Bitcoin is considered an anonymous transaction technology. Transactions are not directly linked to real names or physical identities of users. However, each transaction is recorded in the blockchain, which is publicly available and allows anyone to perform detailed analysis. This bachelor thesis deals with the issue of attributing cryptocurrency wallets to specific nodes in the Bitcoin peer-to-peer network. The aim of the thesis is to examine the process of transaction propagation between nodes, identify factors influencing their order and propagation speed, and propose methods that will allow estimating the original node responsible for creating or first sending the transaction. The theoretical part describes the basic mechanisms of transaction propagation in the network and analyzes anonymization and deanonymization techniques. The practical part focuses on the design and implementation of heuristics combining propagation time profiles with topological information about the network. For this purpose, a modular platform was developed in the .NET environment, which enables the analysis of data from the P2P network. The contribution of this work is the combination of theoretical principles of transaction propagation with the practical use of data from a real network and the extension of existing methods for analyzing anonymity in the Bitcoin cryptocurrency environment.
Transaction propagation delay limits the block interval and is one of the main bottlenecks in improving Bitcoin throughput. However, transaction relay in Bitcoin is entirely voluntary, which results in low bandwidth and high transaction propagation delay. Improving relay motivation by introducing incentives can effectively reduce delay, but it still faces challenges such as Sybil attacks during reward allocation, leakage of network layer privacy, and high on-chain/off-chain overhead. Therefore, this paper proposes Txtail, a practical transaction relay incentive scheme for Bitcoin, based on continuously attaching relay evidence representing the relays’ identity and contribution during transaction propagation. We employ a free pricing mechanism based on the game between relays to allocate rewards fairly. We design an order-insensitive relay evidence structure based on aggregate signatures and public key mapping, which reduces off-chain data overhead while alleviating the leakage of relay paths by obfuscating the relay order. We construct a verifiable lottery mechanism based on Merkle tree commitments to reduce the data that needs to be uploaded to the chain. Both theoretical and experimental results show that Txtail reduces the per-hop off-chain overhead and the overall on-chain overhead by 96.6% and 79.8%, respectively, compared with state-of-the-art baselines, while remaining practical for deployment.
This paper presents a Blueprint theoretical-practical method for covert control over a decentralized network like Bitcoin by manipulating official distribution channels and modifying the client software. The attack, termed the "Great Tribulation Attack," transforms legitimate users into functional zombie nodes that validate blocks under hidden rules or preprogrammed transactions without their knowledge. This technique does not rely on the 51% hashing power but on client deception.
With the increased usage of Bitcoin and othercryptocurrencies, there is a need to address issues related tofraud detection in cryptocurrency systems. Such issuesinclude double-spending, money laundering, and accounthacking, among others, that Bitcoin needs to guard against.However, since Bitcoin is decentralised and transactions arenot reversible, the use of central-system approaches cannotbe applied; thus, an alternative approach must be adopted.The presented project offers a viable method of usingmachine learning for Bitcoin fraud detection. The frauddetection method is real-time, using ensemble stacking,which entails combining multiple machine learning modelsto enhance prediction capabilities. Algorithms to be usedinclude Random Forest, Gradient Boosting (XGBoost,LightGBM), Support Vector Machine (SVM), LogisticRegression, and Isolation Forest. In other words, multiplealgorithms will be used to examine Bitcoin transaction data,such as amounts transacted, transaction frequency, andtransaction patterns. Ensemble stacking allows the use of thestrengths of multiple algorithms, while the real-time functionenhances the applicability of the approach. Scalability isanother critical consideration, especially considering thenumber of Bitcoin users. This is why the use of a Flaskapplication server will be necessary for user datasubmissions, visualisation, and sending fraud notifications.Evaluation will be based on accuracy, precision, recall, andF1-score.Conclusion – The proposed solution appears quiteplausible as the fraud detection through machine learning isefficient, while scalability is one of the main features of theapproach.
