culture, technology awareness, cost, company size and usability. These findings were used to develop a strategic framework which has two sub-frameworks. This study concluded that a specific culture must be adopted on behalf of the government and construction companies to successfully adopt smart devices. Furthermore, this investigation found various similarities and differences regarding the drivers, challenges and CSFs for implementing smart devices in the UK and the DR. This study recommends integrating smart devices in data collection techniques in academia. Also, for construction companies to embrace technological innovation it is recommended to be willing to start new ventures, to be open to the participation of all members of the company, and be creative and client-oriented.Ministerio de Educacion Superior, Ciencia y Tecnología (MESCyT) - Ministry of Higher education, Science and technology of the Dominican Republic