This paper presents a blockchain-based distributed fellowship management system incorporating Attribute-Based Encryption (ABE) and Zero-Knowledge Proofs (ZKP) to verify candidate eligibility without exposing sensitive information. The system ensures that only qualified candidates who meet predefined criteria can receive fellowships, reducing the likelihood of fraudulent applications and administrative errors. Blockchain technology creates an immutable, decentralized ledger that provides transparency and accountability, while ABE ensures fine-grained access control over sensitive data. The integration of ZKP enhances privacy by allowing candidates to prove their eligibility without revealing personal details. This approach streamlines the fellowship verification process, lowers administrative burdens, and increases the dependability and fairness of the system. Our proposal delivers a secure, privacy-preserving solution for managing fellowships with improved efficiency and trust.
Data sharing is ubiquitous in the metaverse, which adopts blockchain as its foundation. Blockchain is employed because it enables data transparency, achieves tamper resistance, and supports smart contracts. However, securely sharing data based on blockchain necessitates further consideration. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising primitive to provide confidentiality and fine-grained access control. Nonetheless, authority accountability and key abuse are critical issues that practical applications must address. Few studies have considered CP-ABE key confidentiality and authority accountability simultaneously. To our knowledge, we are the first to fill this gap by integrating non-interactive zero-knowledge (NIZK) proofs into CP-ABE keys and outsourcing the verification process to a smart contract. To meet the decentralization requirement, we incorporate a decentralized CP-ABE scheme into the proposed data sharing system. Additionally, we provide an implementation based on smart contract to determine whether an access control policy is satisfied by a set of CP-ABE keys. We also introduce an open incentive mechanism to encourage honest participation in data sharing. Hence, the key abuse issue is resolved through the NIZK proof and the incentive mechanism. We provide a theoretical analysis and conduct comprehensive experiments to demonstrate the feasibility and efficiency of the data sharing system. Based on the proposed accountable approach, we further illustrate an application in GameFi, where players can play to earn or contribute to an accountable DAO, fostering a thriving metaverse ecosystem.
Current file sharing solutions have problems such as data loss, unauthorized access and have only one point of failure are insecure and unreliable. To overcome these challenges, this work proposes a Decentralized File Sharing System that optimizes the transfer of data securely and with high reliability. Others include decentralised storage by use of IPFS and Pinata, and safety of the file through AES encryption. Password de- cryption is ensured only by the recipient keeping the password, while MetaMask authentication is connected to the Ethereum network. To protect information integrity every file has a Content Identifier coded as CID. The benchmark assessments reveal that the execution time increases with lower variance for smaller file sizes and varies slightly with larger files. As for decentralized approaches they are protected from focused attacks, more reliable in terms of failures, and have much better scalability than the centralized ones providing a much better solution for file sharing.
The burgeoning size and complexity of Large Language Models (LLMs) introduce significant challenges in ensuring data integrity. The proliferation of "deep fakes" and manipulated information raises concerns about the vulnerability of LLMs to misinformation. Traditional LLM architectures often lack robust mechanisms for tracking the origin and history of training data. This opaqueness can leave LLMs susceptible to manipulation by malicious actors who inject biased or inaccurate data. This research proposes a novel approach integrating Blockchain Technology (BCT) within the LLM data supply chain. With its core principle of a distributed and immutable ledger, BCT offers a compelling solution to address this challenge. By storing the LLM's data supply chain on a blockchain, we establish a verifiable record of data provenance. This allows for tracing the origin of each data point used to train the LLM, fostering greater transparency and trust in the model's outputs. This decentralised approach minimises the risk of single points of failure and manipulation. Additionally, the immutability of blockchain records ensures that the data provenance remains tamper-proof, further enhancing the trustworthiness of the LLM. Our approach leverages three critical features of BCT to strengthen LLM security: 1) Transaction Anonymity: While data provenance is recorded on the blockchain, identities of data contributors can be anonymised, protecting their privacy while ensuring data integrity. 2) Decentralised Repository: Enhances the system's resilience against potential attacks by distributing the data provenance record across the blockchain network. 3) Block Validation: Rigorous consensus mechanisms ensure the validity of each data point added to the LLM's data supply chain - minimising the risk of incorporating inaccurate or manipulated data into the training process. Using the experimental approach, initial evaluations using simulated LLM training data on a blockchain platform demonstrate the feasibility and effectiveness of the proposed approach in enhancing data integrity. This approach has far-reaching implications for ensuring the trustworthiness of LLMs in various applications.
