Immutability is widely recognized as one of the blockchain’s key security attributes. However, in recent years, incidents involving the use of blockchain for disseminating illegal or malicious information have raised concerns over its strict immutability. To address these issues, redactable blockchains are proposed as a novel solution, permitting authorized content redactions without compromising the structural integrity of the blockchain. Unfortunately, current solutions are unable to restrict the abuse of redaction privilege, except for relying on a trusted authority or committee, which contradicts the trustlessness principle of blockchain. In this paper, we propose a controlled redactable blockchain protocol that allows for a limited number of redactions and supports a transparent setup. The cryptographic tools enabling this functionality are our proposed t-times chameleon hash (t-CH) and signature (t-CS) schemes, where generating more than t collisions will expose the trapdoor. We present security models, discrete logarithm-based instantiations, and formal security proofs for both t-CH and t-CS. Subsequently, we present the construction of our redaction protocol in both permissioned and permissionless settings. Finally, we experimentally demonstrate the effectiveness of the proposed protocol in practice.
The classification of the smart contract can effectively reduce the search space and improve retrieval efficiency. The existing classification methods are based on natural language processing technologies. Because the processing of source code by these technologies lacks extraction and processing in the software engineering field, there is still a lot of room for improvement in their methods of feature extraction. Therefore, this paper proposes a multi-feature fusion method for smart contract classification (MFF-SC) based on the code processing technology. From the source code perspective, source code processing method and attention mechanism are used to extract local code features. Structure-based traversal method are used to extract global code features from abstract syntax tree. Local and global code features introduce attention mechanism to generate code semantic features. From the perspective of account transaction, the feature of account transaction is extracted by using TransR. Next, the code semantic features and account transaction features generate smart contract semantic features by an attention mechanism. Finally, the smart contract semantic features are fed into a stacked denoising autoencoder and a softmax classifier for classification. Experimental results on a real dataset show that MFF-SC achieves an accuracy rate of 83.9%, compared with other baselines and variants.
Web3, the next generation of the Internet, represents a decentralized and democratized web. Although it has garnered significant public interest and found numerous real-world applications, there is a limited understanding of people's perceptions and experiences with Web3. In this study, we conducted an empirical study to investigate the categories of Web3 application and their popularity, as well as the potential challenges and opportunities within this emerging landscape. Our research was carried out in two phases. In the first phase, we analyzed 200 popular Web3 projects associated with 10 leading Web3 venture capital firms. In the second phase, we collected and examined code-related data from GitHub and market-related data from blockchain browsers (e.g., Etherscan) for these projects. Our analysis revealed that the Web3 ecosystem can be categorized into two groups, i.e., Web3 infrastructure and Web3 applications, with each consisting of several subcategories or subdomains. We also gained insights into the popularity of these Web3 projects at both the code and market levels and pointed out the challenges in the Web3 ecosystem at the system, developer, and user levels, as well as the opportunities it presents. Our findings contribute to a better understanding of Web3 for researchers and developers, promoting further exploration and advancement in this innovative field.
Wensheng Gan, Zhenqiang Ye, Shicheng Wan, Philip S. Yu
With the rapid growth of the Internet, human daily life has become deeply bound to the Internet. To take advantage of massive amounts of data and information on the internet, the Web architecture is continuously being reinvented and upgraded. From the static informative characteristics of Web 1.0 to the dynamic interactive features of Web 2.0, scholars and engineers have worked hard to make the internet world more open, inclusive, and equal. Indeed, the next generation of Web evolution (i.e., Web 3.0) is already coming and shaping our lives. Web 3.0 is a decentralized Web architecture that is more intelligent and safer than before. The risks and ruin posed by monopolists or criminals will be greatly reduced by a complete reconstruction of the Internet and IT infrastructure. In a word, Web 3.0 is capable of addressing web data ownership according to distributed technology. It will optimize the internet world from the perspectives of economy, culture, and technology. Then it promotes novel content production methods, organizational structures, and economic forms. However, Web 3.0 is not mature and is now being disputed. Herein, this paper presents a comprehensive survey of Web 3.0, with a focus on current technologies, challenges, opportunities, and outlook. This article first introduces a brief overview of the history of World Wide Web as well as several differences among Web 1.0, Web 2.0, Web 3.0, and Web3. Then, some technical implementations of Web 3.0 are illustrated in detail. We discuss the revolution and benefits that Web 3.0 brings. Finally, we explore several challenges and issues in this promising area.
