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BOCA: A novel semantic blockchain-based authentication system of educational certificates
Abstract
In industrial and academic working environments, illegitimate academic certificates have been prepared by individuals who aim to be employed without completing regulated training and education programs. This violation has made an unjust confusion between genuine and fake certificates. Within the hiring process, employers thus need a reliable mechanism for verifying academic certificates that ensures the integrity of data. In accordance with this aim, blockchain technology has been introduced and deployed at some universities supporting fraud prevention or secure access to certificates. However, the method of handling knowledge in these educational systems was not investigated devotedly. This paper introduces an authentication framework of educational certificates that employed blockchain and ontology technologies, named BOCA. The learning ontology (LeOn), which was used to represent the central knowledge model of the system, was assigned to semantically manage the domain knowledge and link the educational data to the blockchain network. The system features, including the working process, the LeON ontological development, and the rule base construction, are described in detail. The system deployment on Hyperledger Fabric yielded promising experimental results. Ongoing work focuses on improving system performance and allowing semantic search on data blocks.
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In personalized learning, each student gets a customized learning plan according to their pace of learning, instructional preferences, learning objects, etc. Hence the content recommender system in Personalized Learning Environment (PLE) should adapt to learner attributes and suggest appropriate learning resources to aid the learning process and improve the learning outcomes. This systematic literature review aims to analyze and summarize the studies on learning content recommenders in adaptive and personalized learning environments from 2015 to 2020. The publications were searched using proper keywords and filtered using the inclusion and exclusion criteria, which resulted in 52 publications. This paper summarizes the recent trends in research on different aspects of the recommender systems, such as learner attributes, recommendation methods, evaluation metrics, and the usability tests used by the researchers. It is observed that cognitive aspects of learners like learning style, preferences, knowledge level, etc., are used by most studies than non-cognitive aspects as social tags or trust. In most cases, recommendation engines are a hybrid of collaborative filtering, content-based filtering, ontological approaches, etc. All models were evaluated for the correctness of the prediction done, and a few studies have also done evaluations based on learner satisfaction or usability.
Certificate is used to measure and assess the skills that a person possesses. This is used for pursuing higher studies, getting jobs, rewarding a person, etc. Nowadays, it is evident that admission forgery happens by producing fake certificates very frequently. Hence, verification of certificates becomes highly essential to overcome the issue of fake certification. Blockchain is a technology that provides solution to this problem. Blockchain enables peer-to-peer transfer of assets without any intermediaries. This chapter presents a framework for blockchain-enabled certificate verification system using robotics technology. Here, in this system, robotic cameras are being used to scan the certificates and store them on cloud using Arduino Uno connected to a WiFi device. Later on, the same has been stored permanently on blockchain in the form of blocks. Since the smart contract is computational component of the technology, hence, the chapter depicts a smart contract for storing of a certificate in blockchain and verifying it. The smart contract has been written as well as tested for its proper functioning, and the objectives had been achieved. Two softwares Sublime Text3 and Remix Ethereum IDE were used for writing and testing of the smart contract, respectively. This smart contract enables the employer to check the stored certificate which eases the task of verifying the job seeker’s certificates. This smart contract can be taken by students, employers as well as educational institutes.
Accurate and complete educational records are a valuable asset for people. In recent years, educational records have been digitized. However, there are still two key challenges that have not been resolved. One is to achieve secure and privacy-preserving storage of educational records, while another concern how to realize the sharing of educational records and ensure the security of the sharing process. In this paper, we propose EduRSS, a blockchain-based storage and sharing scheme for educational records is proposed, which combines blockchain, storage servers, and cryptography techniques to create a reliable and safe environment. In our proposal, the blockchain technology is used to ensure the security and reliability of data storage, while the smart contracts on the blockchain are used to regulate the process of storage and sharing. More precisely, the off-chain storage servers store the original educational records in encrypted form, while the hash information of the records is stored on the blockchain. The off-chain records are anchored periodically with the hash information on the blockchain to ensure the security of data storage. Cryptography techniques are utilized to handle records encryption and messages digital signature. To assess the effectiveness of EduRSS, we designed and tested a proof of concept of this scheme. The relative security analysis shows that EduRSS is safe and has a lower computational cost than that of the CP-ABE and the MA-CPABE schemes.