Covid19 pandemic has affected many sectors including education. All types of schools (public and private) have started to provide online education systems to their students to prevent spreading the disease. The online education system has brought many advantages besides stopping the spread of the disease. The students have more time since the lectures are not in class, it reduces the cost for the students since they physically do not go to school, and it provides flexibility in the lectures that students decide their schedule to attend the classes. However, there are some challenges in the online education system. The system needs to be available for the students when they take exams, view their exam results, and upload their exams for assessment. Since the lectures and exams are taken online, the data is very crucial. The data contains sensitive information such as exams, answers, scores, name, date of birth, address, phone number, government identification number, etc. A traditional online education system has a centralized infrastructure governed and managed by a single entity. This results in the system having single-point-of-failure attacks. This paper proposes an online examination system based on a smart contract and a blockchain. The blockchain eliminates single-point-of-failure attacks. The teachers write questions and store them in the blockchain. Only authorized students retrieve the exams from the blockchain by using smart contracts. The students submit their completed exams at predefined times. Then, the teachers evaluate the students’ exams and put the results into the blockchain. Their exam scores are protected from any unauthorized entities by encryption. Students can freely see and view their scores at any time. Then, the students can show their results to any other third parties (once they apply for an internship or job) that they have completed the courses successfully. The system also uses a decentralized storage (off-chain) system to eliminate scalability problems. Off-chain storage (InterPlanetary File System) stores students’ exams, answers, and exam results while the corresponding content identifiers of the files are stored in the blockchain. The proposed system is resilient to malicious teachers who can manipulate the exam results. In addition, the proposed system also provides a method for dishonest students who can complain about their exam results. In other words, the proposed system solves any conflicts between entities.
Ertem Nusret Tas, István András Seres, Yinuo Zhang, Márk Melczer · 7 authors
We introduce a blockchain Fair Data Exchange (FDE) protocol, enabling a storage server to transfer a data file to a client atomically: the client receives the file if and only if the server receives an agreed-upon payment. We put forth a new definition for a cryptographic scheme that we name verifiable encryption under committed key (VECK), and we propose two instantiations for this scheme. Our protocol relies on a blockchain to enforce the atomicity of the exchange and uses VECK to ensure that the client receives the correct data (matching an agreed-upon commitment) before releasing the payment for the decrypting key. Our protocol is trust-minimized and requires only constant-sized on-chain communication, concretely 3 signatures, 1 verification key, and 1 secret key, with most of the data stored and communicated off-chain. It also supports exchanging only a subset of the data, can amortize the server's work across multiple clients, and offers a general framework to design alternative FDE protocols using different commitment schemes. A prominent application of our protocol is the Danksharding data availability scheme on Ethereum, which commits to data via KZG polynomial commitments. We also provide an open-source implementation for our protocol with both instantiations for VECK, demonstrating our protocol's efficiency and practicality on Ethereum.
