Design thinking is an important tool for connecting innovation ability with practical problems. Design thinking, as a systematic approach to thinking concepts, processes, and learning tools, can provide new ideas for educational reform and the cultivation of talents in the future. Introducing design thinking into higher education and establishing an effective and innovative curriculum system is also aimed at better cultivating innovative talents. Based on the characteristics of blockchain technology such as decentralization, security and equality, this study builds a platform for design thinking education and expounds the practical problems such as the lack of thinking enthusiasm and motivation of students in the existing education model and the transformation of theory into practice. Analyze the possibility that blockchain technology can help students stimulate their creativity through incentive mechanisms, protect students' design achievements through distributed ledgers, and enhance their employment competitiveness. While blockchain technology makes it easier for colleges and universities to implement design thinking education, it also gives them new ideas and opportunities to implement creative teaching based on design principles, creates an equitable and effective learning environment for students, and gives them access to a better learning platform.
As the cryptocurrency market continues to evolve, phishing scams are considered one of the most deceptive forms of fraud. Currently, most existing Ethereum phishing detection methods rely on traditional machine learning or graph representation learning, mainly depending on local statistical and structural features. This can lead to insufficient utilization of transaction graph data across different scales. To address this challenge, we propose Multi-transaction-view Graph Attention Network (MTvGAT), which fully leverages edge features between nodes at different scales and discovers relationships between nodes. Two types of graphs are used to model Ethereum transactions: global views and local views. Global views are constructed by partitioning the complete transaction graph using graph clustering algorithms and inputting them into MTvGAT to obtain global view representations. For each target node, a local view is constructed by sampling K-hop neighbors from the transaction network. Importantly, attention coefficients are calculated between nodes, and edge coefficients are obtained by fusing edge features and attention coefficients, utilizing spatial structure and edge coefficients to enable the phishing detection model to access multi-view sources of information. Experimental results demonstrate that the multi-view graph attention network outperforms existing algorithms in detecting Ethereum phishing scams datasets.
This paper comprehensively discusses the security mechanism of blockchain-based digital currency transactions, from the application of distributed ledgers, consensus algorithms, smart contracts, to the implementation of multiple signatures and cold storage schemes, to advanced privacy protection technologies, such as zero-knowledge proofs and homomorphic encryption. In particular, we delve into innovative mechanisms for attack prevention, including the fusion of heterogeneous multi-chain architectures with PoW+PoS hybrid consensus models. The article also details the practice of performance evaluation and security testing through a series of carefully designed experiments such as throughput and latency testing under different loads, resource utilization monitoring, and security reviews and comparisons with competitors. Experimental results show that the system exhibits good throughput growth under high load, but with the increase of latency, resource utilization is efficient and tends to saturation, most of the security protection mechanisms meet the standards, but access control problems that need to be optimized and high-risk vulnerabilities to be repaired are also found.
Sayeed Ebrahim Darwishean, Abdul Qahar Jawad, Nangialai Nangial
The study explores how to synergize Public Relations 3rd Generation (PR3.0), 3rd generation of the web (Web3.O), and new technologies to have an effective interactive online higher education (OHE) in Afghanistan. It analyzed the distinguishing characteristics of the three concepts by focusing on their application in the context of OHE in the country, aiming to assess the trio's compatibility in Afghanistan. Thus, a prescriptive methodology was used in this study. The findings indicate that the trio possesses common individualities that could be applied productively in the context of Afghanistan for collaborative higher education. The communal features include interactivity, ubiquity, and mobility, which indicate the compatibility of the concepts in the country. New technologies are accessible with the light version of applications for low-speed internet and are installable in smartphones, showing their usability. The 3rd generation of public relations (PR3.0) should be synergized with the two others to produce an effective online scheme of higher education in Afghanistan.
Open access
Politics and Conflicts in Afghanistan, Pakistan, and Middle East
Researching the taxonomy of cryptocurrencies, this study examines the relationships between researchers, their affiliated institutions, and the countries they are associated with. Data from Scopus (Elsevier) and the Web of Science Core Collection were employed, mainly publications from 2005 to 2023. By leveraging tools like VOSviewer, Biblioshiny, and Microsoft Excel, we pinpointed influential research on cryptocurrency taxonomy, collaboration networks among researchers, thematic groupings, and research trends. Our findings indicate that although research collaboration is still evolving, the insights extracted in the thematic analysis outline the structure, components, and implications of taxonomy in the context of blockchain and cryptocurrencies, providing a foundational understanding. The limitation arises from the restricted timeframe, as the data was collected in August 2024. Given the dynamic nature of cryptocurrencies, the bibliometric analysis might benefit from updates to capture the latest developments.
With the rapid advancement of information technology, the sharing of educational resources has become an integral component of the modern educational system. However, traditional data elements in educational resources face challenges such as data security, copyright protection, and trust mechanisms. Blockchain technology, as a distributed ledger technology, offers innovative solutions for the sharing of educational resources data elements with its characteristics of immutability, decentralization, and transparency. This paper designs an educational resource sharing platform based on blockchain technology, and experiments have demonstrated that by optimizing the blockchain threshold elimination model, the overall performance of the platform can be enhanced, improving the security of data processing and achieving satisfactory results.