Nowadays, various online education platforms (such as MOOCs, Coursera, XuetangX and so on) not only provide a broad Internet environment for sharing multimedia learning resources, but also bring a series of challenges in digital rights management, such as the infringement of digital copyrights of multimedia learning resources, the insecurity of digital education certificates, and the low degree of openness of multimedia learning resources. To sovle these issues, we propose a blockchain-enabled digital rights management system, which includes an entirely new network architecture for sharing and managing multimedia resources of online education on the basis of the combination of the public and private blockchains, as well as three specific smart contract schemes for the realization of the recording of multimedia digital rights, the secure storage and the unmediated verification of digital certificates, respectively. The proposed blockchain-enabled digital rights management system has been demonstrated as a promising candidate solution to the blockchain-based multimedia data protection in an online education environment.
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.
Abstract It is a common practice to issue a summary of a learner’s learning achievements in form of a transcript or certificate. However, detailed information on the depth of learning and how learning or teachings were conducted is not present in the transcript of scores. This work presents the first practical implementation of a new platform for keeping track of learning achievements beyond transcripts and certificates. This is achieved by maintaining digital hashes of learning activities and managing access rights through the use of smart contracts on the blockchain. The blockchain of learning logs (BOLL) is a platform that enable learners to move their learning records from one institution to another in a secure and verifiable format. This primarily solves the cold-start problem faced by learning data analytic platforms when trying to offer personalized experience to new learners. BOLL enables existing learning data analytic platforms to access the learning logs from other institutions with the permission of the learners and/or institution who originally have ownership of the logs. The main contribution of this paper is to investigate how learning records could be connected across institutions using BOLL. We present an overview of how the implementation has been carried out, discuss resource requirements, and compare the advantages BOLL has over other similar tools.
Semantic web and its technologies have been eyed in many fields. They have the capacity to organize and link data over the web in a consistent and coherent way. Semantic web technologies consist of RDF schema, OWL, and rule and query languages like SPARQL and these technologies will help the various domains to resolve their problems. This review paper starts with analyzing the nature of semantic web and its requirements. We have considered all 10 domains which are closely related to semantic web and its technologies. For a better understanding of the paper, we have separated it into three major contributions. First, we analyze semantic web and those domains that increase the growth of the semantic web. Second, we discuss all domains where semantic web technologies play a vital role. Third, we emphasize those domains that go hand in hand with semantic web technologies. This review paper will be utilized as an unbiased direction for the researchers.
Blockchain educational technology has created assessment and management tools for learner credentials that are permanent, transparent and sustainable while giving users direct access. Personal encrypted credentials enable users to shape lifelong learning pathways and personalizes education according to individual values and needs. They allow for the permanent documentation of both formal and informal learning based on transversal competencies, adjustable across the economic sector and responsive to situational needs. Badging was the initial response to online credentialing. Mozilla’s open digital badges have become the unofficial global standard and the specifications remain free. They may be viewed in e-portfolios and social networks. Yet, if issuers cease hosting badges, they become invalid even when authentic. Some experiments with blockchain technology remedy this situation by creating a permanent, secure and sustainable infrastructure for learning records. The MIT Media Lab has produced the bitcoin based Blockcerts; whereas the Knowledge Institute, Open University, UK has developed Ethereum’s Smart Contracts to document Microcredentials (Badges). Both are Open Source products. Most EU nations are experimenting with educational blockchain. The technology creates an infrastructure to document, store and manage credentials and provides learners with a sustainable record of achievements they can control. It also benefits universities by reducing administrative costs and bureaucracy.
The Blockchain technology has witnessed a boost in adaptability with respect to its application especially in distributed public ledgers dealing in the financial and academic sectors. However, the major drawbacks of this technology cause hindrance for sustaining in a longer run. Which is why applications solely built on Blockchain might also witness a decrease in their adaptability. Tangle, on the other hand, provides a more suitable and reliable system which also addresses the drawbacks of Blockchain. In this paper, we propose a framework to authenticate academic degrees and certificates built on Tangle so that the intermediate and middle parties which verify the transaction or data are eliminated, having a decentralized control with complete visibility to all the actors involved in the system. Additionally, Tangle provides a quantum resistant security mechanism and a highly scalable architecture.