Federated learning across IoT devices must simultaneously protect each device’s update from disclosure, prevent malicious participants from biasing the global model, and hide which devices are participating from outside observers. Existing systems typically address only a subset of these goals: secure aggregation hides individual updates but cannot validate them, plaintext-based robust filtering requires the server to see updates, and most cryptographic pipelines ignore timing privacy. This paper presents TriSAFE, a protocol composition for IoT federated learning with a single coordinating server and three threshold helpers. The server holds no decryption key. TriSAFE combines four mechanisms that are usually studied in isolation: (i) encrypted client updates accompanied by zero-knowledge proofs that each coordinate lies within a bounded range; (ii) a new lightweight binding step (the plaintext-equivalence protocol, PEP) that cryptographically ties the values proven in zero knowledge to the exact ciphertext later aggregated by the server, closing a substitution gap left by range proofs alone; (iii) helper-added differential privacy noise applied homomorphically before any decryption, so the server only ever sees a noised aggregate; and (iv) fixed-cadence batching with calibrated cover traffic to hide participation from passive network observers. Across two IoT intrusion-detection benchmarks (Edge-IIoTset and N-BaIoT) and MNIST, TriSAFE keeps accuracy within 0.1-2.1 percentage points of the no-attack baseline under Byzantine, label-flip, FANG, and time-delay attacks, with attack success rate below 1% (<0.1% for FANG). Timing inference by a passive observer drops close to chance, and the end to end overhead is 7-36% relative to a non-defended baseline. On MNIST, TriSAFE achieves 89-91% accuracy, 15-17 points above the MODEL benchmark under the same attack suite. The design is practical for gateway-assisted IoT deployments under the assumption that the coordinator does not collude with two helpers and that at least two helpers contribute honest DP noise.
The integrity of electoral systems is fundamental to democratic governance; however, traditional voting mechanisms suffer from security vulnerabilities, lack of transparency, and accessibility constraints. This paper proposes a blockchain-based voting system leveraging distributed ledger technology to ensure secure, transparent, and tamper-resistant elections. The system integrates cryptographic techniques such as Zero-Knowledge Proofs (ZKPs) and Elliptic Curve Cryptography (ECC) within a permissioned blockchain framework using Hyperledger Fabric and Practical Byzantine Fault Tolerance (PBFT) consensus. A three-tier architecture consisting of Application, Blockchain, and Data Storage layers ensures scalability and efficiency. Security mechanisms including multi-factor authentication, end-to-end encryption, and AI-based anomaly detection mitigate potential threats such as Sybil attacks and denial-of-service attacks. Comparative analysis indicates improved security, transparency, and cost-effectiveness over traditional systems. The proposed framework demonstrates strong technical feasibility and provides a foundation for future advancements in digital electoral systems.
Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.
Prof. Abhijeet More, Tejashree B. Patil, Deep Kharate, M P Akhil · 5 authors
As the multi-chain digital assets, decentralized finance (DeFi) and non-fungible tokens (NFTs) seeing rapid development, cryptocurrency portfolio management is causing strong pain among users.With the growing number of blockchain networks like Ethereum and a variety of chains, users commonly have assets across multiple wallets, protocols and dApps.Classic portfolio tracking services often require the constant relationship between client and server, with centralized servers, offering heavy privacy issues and security implications.Manual and account based access Many of these systems require data to be manually entered or employees to sign in with their accounts, which opens up the possibility for data leaks, inaccurate reporting, and divulgence of sensitive financial information.More centralized trackers unfortunately have a very poor understanding of more advanced DeFi functions such as staking, joining liquidity pools, and yield farming positions, total or just plain token approval permissions leading to either incomplete or worse yet misleading asset summaries.To solve the above issues, this system suggests a completely decentralized cryptocurrency portfolio tracker on client-side.The code utilizes APIs like Alchemy, Zapper and CoinGecko to read real-time token balances, NFTs creatures or positions (for DeFi), and allowances from the current network directly offchain.Being exclusively client side, the tracker does not rely on centralized databases and it is designed to minimize privacy compromises.The built-in on-chain security module is its most noticeable feature, as it detects any potentially malicious or extremely large token approvals given to smart contracts.Suspicious approvals can be detected, and then revoked in a timely manner through signed wallet transactions without needing to reveal any private keys.The results show that this decentralized tracker would provide significantly better user privacy, data accuracy and overall security.As a serverless applications service, that bypasses central authentication, as well as database storage, it offers a transparency, user-centric and scalable way to manage digital assets securely.