Michael L. Rosenberg, Tushar Mopuri, Hossein Hafezi, Ian Miers · 5 authors
Zero-knowledge Succinct Non-interactive ARguments of Knowledge (zkSNARKs) allow a prover to convince a verifier of the correct execution of a large computation in private and easily-verifiable manner.These properties make zkSNARKs a powerful tool for adding accountability, scalability, and privacy to numerous systems such as blockchains and verifiable key directories.Unfortunately, existing zkSNARKs are unable to scale to large computations due to time and space complexity requirements for the prover algorithm.As a result, they cannot handle real-world instances of the aforementioned applications.In this work, we introduce Hekaton, a zkSNARK that overcomes these barriers and can efficiently handle arbitrarily large computations.We construct Hekaton via a new "distribute-and-aggregate" framework that breaks up large computations into small chunks, proves these chunks in parallel in a distributed system, and then aggregates the resulting chunk proofs into a single succinct proof.Underlying this framework is a new technique for efficiently handling data that is shared between chunks that we believe could be of independent interest.We implement a distributed prover for Hekaton, and evaluate its performance on a compute cluster.Our experiments show that Hekaton achieves strong horizontal scalability (proving time decreases linearly as we increase the number of nodes in the cluster), and is able to prove large computations quickly: it can prove computations of size 2 35 gates in under an hour, which is much faster than prior work.Finally, we also apply Hekaton to two applications of realworld interest: proofs of batched insertion for a verifiable key directory and proving correctness of RAM computations.In both cases, Hekaton is able to scale to handle realistic workloads with better efficiency than prior work.
Interactive theorem provers (ITPs), such as Lean and Coq, can express formal proofs for a large category of theorems, from abstract math to software correctness. Consider Alice who has a Lean proof for some public statement T. Alice wants to convince the world that she has such a proof, without revealing the actual proof. Perhaps the proof shows that a secret program is correct or safe, but the proof itself might leak information about the program's source code. A natural way for Alice to proceed is to construct a succinct, zero-knowledge, non-interactive argument of knowledge (zkSNARK) to prove that she has a Lean proof for the statement T.
In the realm of healthcare analytics, preserving the privacy of sensitive data while enabling valuable insights poses a significant challenge, particularly given the increasing prevalence of data breaches and the sensitivity of personal health information. This paper presents a secure framework that addresses these concerns by integrating privacy-preserving parameters, zero-knowledge proofs (zk-SNARKs), blockchain technology, and a multi-tenant cloud environment. Through advanced cryptographic techniques, specifically zk-SNARKs, the framework ensures that healthcare records remain protected during analytics computations, without exposing raw data. The privacy-preserving analytics engine utilizes anonymized healthcare records and generates zk-SNARKs to validate computations. These proofs, integrated into a blockchain network, create a tamper-proof, transparent ledger that ensures secure healthcare transactions. This approach is critical in scenarios such as telemedicine, where secure data sharing and computation are paramount. By demonstrating its application in a telemedicine app, the framework highlights its practical significance in balancing data utility and privacy in healthcare analytics, providing a scalable and secure solution to a pressing problem.
Abstract In light of the rapid development of edge computing and the increase in the number of connected devices, this paper addresses the pressing issue of ensuring data integrity. The main focus is on the use of blockchain technology, which offers unique opportunities to solve this problem. This paper provides a brief overview of the existing methods and a new method for ensuring integrity based on blockchain technology. It is proposed to use the Hot Stuff consensus algorithm in the case of multiple active nodes, which ensures fast operation and scalability of the system. Particular attention is paid to the use of a secondary blockchain based on Ethereum to provide additional security and create checkpoints in large blockchain networks. This makes it possible to simplify the work of edge servers and ensure data integrity verification upon the user’s request using smart contracts. The proposed new approaches to ensure data integrity and use blockchain technology can be applied not only in the field of edge computing but also in various variations of the Internet of Things.