Blockchain is the core technology used to create the cryptocurrencies, like bitcoin. As part of the fourth industrial revolution since the invention of steam engine, electricity, and information technology, blockchain technology has been applied in many areas such as finance, judiciary, and commerce. The current paper focused on its potential educational applications and explored how blockchain technology can be used to solve some education problems. This article first introduced the features and advantages of blockchain technology following by exploring some of the current blockchain applications for education. Some innovative applications of using blockchain technology were proposed, and the benefits and challenges of using blockchain technology for education were also discussed.
Modeling an ontology is a hard and time-consuming task. Although methodologies are useful for ontologists to create good ontologies, they do not help with the task of evaluating the quality of the ontology to be reused. For these reasons, it is imperative to evaluate the quality of the ontology after constructing it or before reusing it. Few studies usually present only a set of criteria and questions, but no guidelines to evaluate the ontology. The effort to evaluate an ontology is very high as there is a huge dependence on the evaluator's expertise to understand the criteria and questions in depth. Moreover, the evaluation is still very subjective. This study presents a novel methodology for ontology evaluation, taking into account three fundamental principles: i) it is based on the Goal, Question, Metric approach for empirical evaluation; ii) the goals of the methodologies are based on the roles of knowledge representations combined with specific evaluation criteria; iii) each ontology is evaluated according to the type of ontology. The methodology was empirically evaluated using different ontologists and ontologies of the same domain. The main contributions of this study are: i) defining a step-by-step approach to evaluate the quality of an ontology; ii) proposing an evaluation based on the roles of knowledge representations; iii) the explicit difference of the evaluation according to the type of the ontology iii) a questionnaire to evaluate the ontologies; iv) a statistical model that automatically calculates the quality of the ontologies.
The ‘blockchain’ is the core mechanism for the Bitcoin digital payment system. It embraces a set of inter-related technologies: the blockchain itself as a distributed record of digital events, the distributed consensus method to agree whether a new block is legitimate, automated smart contracts, and the data structure associated with each block. We propose a permanent distributed record of intellectual effort and associated reputational reward, based on the blockchain that instantiates and democratises educational reputation beyond the academic community. We are undertaking initial trials of a private blockchain or storing educational records, drawing also on our previous research into reputation management for educational systems.
The purpose of this paper is to present an approach to create semi-automatically ontology from Arabic texts. The whole process is supervised by a linguistic expert. Our involvement in this project focused on a lexical ontology, taking as model the WordNet ontology, and as input source, the “Arabic verbs” of a contemporary monolingual dictionary () /mζjm Alγny/ in the form a lexical database. The verb, pivot of a sentence, is our goal in creating concepts, by adopting the synset as our meaning representation model. The Markov clustering algorithm of a graph, generated by the defining verbs, obtained from the transitive closure, allowed us to detect similar verbs and to identify as well, for a given verbal entry, all of its synonyms. A tool has been implemented, and experiments have been carried out to evaluate and show efficiency of the proposed approach.
This paper demonstrates how to use MONTO—machine-readable ontology for teaching word problems in mathematics. MONTO is a combination of various ontologies. After presenting a review of the literature of problem solving and math education, this paper presents a framework that is used for evaluation of the systems available in the literature for teaching problem solving in mathematics. This paper analyzes the existing systems and evaluates them against the framework to state the gaps. It also describes MONTO and demonstrates its use. This paper also discusses how the use of MONTO bridges the gaps found in the literature of tutoring systems used for teaching problem solving. A description of the system implemented using MONTO is included along with the key functionalities of the system derived from the ontology. A discussion of how these functionalities are useful for teaching word problems is included too. This paper also presents the results of a small-scale study conducted to evaluate the functionalities that are derived from the ontology.