Open access
Internet Traffic Analysis and Secure E-voting
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
Mohammad Javad Jannati, Abolfazl Iraninasab, Mehrshad Eskandarpour
As blockchain adoption accelerates, smart contracts have become attractive targets for attackers, often resulting in significant financial losses. While many studies focus on well-known vulnerabilities like reentrancy or integer overflows, weaknesses in pseudo-random number generation (PRNG) remain a persistent and critical challenge despite their role in decentralized applications such as lotteries, games, and token distribution. In Ethereum, randomness is often derived from predictable environmental variables like block timestamps or sender addresses, making these systems vulnerable to manipulation. This paper presents a rigorous investigation into PRNG vulnerabilities in Ethereum smart contracts and introduces two practical attack strategies. The first method relies on brute-force contract deployment to obtain a desired output, incurring high gas costs. The second approach leverages the CREATE2 opcode to precompute candidate contract addresses off-chain, reducing gas usage by over 90%. However, since final outcome prediction depends on block.timestamp at execution time, attack success is contingent on network timing stability and validator behavior. Through formal analysis and empirical evaluation on a controlled local test network, we demonstrate success rates of 100% for Method 1 and 98% for Method 2 under fixed-timestamp conditions. Under simulated live-network congestion, Method 2 success drops to 87% due to block.timestamp sensitivity. Our findings highlight the urgent need for secure randomness solutions, such as verifiable random functions (VRFs) and decentralized randomness beacons. Without adopting such mechanisms, blockchain applications across Ethereum and other EVM-compatible platforms remain exposed to critical security risks.
Token-based voting systems are increasingly adopted in digital governance contexts such as decentralized autonomous organizations and participatory budgeting, yet their standard aggregation rules often lead to undesirable outcomes, including oligarchic dominance or voter apathy. This paper introduces a general mathematical framework for token-based voting that interpolates between one-person-one-vote and one-token-onevote paradigms through the notion of radical voting functions. These functions map voting tokens to actual votes via concave transformations that preserve incentives for participation while compressing excessive voting power. We formalize consensus as an aggregation of transformed votes and study its structural properties using tools from convex analysis and majorization theory. We show that radical voting functions reward broad and evenly distributed support and penalize highly concentrated voting patterns, thereby favoring pluralistic outcomes over individualistic ones. Quadratic voting emerges as a special case within this framework, characterized by linear marginal voting costs. The analysis is extended to account for voter heterogeneity by incorporating similarity measures into the consensus function, linking voting outcomes to diversity among participants. Overall, the framework provides a principled foundation for designing voting mechanisms that balance merit, inclusiveness, and resistance to capture in token-based governance systems.
Blockchain-based voting systems provide transparency and auditability but introduce significant privacy risks due to publicly observable metadata. Existing approaches rely on mixnets or heavy cryptographic primitives to achieve anonymity, resulting in high computational overhead and limited scalability. In this paper, we propose a novel privacy-preserving voting protocol that eliminates the need for full ciphertext mixnets by introducing a selective metadata mixing mechanism. Our protocol combines zero-knowledge proofs for vote validity, homomorphic encryption for confidential aggregation, and randomized metadata transformations to achieve unlinkability. We formalize security properties including ballot secrecy, unlinkability, and end-to-end verifiability, and prove security under standard cryptographic assumptions. We further provide a gas-aware smart contract model and evaluate scalability for elections with one million voters under Layer-2 rollup deployment. Our results show that the proposed protocol reduces anonymization complexity from O(n log n) to O(n) while maintaining strong privacy guarantees.
Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.