Blockchain technology has emerged as a transformative solution in the realm of cybersecurity, addressing critical challenges of data integrity and transparency.The ever-increasing sophistication of cyber threats necessitates robust mechanisms to secure sensitive data and ensure accountability in digital systems.Traditional methods, while effective to some extent, often fail to prevent data tampering and lack comprehensive traceability, leaving organizations vulnerable to breaches.Blockchain's decentralized, immutable ledger offers an innovative approach to overcoming these limitations by ensuring secure data integrity and creating transparent audit trails.This paper explores the application of blockchain technology in enhancing cybersecurity frameworks, emphasizing its role in preventing unauthorized data modification and enabling traceability.By employing cryptographic hashing and consensus mechanisms, blockchain ensures data authenticity while eliminating single points of failure.Its capabilities are particularly relevant for industries with stringent regulatory requirements, such as finance, healthcare, and supply chain management, where data accuracy and accountability are paramount.Moreover, we investigate advanced blockchain models, including private and consortium blockchains, to balance scalability, efficiency, and confidentiality.Integration with complementary technologies like smart contracts and artificial intelligence further extends its utility, enabling automated security protocols and anomaly detection.Despite its promise, blockchain adoption faces challenges, including high energy consumption, scalability issues, and the need for standardization.This study provides a comprehensive analysis of blockchain's potential and limitations in cybersecurity, proposing future directions to optimize its effectiveness.By bridging gaps in technology and implementation, blockchain holds the potential to redefine secure digital interactions, ensuring trust and resilience in increasingly interconnected systems.
Jovener M. Pajalla, Sean Daniel M. Lu, Aleera P. Ojenar, Remedios G. Ado · 5 authors
University events are essential avenues for faculties and students to promote community building and engagement, social interactions, skills development and the overall enhancement of learning for the welfare of the whole university. However, the majority of the universities do not implement a secure yet transparent and organized access system for such activities, leading to denied access for the learners, undesirable user experiences, and the general mismanagement of events. With this, the proponents' aim is to develop a blockchain-powered ticketing and access system to facilitate university events for PUP. A smart contract implementing ERC-721 was developed to mint Non-Fungible Tokens (NFTs) to reserve slots/seats for certain events, while a user interface was built to select the listed events on a website. The researchers made various tests for smart contracts and mock transactions to evaluate the functionality of the proposed system. In conclusion, PUP UniChain offers potential solutions to handle event access and management for PUP.
Abstract With the development of Web3 technologies, the third generation of the Internet has become one of the most promising areas. It involves the use of decentralized, transparent, and user-oriented applications. However, many Web3 projects do not pay sufficient attention to security, which can lead to serious consequences. Even a small error in the code can make the system vulnerable, opening access to attackers. As a result, the industry faces frequent security breaches that threaten users and undermine trust in new technologies. One of the main problems with Web3 is private key management. This is a critical security aspect that is directly related to the protection of digital assets and users' personal information. The risk of losing or theft of a private key can lead to irreparable consequences, since in the case of loss there is no way to restore or reset the key. Various ways of storing the private key of a crypto wallet to ensure security are discussed. For example, the key can be split into parts and stored encrypted on hardware media, or the entire encrypted key can be stored on secure media. Quantitative data are calculated using Shamir’s scheme.
The scaled Web 3.0 digital economy, represented by decentralized finance (DeFi), has sparked increasing interest in the past few years, which usually relies on blockchain for token transfer and diverse transaction logic. However, illegal behaviors, such as financial fraud, hacker attacks, and money laundering, are rampant in the blockchain ecosystem and seriously threaten its integrity and security. In this paper, we propose a novel double graph-based Ethereum account de-anonymization inference method, dubbed DBG4ETH, which aims to capture the behavioral patterns of accounts comprehensively and has more robust analytical and judgment capabilities for current complex and continuously generated transaction behaviors. Specifically, we first construct a global static graph to build complex interactions between the various account nodes for all transaction data. Then, we also construct a local dynamic graph to learn about the gradual evolution of transactions over different periods. Different graphs focus on information from different perspectives, and features of global and local, static and dynamic transaction graphs are available through DBG4ETH. In addition, we propose an adaptive confidence calibration method to predict the results by feeding the calibrated weighted prediction values into the classifier. Experimental results show that DBG4ETH achieves state-of-the-art results in the account identification task, improving the F1-score by at least 3.75% and up to 40.52% compared to processing each graph type individually and outperforming similar account identity inference methods by 5.23 % to 12.91 %.