Robinson lists are adopted in many countries to protect phone subscribers against commercial spam calls. In its essence, they collect the denial of the subscribers to be contacted by marketing operators. Nowadays, all Robinson lists run as centralised services. Namely, citizens have to rely on trusted third parties for the management of their own choices. The Blockchain allows us to envision the development of a decentralised Robinson list in which citizens are finally empowered to autonomously manage their choices. In this paper, we present a proof-of-concept (PoC) of a decentralised Robinson list developed with the Algorand technology. To the best of our knowledge, this is the first attempt to implement a Robinson list on a blockchain technology. The PoC has been designed to support the requirements provided by Fondazione Ugo Bordoni, the manager of the Italian Robinson list. The evaluation of the PoC shows that our decentralised solution provides satisfactory performance, in terms of scalability, latency and costs, when compared to the current centralised service.
The Internet of Drones (IoD) is an emerging domain due to its capability of being deployed in several domains. The drones in IoD are capable of exploring the platform and transfer commodities with embedded sensors. However, the data accumulated by drone sensors face privacy and security issues due to advanced technologies. This paper devises a blockchain-based access control scheme for initiating secure communication among the drones in IoD. The system has four different entities that involve the Drone, server, user, and control room. The proposed Blockchain-based access control scheme involves two phases: the authentication and access control phases. The authentication phase is performed considering sender drone credentials, and the access control phase is done using four methods. In the access control phase, four kinds of access control mechanisms are considered: Drone to drone access control, Drone to server access control, Emergency access control if drone failure and Control set up with blockchain technology. Both the communicating entities can establish the secret key for secure communication at the end of access control. The proposed Blockchain-based access control scheme provided superior performance concerning classical methods with a minimal end-to-end delay of 0.870sec, a minimal packet loss rate of 2%, and maximal throughput of 70.493bps.
In the last decade various crypto-currencies opened new doors to a decentralized electronic monetary system. Emergence of new Blockchain platforms, such as Ethereum, introduced new features for the implementation of decentralized software or smart contracts. The applications of blockchain technology for secure and efficient information systems is rapidly increasing. However, due to the limitations of this platform including high computational and storage cost, it is not possible to run sophisticated and computationally expensive software on the blockchain. In this paper, a new framework for execution of smart programs on blockchain called the Smart Program Runner Framework (SPRF) is proposed. The proposed framework works by moving decentralized applications to the off-chain and only storing the hash of the state of the application on-chain. This framework can be implemented by creating a side-chain to an existing blockchain without any modifications. The proposed framework is implemented on Stellar blockchain and has various applications for secure and efficient information systems and can provide the required platform for execution of computationally demanding software on blockchain.
The study intends to identify the emerging themes of e-learning through the Semantic Web. To highlight the key challenges and explore the core benefits of this mesmerizing technology was another goal of the study. To get the set goals researchers systematically reviewed the literature in five leading databases, out of which one specialized database of education; ERIC and four general databases i.e Scopus, J-store, Science Direct & Google Scholar. The preferred reporting items were used for systematic review and meta-analysis (PRISMA) guidelines. The selected 22 research studies identified eight emergent themes within the body of research. In answer to the second part of the research study, the review shows that Semantic Web technology has opened new horizons for e-learning. On the other hand, data analysis of selected studies reflects the technological, socio-cultural and other challenges which may cause the hurdle for the realization of these goals in true sense. The overall result shows, interoperability, data security & privacy, ontology’s & crowd sourcing technology or automatic annotation as future research trends indicated by the identified studies to meet up these challenges. This SR may be beneficial for stakeholders to understand the e-learning scenario through Semantic Web technology.
The large number of counterfeit certificates in circulation is a huge problem that has been prevalent for a long time. Issuing of such certificates has become a business stemming from the need/want of the people for employment. Hard working people with legitimate degrees/certificates have to suffer the consequences of this phenomenon since they are denied what could have been theirs by the holders of these fake credentials. It a lot of cases this can prove extremely dangerous for example, consider a surgeon operating on the basis of a fake degree. It is situations like these that highlight the need for a system which can provide verification and authentication of the certificates, its issuer and the holder. In this paper, leveraging the tamperproof and non-repudiation property of blockchain, we propose and implement a certificate issuing and verifying model.
