In this paper, we identify and review key challenges to bridge the knowledge-gap between SME’s, companies, organisations, businesses, government institutions and the general public in adopting, promoting and utilising Blockchain technology. The challenges indicated are Cybersecurity and Data privacy in this instance. Additional challenges are set out supported by literature, in researching data security management systems and legal frameworks to ascertaining the types and varieties of valid encryption, data acquisition, policy and outcomes under ISO 27001 and the General Data Protection Regulations. Blockchain, a revolutionary method of storage and immutability, provides a robust storage strategy, and when coupled with a Smart Contract, gives users the ability to form partnerships, share information and consent via a legally-based system of carrying out business transactions in a secure digital domain. Globally, ethical and legal challenges significantly differ; consent and trust in the public and private sectors in deploying such defensive data management strategies, is directly related to the accountability and transparency systems in place to deliver certainty and justice. Therefore, investment and research in these areas is crucial to establishing a dialogue between nations to include health, finance and market strategies that should encompass all levels of society. A framework is proposed with elements to include Big Data, Machine Learning and Visualisation methods and techniques. Through the literature we identify a system necessary in carrying out experiments to detect, capture, process and store data. This includes isolating packet data to inform levels of Cybersecurity and privacy-related activities, and ensuring transparency demonstrated in a secure, smart and effective manner.
This paper reports on part of a larger study examining the applicability of fuzzy logic to the higher level supervisory control functions of unmanned air vehicles and details the work so far in testing the feasibility of a candidate self-organising scheme. The candidate algorithm consists of a regular fuzzy control system whose rule set is improved over time as a function of the deviation of the plant from some desired performance. Historically, virtually all work in this area has examined the application of the algorithm to the classic regulator problem, and focussed on achieving both better performance in that role and establishing tuning guidelines based on a more systematic approach. The application discussed in this paper is assessing the algorithm to ascertain its possible utility in the higher level supervisory capacities. The candidate control problem was one of station-keeping of one air vehicle behind another.
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