Web 3.0 technologies such as blockchain, cryptocurrency, and Non-Fungible Tokens (NFTs) are progressively making waves. Despite their adoption in various sectors, their application in the education sector, particularly in Higher Educational Institutions (HEIs), is largely unexplored. Our research proposes the development of a secure NFT platform using blockchain technology, tailored for HEIs. The primary aim of this research is to authenticate rewards, and certificates, and digitalize badges using NFTs, minimizing potential fraud and enhancing data security. Reward NFTs can enhance students' and teachers' career recognition and credit. EduNFT is a ‘first of its kind’ in the Sultanate of Oman in creating a Web 3.0 technology-enabled campus where students are rewarded with digital assets (NFTs) for their achievements by the teachers or the institution over an NFT platform in a secured environment. It runs on the Polygon blockchain which is a "layer two" or "sidechain" scaling solution that runs alongside the Ethereum blockchain - allowing speedy transactions with low fees. The research methodology incorporates an authentication process that requires users to log in via their crypto wallets which enhances security and maintains user privacy. Instead of traditional physical rewards, this digital approach allows achievements to be stored perpetually in the blockchain, reducing risks of loss or damage. The proposed research empowers an impressive expansion of NFT utilization in higher education, contributing to the ongoing growth of the NFT space. The outcome, a pioneering NFT platform powered by Web 3.0 technology, stands to revolutionize the higher education sector, not only in Oman but potentially worldwide. In addition, the research serves as a crucial step toward integrating contemporary technologies into educational systems and furthering their evolution.
This work presents the DGChain (Data-Git- for Blockchain) project. This Python package allows version control of data in blockchain and IPFS based on a DAO (decentralized autonomous organization) for managing data in the development cycles of reproducible computational scientific research. Analyzes the benefits of using this Blockchain-Based Decentralized Architecture to mediate collaborative interactions between developers compared to existing solutions. Presents a use case in developing a medical research project and typical IRIS example to offer the traceability of changes and provenance of metadata, data, and code in Data / Software Version Control systems through management of intrinsic hash-based persistent, immutable CIDs (Content Identifier) recorded in Merkle trees in the development cycle of its main products, publication, software source code, and Data to guarantee reproducibility and trustworthiness in computational scientific research using DGChain.
The increasing popularity of blockchain and cryptocurrencies has led to a considerable proliferation of the cryp-tocurrency market in recent years, pulling more investors into the trillion-dollar industry. The increasing number of users has led to increasing privacy concerns. While the network's ability to facilitate financial inclusion is enhanced by the blockchain's openness and public nature, it also exposes users' transaction histories, raising the possibility of privacy violations and other concerns, such as user profiling. To address these privacy challenges, various techniques emerged, categorized as joint transactions and mixing services. While promising, these methods have limitations, such as potential information leakage and the need for trust in centralized entities. To overcome these shortcomings, we propose a novel system that combines joint transactions and mixing services, incorporating Zero-Knowledge Proofs (ZKPs) for enhanced privacy guarantees. Our proof of concept on the Ethereum blockchain demonstrates improved privacy while providing the basic requirements. The evaluation includes performance metrics and security analysis, focusing on key considerations—unlinkability, verifiability, and double-spending. Our method achieves unlinkability by obfuscating transaction paths through multiple stages (ZKPs, CoinJoin, CoinSwap), ensures verifiability through signatures and commitment exchanges, and prevents double-spending through nonce utilization, all while maintaining a feasible execution time.