Voting is a cornerstone of democracy, enabling individuals to choose their leaders and influence decisions shaping their communities and future. Traditional voting systems, however, face numerous challenges, such as long queues, paper-based inefficiencies, and security vulnerabilities. To address these issues, blockchain technology has emerged as a transformative solution, leveraging its decentralized and secure infrastructure. This paper presents a blockchain-based e-voting system aimed at enhancing accessibility, security, and efficiency. By utilizing the Ethereum blockchain and smart contracts, the system ensures transparency, immutability, and tamper-proof vote recording. Furthermore, the integration of AI-powered facial recognition technology reinforces identity verification, guaranteeing that only authorized voters participate. Comprehensive testing, including simulations and stress analyses, confirms that the proposed model enhances the voting process by offering a secure, user-friendly, and reliable digital platform. This research highlights the potential of combining blockchain and AI to modernize voting systems, fostering trust and inclusivity in democratic processes. This paper introduces a blockchain-based e-voting system that simplifies the voting process while ensuring maximum security and trust. By using the Ethereum blockchain and smart contracts, votes are recorded and verified securely, leaving no room for manipulation. To make the system even more robust, AI-powered facial recognition is integrated to confirm voter identity, ensuring only eligible individuals can participate. The system has been tested extensively to ensure it’s not only secure but also easy to use, providing a seamless experience for voters. This combination of blockchain and AI has the potential to revolutionize voting, making it fairer, more inclusive, and efficient for everyone.
Online harassment, incitement to violence, racist behavior, and other harmful content on social media can damage social harmony and even break the law. Traditional blocklisting technologies can block malicious users, but this comes at the expense of identity privacy. The anonymous blocklisting has emerged as an effective mechanism to restrict the abuse of freedom of speech while protecting user identity privacy. However, the state-of-the-art anonymous blocklisting schemes suffer from either poor dynamism or low efficiency. In this paper, we propose $\mathsf{ShadowBlock}$, an efficient dynamic anonymous blocklisting scheme. Specifically, we utilize the pseudorandom function and cryptographic accumulator to construct the public blocklisting, enabling users to prove they are not on the blocklisting in an anonymous manner. To improve verification efficiency, we design an aggregation zero-knowledge proof mechanism that converts multiple verification operations into a single one. In addition, we leverage the accumulator's property to achieve efficient updates of the blocklisting, i.e., the original proof can be reused with minimal updates rather than regenerating the entire proof. Experiments show that $\mathsf{ShadowBlock}$ has better dynamics and efficiency than the existing schemes. Finally, the discussion on applications indicates that $\mathsf{ShadowBlock}$ also holds significant value and has broad prospects in emerging fields such as cross-chain identity management.
How users adapt after being sandwiched remains unclear; this paper provides an empirical quantification. Using transaction level data from November 2024 to February 2025, enriched with mempool visibility and ZeroMEV labels, we track user outcomes after their n-th public sandwich: (i) reactivation, i.e., the resumption of on-chain activity within a 60-day window, and (ii) first-time adoption of private routing. We refer to users who do not reactivate within this window as churned, and to users experiencing multiple attacks (n>1) as undergoing repeated exposure. Our analysis reveals measurable behavioral adaptation: around 40% of victims migrate to private routing within 60 days, rising to 54% with repeated exposures. Churn peaks at 7.5% after the first sandwich but declines to 1-2%, consistent with survivor bias. In Nov-Dec 2024 we confirm 2,932 private sandwich attacks affecting 3,126 private victim transactions, producing \$409,236 in losses and \$293,786 in attacker profits. A single bot accounts for nearly two-thirds of private frontruns, and private sandwich activity is heavily concentrated on a small set of DEX pools. These results highlight that private routing does not guarantee protection from MEV extraction: while execution failures push users toward private channels, these remain exploitable and highly concentrated, demanding continuous monitoring and protocol-level defenses.