Yusra Mohammed AlRoshdi, Mohammed Al-Badawi, Abdullah Al-Hamdani, Mohamed Sarrab
Decentralized Web (Web3) and Finance (DeFi) have become the main discussion topic in research and industry fields.Cryptocurrencies, as an essential part of DeFi, enjoyed the interest of many stakeholders such as companies, professionals, researchers, and even common citizens eager to benefit from the proposed ecosystems.Although previous research studies focused on establishing price prediction systems using Sentiment Analysis (SA) techniques, the main focus of these studies was the performance of the predictive system rather than the accuracy and efficiency of the used models.In our work, we address two research questions; the predictability of cryptocurrency price based on past social and technical information, and the effect of social features on cryptocurrency price fluctuations using an SA and a Time Series approach.A combination of selected social and technical features was processed and reframed as a prediction problem, then studied to assess the ability of our model to predict the desired price.We noted that there is both an explicit correlation for some considered features and implicit for others, also social features including overall positive and neutral sentiment, and community engagement improved the performance of our model.
This paper presents an architectural overview and detailed design of the Krypton network, the first decentralized search engine built on Web3 principles. Krypton leverages blockchain technology, token-driven incentives, and privacy-focused features to revolutionize internet search. The proposed solution incorporates distributed storage, decentralized web crawling and indexing, a consensus mechanism, open-source search algorithms, and a privacy-focused search experience. Krypton introduces the novel concept of Proof of Learning, a machine learning protocol embedded in the search engine to facilitate the discovery of decentralized platforms and enable direct peer-to-peer networking. The system also employs decentralized cloud technologies (validators in the PoS blockchain) to promote enhanced decentralization and encryption, paving the way for a more secure and equitable internet.
The search for smart contract source codes has drawn research attention to fulfill developers’ and researchers’ needs. Yet, the existing studies are not mature enough to address smart contracts’ technical properties and functionalities. This paper proposes a system to improve the naive search for smart contract codes; for example, Etherscan has one keyword search feature without regard to the contract structure. We consider clustering smart contracts based on developers’ preferences, which increases the probability that the resulting source codes match developers’ needs. Our experimental results show a significant improvement in the complexity of the retrieved source codes of smart contracts compared with the baseline scenario using blockchain search engines (e.g., Etherscan). Our solution reduces the number of retrieved smart contract codes the developer has to check if the codes match her/his needs by 94%, 88%, 82%, or 98%, depending on the user’s search preferences.
Abstract Event studies in general rely on having a high-quality curated database of events. In this paper we introduce CryptoGDelt2022, a news event dataset extracted from the Global Database of Events, Language and Tone (GDELT) containing more than 243 thousands cryptocurrency related news events between the 31st of March 2021 and 30th of April 2022. The dataset is enriched with supervised machine learning scores for Relevance, Sentiment and Strength. Supervised Relevance Score measures how related to Cryptocurrency the topic is using news web scrapped from Yahoo in general and from the Cryptocurrency part of the site, after a comparison of approaches; Latent Dirichlet Allocation (LDA), BERT and Naive Bayes, Naive Bayes was chosen and the hyper-parameter tuned model reached accuracy: 97.84 % in the train set and 91.70% in the test set. Supervised Sentiment Score measures the negative, neutral or positive tone of the news, after hyper-parameter tuning, the retrained FinBERT model achieved accuracy of 92.63% in the train set and 86.11% in the test set. Supervised Strength Score measures how strong the news by using the abnormal return using Fama French 3-factor model as target output variable, after hyper-parameter tuning, the trained Naive Bayes model reached accuracy of 63.34%. The work concludes that GDELT is more reliable source of event when compared to news selected from cryptocurrency specialized websites as it presents a more balanced positive and negative number of news. All data sets and Python Jupyter Notebooks are available in the project's GitHub.