BlockVerify is a decentralized platform created to offer a safe and impenetrable way to use blockchain technology for document verification. BlockVerify guarantees the authenticity of documents by utilizing the immutability and transparency of the Ethereum blockchain. This makes it the perfect solution for individuals and organizations that need strong document verification. Users of BlockVerify can upload metadata for decentralized storage, including IPFS hashes, along with document hashes. The platform makes sure that the only people who can add and edit document records are authorized exporters who are managed and added by the contract owner. Document verification, ownership transfer, exporter management, and hash storage are important aspects. The project develops smart contracts using Solidity and Ethereum (Sepolia testnet), and it has an easy-to-use online interface using technologies like HTML, CSS and JavaScript to promote communication and MetaMask for secure wallet interactions. With future ambitions to expand to the mainnet and support new document kinds, BlockVerify intends to combat document fraud by offering a dependable way to check the legitimacy of documents.
This paper explores the integration of blockchain technology to enhance data integrity in cloud computing environments. As data breaches and unauthorized access continue to challenge traditional cloud security measures, blockchain offers a decentralized solution that ensures tamper-proof record-keeping and accountability. By leveraging cryptographic techniques and distributed ledger technology, the proposed framework enables secure data storage, sharing, and validation processes. This study highlights key use cases, potential challenges, and the overall impact of blockchain on improving trust and reliability in cloud computing, paving the way for more robust data integrity solutions in various applications across industries.
Avraam Tepelidis, Eirini E. Mitsopoulou, Athanasios T. Patenidis, Kristina Livitckaia · 6 authors
Blockchain technology advancements have made it feasible to build secure, decentralized networks with numerous use cases in various industries, including banking, education, government, and health. In higher education, there is a significant need for certification and credential verification through digital means, as fake certificates are common in the labor market. The BlockAdemiC system presented in this article falls into solutions for such issues. BlockAdemiC is a blockchain-based educational platform that makes use of cutting-edge features in blockchain technology to ensure the required degree of trust both at the individual user and institutional level. Specifically, BlockAdemiC represents a digital distributed security system for the certification and verification of educational activities, degrees, and skills in higher education and lifelong learning, producing an immutable educational passport. Information distributed using blockchain enhances trust in the exchange of information between institutions, agencies, companies, and alumni and introduces a trustworthy mechanism for content verification and authentication. For self-sovereign identity and identification management, the system utilizes distributed ledger technology via Hyperledger frameworks and offers users authority over their identities and credentials, removing the need for the involvement of central authorities to validate and verify user identities. Smart contracts are additionally supported, which provide the connection for storing student activities that take place on educational platforms on the EOSIO blockchain. The BlockAdemiC was evaluated via a technological feasibility study focusing on the system’s performance. The initial findings show that the system can efficiently process a high load of queries in parallel similar to the real-world situation and can be further considered for large-scale deployment and use.
Zain Ul Islam Adil, Majid Iqbal Khan, Kahkishan Sanam, Saif Ur Rehman Malik · 6 authors
ABSTRACT Counterfeit medical devices pose a threat to patient safety, necessitating a secure device authentication system for medical applications. Resource‐constrained sensory nodes are vulnerable to hacking, prompting the need for robust security measures. Token‐based authentication schemes, such as one‐time passwords (OTPs), smart cards, key fobs, and mobile authentication apps, along with certificate‐based authentication methods, such as client and code‐signing, employ cryptographic frameworks like elliptical curve cryptography (ECC) and physical unclonable functions (PUF). However, these methods face challenges, including block sequence issues and susceptibility to side‐channel attacks. To address these issues, we propose a framework for mutual authentication using private Ethereum. This framework integrates private Ethereum and cryptographic techniques for encrypting and decrypting data using mathematical algorithms to overcome block sequence issues and side‐channel attacks. Similarly, fog nodes are utilised to enhance local computing, storage, and networking capabilities for sensors. The framework is evaluated using metrics such as communication costs, execution costs, and computation costs based on Ethereum gas consumption. The performance of the LightAuth framework is compared with that of the Smart Contracts Against Counterfeit IoMT (SCACIoMT) framework, designed for Internet of Medical Things (IoMT) devices. The effectiveness of LightAuth is verified through formal security analysis using BAN logic.