Data Security for Connected Governments and Organisations

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

A cluster medoid approach for cloud task scheduling

One of the familiar distributed technologies for sharing computing resources through internet is a cloud computing technology. One need not setup all computing resources on their own to design their applications. They can own as much they want by requesting computing resources through net. These resources are shared between users upon request by properly scheduling tasks in cloud. The process of scheduling tasks is to be optimized to share the resources very fast. The paper proposes a cluster medoid based task scheduling technique KMPS (K-medoid particle swarm approach) for minimizing the makespan. KMPS uses the merits of both Particle Swarm Optimization (PSO) and k-medoid approaches with added weights concept. Experimental results have shown that KMPS has optimized the results of make span and it is most suitable one for cloud computing.

Data Security for Connected Governments and Organisations

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

A Blockchain-Based Voting System for E-Elections in Totalitarian States

The purpose of the present research was to introduce a blockchain-based voting system so that any state, including totalitarian states, can show interest in using it. In this method, a hybrid voting system with two centralized and distributed systems was used. Its centralized system is one of the most common voter identification and polling models, and its distributed system, which is designed with Ethereum public blockchain, is voting for voters. Totalitarian states are not interested in announcing the results online. Also, the lack of trust in E-voting systems by both states and voters has led to E-voting in important political elections in most states as support for manual or paper voting. Based on the results of field research with this voting system, it was possible to create a 7 min break between the end of the voting process and the announcement of the results for political considerations. This break can be increased by agreement. The results of the votes cannot be manipulated in any way. Survey results should also be communicated to voters before the voting process. This voting system can improve the level of democracy and maximum participation. It is hoped that the spread of distributed technologies, especially the blockchain, will pave the way for the spread of justice and democracy around the world.

EDUCATIONAL PROJECT TO CREATE AN AUTOMATED CONTROL SYSTEM OF THE GREENHOUSE COMPLEX

The article presents the process of design of educational project to create an automated control system of the greenhouse complex, which includes a controller with sensors, as well as a cloud server with a universal web-interface for displaying data from sensors. All developments within the framework of the research were carried out on the basis of modern, free-distributed technologies of the Internet of things. The use of these technologies made it possible to implement a working version of a prototype controller for monitoring parameters of the greenhouse complex, with the least expenditure of resources.

Democratizing Investment

Americans have trillions of dollars invested in public and private companies, yet stock ownership is highly unequal: the wealthiest 1 percent of households possess 40 percent of all wealth, and there is a large and persistent racial wealth gap. What if innovations in distributed technologies allowed for democratic facilitation of new opportunities for wealth and a rebalancing of power within the capital markets? This article proposes using innovative financial technologies to create a “Public Investment Platform”—a public option for participation in capital markets—and a “Public Investment Account” to universalize access to investment opportunities. Capital markets are currently governed by public policies that submerge the role of the public in structuring them and enable an inequitable accumulation of wealth. To democratize finance, new policies are required to democratize participation in investment.

To Implement an Open-MAS Architecture for Semantic Web Services Discovery

Recently, several models have been proposed to design distributed and collaborative infrastructures for web services based systems. In this area, Peer-to-Peer (P2P) networks and Multi-Agents Systems offer many techniques for web services discovery and composition. However, both of the two combinations (P2P/web services and MAS/web services) have suffered from some problems. This article presents a generic P2P/MAS architecture for semantic web services discovery. It tries to merge these two distributed technologies and demonstrate how P2P networks can implement open-MAS architectures to build a collaborative distributed system. The main objective of this article is to find the most appropriate P2P protocol to make such systems. Before the presentation of the proposed architecture, it already presents a background of P2P categories and models. After, it chooses four different P2P protocols wherever it analyzes and discusses, for each one, the stabilization and traffic generation of the network.