In 2008, the idea of Bitcoin, a peer-to-peer electronic cash system, was proposed by Satoshi Nakamoto. It describes a distributed system for managing digital transactions. Based on this idea, the blockchain concept has evolved. Blockchain is a distributed ledger. The ledger is immutable and shareable among all the user nodes. The ledger/blockchain contains several blocks chained by hash values. If we try to modify a block, its hash value will change; the hash value is already stored in the neighbor node, so the neighbor node will not allow it to change. Thus, immutability is achieved. The blockchain is worthy because of its good characteristics, such as data decentralization and a high level of trust. This chapter represents a detailed study on blockchain architecture, consensus mechanisms, and their application in digital image watermarking. Digital image watermarking is used for copyright protection, ownership claim, and image tamper detection. If we use blockchain with watermarking, the technique becomes more secure and robust. Though the applications of blockchain technology in image watermarking are in a nascent stage at present, the disruptive and revolutionary nature of the blockchain will make it a significant force shortly.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Secure electronic voting (e-voting) systems have become an essential component of modern democratic processes, demanding strong guarantees of privacy, integrity, verifiability, and resistance to coercion. Homomorphic commitment schemes, which integrate the properties of commitment schemes with homomorphic encryption, provide a promising approach to meeting these requirements by enabling computations on encrypted or committed data without revealing the underlying information. This capability allows secure vote tallying while preserving voter anonymity. This paper presents a comprehensive review of homomorphic commitment schemes within secure voting infrastructures, focusing on key security models such as privacy, verifiability, coercion resistance, and robustness against malicious adversaries. It also examines optimization techniques, including batching, threshold cryptography, and blockchain integration, which enhance system efficiency and scalability. Furthermore, emerging paradigms such as post-quantum cryptography and decentralized systems are discussed for their potential impact on voting protocols. The study highlights advancements in cryptographic primitives, zero-knowledge proofs, and distributed ledger technologies, while providing a comparative analysis of multiple research contributions. The findings indicate that although homomorphic commitment schemes significantly enhance transparency and privacy, challenges related to computational complexity, scalability, and real-world implementation persist, suggesting the need for lightweight, quantum-resistant, and hybrid secure voting solutions. , , , ,
Even in this day and age, when digital technologies are becoming more and more prevalent, it is still extremely important for democratic systems to maintain the honesty and openness of their voting procedures. This article introduces NextGenVote, a decentralised online voting platform developed to address the security, transparency, and confidence issues traditional electronic voting systems face. Automation of election operations, including voter registration, candidate administration, ballot casting, and result computation, is achieved through smart contracts written in the Solidity programming language. The system is built on the Ethereum blockchain. MetaMask is a React-based frontend that uses Web3.js to connect to the blockchain. MetaMask is responsible for ensuring that user authentication and transaction signatures are secure. Therefore, to prevent unauthorised manipulation, the platform utilises a role-based access control approach that clearly distinguishes between administrative capabilities and voter credentials. NextGenVote assures that election results are tamper-proof, traceable, and auditable. It was deployed and tested in a local blockchain environment powered by Ganache. The system provides a solid foundation for scalable, secure, and transparent digital elections by eliminating centralised intermediaries and relying solely on processes executed on the blockchain.
Tengku Mohd Diansyah, Nuraminah Ramli, Muzammil Jusoh
This study addresses the limitations of existing decentralized e-voting systems, particularly their reliance on public distributed infrastructures, limited real-world deployment feasibility, and lack of comprehensive evaluation. Previous studies have demonstrated the potential of distributed ledger-based voting mechanisms; however, most focus on conceptual designs or small-scale prototypes without detailed performance and usability validation. To address this gap, this research proposes and implements a decentralized e-voting system deployed on a local server infrastructure using distributed ledger technology and automated validation mechanisms for vote integrity. The system is designed to reduce dependency on external networks while maintaining transparency, immutability, and operational efficiency. The system was evaluated through functional testing, performance analysis, and user acceptance testing involving 30 participants in a controlled environment with 20 simulated voters. The results show that the system achieved a functional accuracy of 96% across 25 test scenarios. The average transaction response time ranged between 0.6 and 1.6 seconds, indicating efficient processing under moderate load conditions. However, the evaluation is limited to small-scale simulations and does not include stress testing, large-scale scalability analysis, or advanced security validation. Therefore, the findings demonstrate system feasibility rather than fully validated effectiveness. These results suggest that decentralized e-voting systems deployed on local infrastructures can provide a practical and efficient solution for controlled election environments, while further research is required to evaluate scalability, security robustness, and real-world deployment readiness.