Cryptocurrency being a digital or virtual currency that uses cryptography to secure transactions and control the creation of new units. Bitcoin, one of the most popular cryptocurrency, offers various advantages such as security, transparency, and efficiency. The value of Bitcoin can change over time, similar to the regular currencies, and the need to predict the value can be as important as those in the regular. The prediction can be done by multiple algorithms. The purpose of this research is to compare five algorithms in predicting bitcoin value based on Root Mean Squared Error (RMSE) and Squared Error (R2). The five algorithms compared can model the prediction of changes in the bitcoin cryptocurrency, effectively. Based on the experiment, Random Forest outperformed the other algorithms based on its RMSE and R2 result
The anonymity of blockchain and its inadequate supervision make it difficult to investigate criminal activities on the blockchain. In recent years, criminals have profited from deploying Ponzi schemes on the Ethereum blockchain through smart contracts, resulting in substantial economic losses and adverse impacts, seriously impeding the development of the blockchain community and technology. However, despite some research on identifying Ponzi schemes on Ethereum, existing methods face certain difficulties in data acquisition, complex feature construction, and insufficient exploration of opcode data features. To address these issues, this paper proposes a method that only relies on smart contract opcodes to verify whether a contract is a Ponzi scheme. Specifically, Word2vec word embedding technology is first used to train the data, obtaining opcode word vector representations through the training process. Subsequently, by passing the word vectors into the Convolutional Neural Network (CNN) and Bidirectional Gated Recurrent Unit Network (BiGRU) models, spatial and semantic features are extracted to better capture semantic information at different levels of smart contract opcodes. The attention mechanism allocates different weights to various features, highlighting key attributes. The results of the experiment show that the proposed method displays a strong detection performance, indicating specific improvements in precision, recall, and F1 score in contrast to previous methods.
Byeongchan Park, Se‐Young Jang, Seok-Yoon Kim, Youngmo Kim
Due to the Corona-19 pandemic phenomenon, various video service platforms that provide OTT (Over The Top) services such as 'Netflix' have achieved rapid growth.OTT platforms that provide such video content do not disclose the viewing time of the content watched by users due to various issues such as personal information protection, so stakeholders are conducting third-party research on usage patterns.While an objective and reliable third-party method of investigating usage patterns is needed, efforts to protect personal information are also needed in the process.The information required for viewership surveys to investigate usage patterns only requires information about what content is used and to what extent, and does not require personal information about users.In this paper, we propose a method to generate and verify the generated usage information by de-identification using zero-knowledge proof protocol when a user selects a specific OTT platform and uses content through an OTT player agent that provides OTT services.
Combining the characteristics of blockchain technology with distributed ledger, consensus mechanism, encryption algorithm, etc., this paper proposes a filtering algorithm based on intangible cultural heritage, builds a video tracking scanning imaging model of dancers in ethnic areas, and detects the edges of video images of dancers in ethnic areas.The contour model is used to enhance the video images of dancers in ethnic areas according to the initial contour distribution, and establish a visual perception model of the dancers in ethnic areas.Sequence, the posture probability of the observation sequence is obtained through the forwardbackward algorithm, and the corresponding posture of the hidden Markov model with the largest observation sequence probability value is the dance tossing posture that needs to be recognized.
Abstract In view of the node security risks and key management vulnerabilities in heterogeneous sensor networks, a key management protocol for heterogeneous sensor networks based on zero trust security and chaotic neural networks (KMPHSN-ZTSCNN) was proposed. Taking advantages of the decomposition difficulty of singular matrix and chaotic classification characteristics of Hopfield overload chaotic neural network, the node registration and authentication of sensor network were achieved by blockchain and zero-knowledge proof. The channel state information (CSI) and the adjustable mathematical function were relied on to generate a dynamically changing key to complete continuous verification and achieve zero trust security authentications, thus ensuring data security. The protocol can dynamically allocate different keyspace sizes according to the security level of the group, the storage capacity if the nodeand computing capacity and can adapt to the asymmetric structure of heterogeneous sensor networks. Theoretical proof and experimental performance analysis results show that the protocol is feasible and can meet the security requirements of heterogeneous sensor networks.
As the growing interest of investment on Cryptocurrencies and the huge volatility of their price, a need for scientific model to predict the future price is growing.In this context, the paper uses linear regression and LSTM model to predict the price of Bitcoin and Ethereum.The result shows that the prediction made by Linear Regression shows less errors but greater lag compared with the prediction made by LSTM method.The lag problem is considered to generate from lack of peripheral information other than previous prices.The prediction implies that the prices of Cryptocurrencies are theoretically predictable, and shows a direction of further research, such as the use of mixed-LSTM model.The methods provided in this paper can be used in development of better models and further investments.
