A systematic literature review of blockchain-based applications: Current status, classification and open issues

(1963). Cybernetics, or Control and Communication in the Animal and the Machine. Technometrics: Vol. 5, No. 1, pp. 128-130.

Cybernetics, or Control and Communication in the Animal and the Machine

Blockchain technologies have grown in prominence in recent years, with many experts citing the potential applications of the technology in regard to different aspects of any industry, market, agency, or governmental organizations. In the brief history of blockchain, an incredible number of achievements have been made regarding how blockchain can be utilized and the impacts it might have on several industries. The sheer number and complexity of these aspects can make it difficult to address blockchain potentials and complexities, especially when trying to address its purpose and fitness for a specific task. In this survey, we provide a comprehensive review of applying blockchain as a service for applications within today’s information systems. The survey gives the reader a deeper perspective on how blockchain helps to secure and manage today information systems. The survey contains a comprehensive reporting on different instances of blockchain studies and applications proposed by the research community and their respective impacts on blockchain and its use across other applications or scenarios. Some of the most important findings this survey highlights include the fact that blockchain’s structure and modern cloud- and edge-computing paradigms are crucial in enabling a widespread adaption and development of blockchain technologies for new players in today unprecedented vibrant global market. Ensuring that blockchain is widely available through public and open-source code libraries and tools will help to ensure that the full potential of the technology is reached and that further developments can be made concerning the long-term goals of blockchain enthusiasts.

A Survey on Blockchain for Information Systems Management and Security

EXECUTIVE EDITORS Tom Bramley, Cambridge Assessment, UK Jannette Elwood, Queen’s University Belfast, UK Harvey Goldstein, University of Bristol, UK Anthony Green, University of Bedfordshire, UK Sandra Johnson, University of Bristol, UK Joshua McGrane, Oxford University Centre for Educational Assessment, UK Pauline Rea-Dickins, Oxford University Centre for Educational Assessment, UK Gordon Stobart, UCL Institute of Education, UK Sally Thomas, University of Bristol, UK Guoxing Yu, University of Bristol, UK

Assessment in Education: Principles, Policy & Practice

Recently, blockchain technology has gained considerable attention from researchers and practitioners. This is mainly due to its unique features including decentralization, security, reliability, and data integrity. Despite this growing interest, little is known about the current state of knowledge and practice regarding the use of blockchain technology in education. This article is a systematic review of research investigating blockchain-based educational applications. It focuses on three main themes: (1) educational applications that have been developed with blockchain technology, (2) benefits that blockchain technology could bring to education, and (3) challenges of adopting blockchain technology in education. A detailed results analysis of each theme was conducted as well as an intensive discussion based on the findings. This review also offers insight into other educational areas that could benefit from blockchain technology.

Blockchain-Based Applications in Education: A Systematic Review

Periocular biometrics is the recognition of individuals based on the appearance of the region around the eye. Periocular recognition may be useful in applications where it is difficult to obtain a clear picture of an iris for iris biometrics, or a complete picture of a face for face biometrics. Previous periocular research has used either visible-light (VL) or near-infrared (NIR) light images, but no prior research has directly compared the two illuminations using images with similar resolution. We conducted an experiment in which volunteers were asked to compare pairs of periocular images. Some pairs showed images taken in VL, and some showed images taken in NIR light. Participants labeled each pair as belonging to the same person or to different people. Untrained participants with limited viewing times correctly classified VL image pairs with 88% accuracy, and NIR image pairs with 79% accuracy. For comparison, we presented pairs of iris images from the same subjects. In addition, we investigated differences between performance on light and dark eyes and relative helpfulness of various features in the periocular region under different illuminations. We calculated performance of three computer algorithms on the periocular images. Performance for humans and computers was similar.

Human and Machine Performance on Periocular Biometrics Under Near-Infrared Light and Visible Light

Several initiatives have been proposed to collect, report, and analyze data about school systems for supporting decision-making. These initiatives rely mostly on self-reported and summarized data collected irregularly and rarely. They also lack a single independent and systematic process to validate the collected data during its entire lifecycle. Furthermore, schools in developing countries still do not maintain complete and up-to-date school records. Due to these and other factors addressing the education challenges in those countries remains a high priority for local and international governments, donor and non-governmental agencies across the world. In this paper, we discuss our initial design, implementation, and evaluation of a blockchain-enabled School Information Hub (SIH) using Kenya's school system as a case study.

Towards Blockchain-enabled School Information Hub

Affective computing relates to, arises from, or intentionally influences emotion. It is a continuously growing multidisciplinary field that explores how technology can inform an understanding of human affect, how interactions between humans and technologies can be impacted by affect, how systems can be designed to utilize affect to enhance capabilities, and how sensing and affective strategies can transform human and computer interaction. Encompassing disciplines, such as engineering, psychology, education, cognitive science, sociology, and others; this chapter explores some of the historical foundations and general goals of affective computing, approaches to affect detection and generation, applications, ethical considerations, and future directions.

Affective Computing: Historical Foundations, Current Applications, and Future Trends

An example operation may include one or more of obtaining a first biometric sample of a user from a user device. extracting, by an issuing node of a permissioned blockchain network, a biometric template from the first biometric sample, encrypting the biometric template, distributing an issuetoken proposal comprising the encrypted biometric template to the blockchain network, and generating and distributing a biometric token to the user device. In response to the user indicating to the user device to redeem the biometric token, the method includes one or more of presenting, by the user device, the biometric token to a verifying node of the blockchain network, validating, by the verifying node, the biometric token, receiving, by the verifying node, a second biometric sample from the user device, distributing a redeemtoken proposal to the blockchain network, committing a transaction corresponding to the biometric token, to the blockchain network, and invalidating the biometric token.

Biometric token for blockchain

Numerous applications require users to interact with a multitude of entities in order to avail a service. In such applications, the identity of the user is typically verified through physical or digital tokens, which are prone to both identity theft (lost or stolen tokens) and repudiation claims by malicious users. The use of biometrics can provide non-repudiability by ensuring that a purchaser is the bonafide user of the service. However, in applications entailing multiple stakeholders, there may be privacy issues with sharing user's biometrics data. While this concern can be addressed by storing the user's biometric data on the token itself, strong mechanisms are required to ensure that token is both secure and tamper-proof. In this paper, we propose a single use biometric token that relies on Shamir's secret sharing algorithm and blockchain technology to ensure that the encrypted biometric template contained in the token is secure, tamper-proof, and any attempt to use the issued token is irrefutably logged to prove subsequently that the user indeed availed the service. We also analyze issues related to the system security, user privacy, and usability of the proposed solution.

Shelby Solomon Darnell

Papers

Human and Machine Performance on Periocular Biometrics Under Near-Infrared Light and Visible Light

Towards Blockchain-enabled School Information Hub

Affective Computing: Historical Foundations, Current Applications, and Future Trends

Biometric token for blockchain

Secure one-time biometrie tokens for non-repudiable multi-party transactions