Chi Zhang, Fenhua Bai, Xiaohui Zhang, Jinhua Wan · 6 authors
As a middleware technology in distributed computer systems, blockchain systems represent a paradigm for achieving node interconnectivity. Despite this, technical differences between various blockchain networks have led to the emergence of a phenomenon known as multi-chain, where inter-chain communication has become a trust barrier. Cross-chain technology is a powerful tool that allows data to flow between different blockchain networks, breaking down data barriers and enabling seamless data transfer. However, cross-chain identification may lead to potential risks such as the exposure of private information and data loss or tampering. In this brief, we propose Universal Cross-Chain Permissioned Blockchain (UCCPB) architecture, which connects single permissioned chains into a multi-chain system. Based on this, the Cross-Chain Anonymous Identity Authentication (CCAIA) model is proposed, which implements privacy-preserving chain identity registration and verification through zero-knowledge proof without a trusted setup. Furthermore, we propose the Proof of Cross-Chain Invocation (PoCI) mechanism of UCCPB, which consists of a node election and consensus on the invocation result. This mechanism ensures the correctness of the cross-chain invocation results and incentivizes nodes to participate in UCCPB. Our experiments show that the proposed UCCPB achieves a balance between performance and privacy while improving the security of cross-chain invocations.
Denis Wapukha Walumbe, Gabriel Kamau, Jane Wanjiru Njuki
With the rising integration of blockchain in critical domains such as healthcare, designing efficient, lightweight, and privacy-preserving consensus mechanisms remain a significant challenge.Existing Proof-of-Stake (PoS) implementations often incur high computational and communication overhead, making them unsuitable for telemedicine systems.This study proposed LightweightPoS, a novel voting mechanism designed for this environment.The proposed mechanism incorporates a cluster-based voting to minimize message complexity, Byzantine Agreement protocol for robust fault tolerance and cryptographic sortition to ensure fairness and privacy.This implementation slashes global communication, reducing message complexity by over 95% compared to traditional PoS models.The study evaluated the proposed and baseline mechanisms through simulations using real-time telemedicine data sensors.The results demonstrated that the proposed mechanism consistently achieved sub-10ms latency, high transaction throughput (up to 2400 TPS) and low energy consumption (~0.002kWh per round).It significantly outperformed baseline mechanism like Algorand and Ouroboros.Furthermore, the system included an effective Byzantine node detection, ensuring reliability under adversarial conditions.This work contributes a practical consensus voting mechanism that balances privacy and regulatory compliance.It provides a robust foundation for deploying blockchain technology in privacy-sensitive telemedicine applications.
Private BitTorrent trackers enforce upload-to-download ratios to prevent free-riding, but suffer from three critical weaknesses: reputation cannot move between trackers, centralized servers create single points of failure, and upload statistics are self-reported and unverifiable. When a tracker shuts down, users lose their contribution history and cannot prove their standing to new communities. We address these problems by storing reputation in smart contracts and replacing self-reports with cryptographic attestations. Peers sign receipts for received pieces; the tracker aggregates them via BLS signatures and updates reputation. If a tracker is unavailable, peers fall back to an authenticated distributed hash table (DHT): stored reputation acts as a public key infrastructure (PKI), preserving access control without the tracker. Reputation is portable across tracker failures through single-hop migration in factory-deployed contracts. We also address the privacy implications of publishing public keys and reputations tied to private trackers on a public ledger: we propose ephemeral session keys to prevent linking peer identities, zero-knowledge membership proofs for anonymous DHT participation, and confidential reputation using homomorphic commitments. We formalize the security requirements, prove four security properties under standard cryptographic assumptions, and evaluate a prototype. Measurements show that transfer receipts add less than 5\% end-to-end overhead with typical piece sizes. To minimize signing overhead, we adopt a hybrid signature scheme: ECDSA signs individual piece receipts at transfer time for low per-operation latency, while BLS serves as the overarching scheme, enabling compact aggregation of many receipts into a single proof at report time. This design reduces client-side signing cost by an order of magnitude compared to using BLS throughout.