We are interested in the acquisition of instances of concepts from a text resource. These concepts are defined in the multi-viewpoints ontology. The multi-viewpoints ontology allows giving several definitions of a single concept. Each definition is guaranteed by a viewpoint. In the multi-viewpoints ontology, a single individual is an instance of several concepts. That is, which we call the multi-instantiations. The acquisition of the multi-instantiations from a resource requires alignment between the resource elements and the multi-viewpoints ontology elements. The structure of the multi-viewpoints ontology and the semantic constraints of the multi-viewpoints ontology concepts differ from the classical ontology’s. For that, the existing processes, which allow aligning the resource element with a classical ontological concept, cannot align the resource element with a multi-viewpoints ontology concept. Thus, we propose a new process, which offers a possibility to align resource elements with multi-viewpoints ontology concepts in order to acquire the multi-instantiations. The obtained multi-instantiations will be represented in the Multi-Viewpoints Ontology Language, in order to be integrated into the multi-viewpoints ontology.
The precedence of unexplored Uniform Resource Locators (URLs) is calculated in many existing works based on a linear combination of similarities of different texts of the web_page and the specified topic along with their associated weights. These weights, however, are chosen based on various methodologies like Term Frequency-Inverse Document Frequency (TF-IDF), so these weights can immediately create severe deviations from the priorities of unvisited web pages and also it will calulate the similarity only if the word occurs in the web page. It won’t consider the semantic similarity of the word in the web page. To overcome the troubles mentioned above, this article presents a new focused web crawler based on combined Normalized Pointwise Mutual Information (NPMI) and Resnik based semantic similarity algorithm, called as P-crawler. In the P-crawler, the records of an unexplored web page are made up of web page text, anchor text, title text, bold text and heading text of the web page. The experimental findings show that the suggested algorithm increases focused on crawler efficiency. In conclusion, the above technique is efficient and promising for focused web crawlers.
This research is still in progress and focuses on using the blockchain for the verification of the authenticity of issued certificates. In this first stage of the research we are presenting a prototype that allows the registration of academic institutions and its respective institutes/faculties, registration of student cohorts and issuing of certificate awards. The issued certificates are registered on the blockchain so that any third party who would need to verify the authenticity of a certificate can do so, independently of the academic institution, even in the event that such institution has closed. The next phase of this research aims to extend the prototype to the registration of medical records on the blockchain with a focus on the privacy of sensitive data and allowing the owner of the information to control user access to the documents. The final phase of the research will involve gathering user and corporate feedback on the proposed prototypes.
The traditional educational paradigm has been nowadays transformed to tech-aided personalised learning, tailored to individual learning styles and needs, applicable in any environment. Such an educational framework should provide capabilities for adaptive, affective and interactive learning, taking advantage of technological means to recognize the learners’ performance, behaviour and progress over the learning process. A novel methodology is proposed to model an educational framework able to represent and optimally foster these needs, along with a methodology for non-linearly adapting networked learning objectives. In addition, the framework is supported with an ontology that enables personalised and contextualised decision-making over learning activities on autonomous devices, enabling their dynamic modularisation during the learning process.
Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (www.hyperledger.org).
Fabric is the first truly extensible blockchain system for running distributed applications. It supports modular consensus protocols, which allows the system to be tailored to particular use cases and trust models. Fabric is also the first blockchain system that runs distributed applications written in standard, general-purpose programming languages, without systemic dependency on a native cryptocurrency. This stands in sharp contrast to existing block-chain platforms that require "smart-contracts" to be written in domain-specific languages or rely on a cryptocurrency. Fabric realizes the permissioned model using a portable notion of membership, which may be integrated with industry-standard identity management. To support such flexibility, Fabric introduces an entirely novel blockchain design and revamps the way blockchains cope with non-determinism, resource exhaustion, and performance attacks.
This paper describes Fabric, its architecture, the rationale behind various design decisions, its most prominent implementation aspects, as well as its distributed application programming model. We further evaluate Fabric by implementing and benchmarking a Bitcoin-inspired digital currency. We show that Fabric achieves end-to-end throughput of more than 3500 transactions per second in certain popular deployment configurations, with sub-second latency, scaling well to over 100 peers.