More and more shared products and services have been introduced to the market one after another, which has changed the traditional Chinese economic model. The construction of digital teaching resources is one of the important contents of higher education informatization. Today, with the extremely developed network, the problem of sharing digital teaching resources in colleges and universities becomes more and more prominent. Network can not only realize the sharing of educational resources, but also greatly expand the information exchange between teachers and students, and create a learning environment for individual teaching for learners. With the continuous improvement of technology and the maturity of application, the Blockchain and new energy and related applications will develop rapidly under the impetus of the government and the huge social demand. As a new force to change the Internet, Blockchain and new energy will bring great changes to information resource sharing activities and information service institutions. This paper explores the application of Blockchain and new energy technology in the co construction and sharing mode of digital teaching resources in Colleges and universities through the research on the participation subjects of block chain technology and digital teaching resources co construction and sharing.
Blockchain technology is considered to be the most important invention of human society since the birth of the Internet, which is deeply influencing the operation concept, organization and business mode of institutions or services such as global governance, economic development, finance and education, especially in the banking, securities, insurance, notarization, music, distributed storage, Internet of things and other industries and fields. At the same time, blockchain technology has also been initially developed in the field of education, and its impact on education and teaching is increasingly reflected. At present, educational institutions, institutions concerned about education and future social development, as well as people of insight, have taken action to guide and utilize blockchain technology in a forward-looking manner by providing blockchain technology teaching and developing a teaching management platform based on blockchain technology, so as to meet the new education and teaching reform. In this paper, the essence, characteristics and development process of blockchain technology are discussed, and the application prospect of blockchain technology in higher education is given. At the same time, thoughts on the development of "blockchain+education" are also put forward, in order to provide reference for exploring the deep integration of modern information technology and education, and leading the innovation of education concept and education mode with informatization.
In traditional blockchain transactions,privacy protection is to encrypt users' sensitive information under the anonymity mechanism,and a trusted third party is involved to verify the transaction plaintext information.However,once the third party is attacked,the users' transaction information will be divulged.Furthermore,there is no truly trusted third party in a rational state.To better solve the privacy problems in blockchain transactions,and in view of issues of confidentiality verification of the tra-ders' transaction amount under the non-anonymous state,the PVC digital commitment protocol is adopted to hide the transaction amount in the commitment,and a publicly verifiable zero-knowledge proof scheme is established,so that verifiers are able to confidentially verify the legitimacy of the transaction without obtaining sensitive information from the traders.At the same time,the elliptic curve homomorphic encryption feature is used to encrypt the amount,thereby solving the problem of updating the traders' ciphertext ledger.The correctness of the proposed privacy protection scheme is verified and analyzed,and the results shows that compared with the existing schemes,the proposed scheme has the advantages of relatively low computational complexity,strong security and high efficiency.
Based on the cloud platform, the concept and importance of double-precision teaching in wisdom teaching is analyzed, and the basic framework of online and offline wisdom teaching based on blockchain technology is constructed in this paper. Based on the characteristics of blockchain such as security and decentralization, an accurate learning resource teaching model based on knowledge representation of learners and teaching resources is proposed. A double-precision collaborative strategy of accurate perception of wisdom teaching demand and accurate supply of resources is proposed. The framework of wisdom teaching is constructed, in which the accurate perception of wisdom teaching demand and the accurate supply of resources based on big data technology is analyzed. Based on blockchain technology, tracking the learning records of learners at each stage of learning is helpful. It effectively promotes the distribution and sharing of learning resources, efficiently bridges teaching resources and learning requirements, and provides more accurate, personalized learning support, and services for learners. It provides a secure data access strategy for both teachers and learners. The precise wisdom teaching framework based on blockchain technology has far-reaching practical value for the efficient development of online and offline teaching.
Abstract Blockchain is the systematic integration innovation of distributed accounting, consensus mechanisms, point-to-point transmission, encryption algorithms, intelligent contracts and other technologies, providing a solution for information security and social trust in the Information Age. The principles, characteristics and deep thinking of Blockchain technology can promote thinking innovation and solve the existing obstacles, including the weak effectiveness of education activities, the burnout of education subjects and the lack of mutual trust in the field of ideological and political education. This paper focuses on analyzing the expanded application of Blockchain theory in ideological and political education. The fit of blockchain technology application of educational thinking innovation and value orientation is 0.928; there is a linear relationship, and after applying blockchain technology for one year, the difference between the students’ thinking tendencies and the six aspects of their performance, except for the desire for knowledge, is statistically significant (P<0.5) when compared with the situation of the students one year ago. In addition, it is emphasized that we should build Learn Ledger, promote the participation degree of education subjects, establish a new interactive trust mechanism and intensify endogenous incentives to promote the deep transformation of ideological and political education, enhance the effectiveness of educational content, expand the participation in educational activities, and strengthen the multi-subject trust-relationship reconstruction of ideological and political education.
The development of fast-growing blockchain technology is encourages for the review and rethinking of many of the fundamental facts of our traditional education systems. As experience shows, the blockchain increases security and accessibility tremendously, such concepts as confidence, assessment and identity, currently doesn't satisfy users desires and there a reasonable necessity for the improvements. In this paper, we will consider providing of new methods for the database system in education, implementing the new blockchain technology in education since a new scheme can increase transparency and security in the education system.