Web3, one of the novel paradigms which may drive the evolution of the future Web, is offering an invaluable volume of data stored in the supporting blockchains. Researchers from different fields such as network science, computational social science and data mining, might benefit from these large collections of temporal and heterogeneous data capturing different kinds of interaction among people and between people and the platforms. In this study we focus on a specific issue related to these modern techno-social systems, i.e. the understanding of the rules driving their growth. To reach this goal, we performed an analysis based on graph evolution rules - GERs - on different networks gathered from Web3 platforms such as Steemit or OpenSea. Graph evolution rules mining is a frequency-based method for evaluating network evolution which does not require any prior growth process for disentangling how networks evolve. By comparing the evolution rules of social network platforms and asset trading services through GER profiles, we observe that some evolution rules are common to all Web3 platforms, regardless of the system specificity. On the other hand, in specific cases, the frequency of graph evolution rules is influenced by the nature of the platform: whereas social and token-transfer networks are characterized by rules which increase network transitivity and reciprocity, NFT trading networks, especially those specialized in a specific type of digital asset, are driven by rules which form trading chains. These findings suggest that the GER approach and the GER profiles are a good starting point to get insights into the evolutionary behavior of a network and to define a classification of graph evolution rules.
Md. Amir Hossain Fahad, Redoyan Chowdhury, Hasan-Al– Shabbir
Web development has greatly advanced from basic static web pages to dynamic, datadriven applications utilizing modern technology. Specifically, this article looks at the past, present, and future of web development, focusing on the importance of artificial intelligence (AI), progressive web apps (PWAs), security measures, and performance improvement. The adoption of contemporary frontend and backend technologies has improved user experience, scalability, and security, while nascent trends like Web3, blockchain integration, and decentralized apps (DApps) are poised to transform the digital environment. Even with these advances, there are still problems, such as cybersecurity risks, accessibility issues, and the need to keep improving online performance. This evaluation shows how important it is to welcome new technologies while also addressing important problems in order to create a safe, effective, and welcoming digital world. Future research must concentrate on enhancing cybersecurity frameworks, refining AI-driven web development, and investigating decentralized computing paradigms. Utilizing advanced technology, web developers may design more intelligent, responsive, and user-centric online apps that satisfy the increasing expectations of the digital age.
This paper examines the effects of inherent risks in the emerging technology of non-fungible tokens and proposes an actionable set of solutions for stakeholders in this ecosystem and observers. Web3 and NFTs are a fast-growing 300 billion dollar economy with some clear, highly publicized harms that came to light recently. We set out to explore the risks to understand their nature and scope, and if we could find ways to mitigate them. In due course of investigation, we recap the background of the evolution of the web from a client-server model to the rise of Web2.0 tech giants in the early 2000s. We contrast how the Web3 movement is trying to re-establish the independent style of the early web. In our research we discover a primary set of risks and harms relevant to the ecosystem, and classify them into a simple taxonomy while addressing their mitigations with solutions. We arrive at a set of solutions that are a combination of processes to be adopted, and technological changes or improvements to be incorporated into the ecosystem, to implement risk mitigations. By linking mitigations to individual risks, we are confident our recommendations will improve the security maturity of the growing Web3 ecosystem. We are not endorsing, or recommending specifically any particular product or service in our solution set. Nor are we compensated or influenced in any way by these companies to list these products in our research. The evaluations of products in our research have to simply be viewed as suggested improvements.
Understanding the semantic of a collection of texts is a challenging task. Topic models are probabilistic models that aims at extracting "topics" from a corpus of documents. This task is particularly difficult when the corpus is composed of short texts, such as posts on social networks. Following several previous research papers, we explore in this paper a set of collected tweets about bitcoin. In this work, we train three topic models and evaluate their output with several scores. We also propose a concrete application of the extracted topics.