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.
On the way to increasing customization in e-learning systems, the learner model is the main source of variability. Such a model includes a number of psychological characteristics and study preferences that describe the learner's personality traits related to learning. During the last decades, the design methods and tools for e-learning have been designed assuming specific learner models. Therefore, in the search for a learning environment suitable for as many learner models as possible, we need tools to explore -and exploit- such models. In general, the learner's characteristics can be linked to the so-called learner's learning style (which is a part of the learner model) to provide the instructor with extensive knowledge about the learner's characterization in perceiving and processing information. Numerous learning styles have been proposed in the last decades, in some cases with overlapping characteristics with the same or different names. Thus, the heterogeneity of the learning style space makes it difficult to handle customization effectively. In this paper, we introduce a Learner's Characteristics Ontology based on creating interconnections between the different learning style model dimensions and learning styles with the relevant learner's characteristics, that: (1) helps instructors to improve and personalize the learning content; (2) can recommend learning materials to learners according to their learning characteristics and preferences; (3) can provide both instructors and learners with extensive knowledge about how they can improve their teaching and learning abilities; and (4) can improve communications and interaction between humans and computers by specifying the semantics of the learning style models' characteristics.
Recent developments in the area of deep learning have been proved extremely beneficial for several natural language processing tasks, such as sentiment analysis, question answering, and machine translation. In this paper we exploit such advances by tailoring the ontology learning problem as a transductive reasoning task that learns to convert knowledge from natural language to a logic-based specification. More precisely, using a sample of definitory sentences generated starting by a synthetic grammar, we trained Recurrent Neural Network (RNN) based architectures to extract OWL formulae from text. In addition to the low feature engineering costs, our system shows good generalisation capabilities over the lexicon and the syntactic structure. The encouraging results obtained in the paper provide a first evidence of the potential of deep learning techniques towards long term ontology learning challenges such as improving domain independence, reducing engineering costs, and dealing with variable language forms.
Besides attracting a billion dollar economy, Bitcoin revolutionized the field of digital currencies and influenced many adjacent areas. This also induced significant scientific interest. In this survey, we unroll and structure the manyfold results and research directions. We start by introducing the Bitcoin protocol and its building blocks. From there we continue to explore the design space by discussing existing contributions and results. In the process, we deduce the fundamental structures and insights at the core of the Bitcoin protocol and its applications. As we show and discuss, many key ideas are likewise applicable in various other fields, so that their impact reaches far beyond Bitcoin itself.
This paper describes a scenario-based methodology called the NeOn Methodology framework. The aim of this framework is to speed up the construction of ontologies and ontology networks by reusing available knowledge resources (ontologies, non-ontological resources and ontology design patterns). The methodology is founded on four pillars: (1)a glossary of processes and activities; (2)a set of nine scenarios for building ontologies and ontology networks; (3)two ontology life-cycle models; and (4)a set of prescriptive methodological guidelines for performing specific processes and activities. The paper also shows how to apply this methodology framework to develop an ontology network within the multimedia domain. Finally, it presents an empirical evaluation of the NeOn Methodology framework.
We develop a sociological context for understanding the phenomenon of falsely claimed educational credentials and analyze national data that cast light on the incidence of false degrees. We find that about 6% of Bachelor's degrees and 35% of Associate's degrees are falsely claimed. Most individuals who falsely claim degrees have attended the college in question. Many have nearly completed the required credits, but claim a degree without having finished. The socio-demographic profile of persons falsely claiming credentials is consistent with Merton's theory of innovative deviance, but not with the theory of status inconsistency.
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
In this paper, we present a brief overview of Pellet: a complete OWL-DL reasoner with acceptable to very good performance, extensive middleware, and a number of unique features. Pellet is the first sound and complete OWL-DL reasoner with extensive support for reasoning with individuals (including nominal support and conjunctive query), user-defined datatypes, and debugging support for ontologies. It implements several extensions to OWL-DL including a combination formalism for OWL-DL ontologies, a non-monotonic operator, and preliminary support for OWL/Rule hybrid reasoning. Pellet is written in Java and is open source.
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