A group of researchers, builders and activists came together to discuss platform cooperativism and the intersection with the web3 movement. We touched on some of the key takeaways from the history of cooperatives that can be applied to developing new internet platforms and protocols, as well as the challenges platform cooperatives face scaling alternative models of ownership and control. Consequently, we investigated how developers and emerging internet companies might learn from the shared history of cooperatives and how, in practice, they can construct systems that respect cooperative ideals.
As online sources are becoming more prevalent in journalism and scientific literature, the ephemeral nature of the World Wide Web is becoming an increasingly serious issue for their verifiability, replicability, and reproducibility. The architecture of Webchain, a new system enabling source and reference verifiability on the Web, is combining distributed ledger technologies with secure timestamping to ensure the history of creation, ownership, and referential integrity of online resources. We present the architecture and system extensions, conduct a security analysis, and evaluate the Webchain system based on a comprehensive prototype implementation. The results confirm the feasibility and robustness of our approach.
Smart Contracts are computer programs which implement and execute transactions and manage business logic on a decentralized public ledger. Smart Contracts can be written in different programming languages and for different Blockchains. Currently the most used language for Smart Contracts is Solidity and the most used platform is the Ethereum Blockchain. Assessing the quality of Smart Contract programs is an important task required to professional programmers, especially when a programming language has so powerful economic implications. It is therefore crucial to provide professional programmers with tools for the evaluation of Smart Contracts. In software engineering, software metrics has been defined and used to measure software quality and, more in general, to qualify software under the principle “You Can't Manage What You Don't Measure”. For the Solidity programming language there are only a few Standalone Applications to analyse the Smart Contract metrics. The aim of this paper is first to build a tool for the practical computation of a specific set of Solidity source code metrics, so that the set will be extensible in the future according also to Solidity compiler evolution, second to fully enable a web-based usage of the tool to access the metrics of the Solidity programming language. The tool, PASO, differently from the existing application, is able to give software metrics values for Smart Contracts written in Solidity programming language just using a web browser.
Sai Medury, Anthony Skjellum, Richard R. Brooks, Lu Yu
X.509 certificates underpin the security of the Internet economy, notably secure web servers, and they need to be revoked promptly and reliably once they are compromised. The original revocation method specified in the X.509 standard, to distribute certificate revocation lists (CRLs), is both old and untrustworthy. CRLs are susceptible to attacks such as Man-in-the-Middle and Denial of Service. The newer Online Certificate Status Protocol (OCSP) and OCSP-stapling approaches have well-known drawbacks as well. The primary contribution of this paper is Secure Revocation as a Peer Service (SCRaaPS). SCRaaPS is an alternative, reliable way to support X.509 certificate revocation via the Scrybe secure provenance system. The blockchain support of Scrybe enables the creation of a durable, reliable revocation service that can withstand Denial-of-Service attacks and ensures non-repudiation of certificates revoked. We provide cross-CA-revocation information and address the additional problem of intermediate-certificate revocation with the knock-on effects on certificates derived thereof. A Cuckoo filter provides quick, communication-free testing by servers and browsers against our current revocation list (with no false negatives). A further contribution of this work is that the revocation service can fit in as a drop-in replacement for OCSP-stapling with superior performance and coverage both for servers and browsers. Potential revocation indicated by our Cuckoo filter is backed up by rigorous service query to eliminate false positives. Cuckoo filter parameters are also stored in our blockchain to provide open access to this algorithmic option for detection. We describe the advantages of using a blockchain-based system and, in particular, the approach to distributed ledger technology and lightweight mining enabled by Scrybe, which was designed with secure provenance in mind.
Muhammad Syafiq Mohd Pozi, Gopinath Muruti, Asmidar Abu Bakar, Adam Jatowt · 5 authors
Authorship contribution is often taken for granted. Internally, the contribution rate is usually known among all the authors of a given paper. However, this rate is hard to be verified by external parties, as the measurement of the authors' contribution is still not common and the way to measure it is unclear. In this paper, we propose a new blockchain based framework to assess the contribution of all authors of any scientific paper. Our framework can be implemented by anyone who is directly or indirectly involved in the publication of the paper, such as a principal researcher, grant funder, research assistant or anyone from relevant external bodies.