Elections may be expedited, simplified, and enhanced through electronic voting. They are not frequently employed as a result of security, transparency, scalability, and voter confidentiality concerns. Our blockchain-based electronic voting system is impermeable, visible, and privacy-protective due to the use of advanced cryptographic algorithms and a permissioned distributed ledger. A permissioned blockchain that employs an expedited consensus method enhances throughput and minimizes latency during critical elections. Voter registration, voting, and tabulation are automated through the use of smart contracts. This mitigates centralization and manipulation. Privacy is safeguarded through encryption, decentralized identity (DID) frameworks, and verified methods. Comprehensive verification is facilitated by the protection of voter anonymity. In a hybrid architecture, scalability is enhanced and computational power is reduced through off-chain storage and on-chain validation. The proposed system is capable of withstanding unauthorized access, data manipulation, and duplicate voting, as evidenced by a comprehensive security and performance analysis. Furthermore, it surpasses voting systems that are founded on blockchain technology. The findings indicate that the secure digital election technology is both scalable and viable, thereby facilitating the implementation of transparent and dependable voting systems.
Mohammad Y. Allaho, Mehmet H. Karaata, Israa A. Elgemiei
The distributed ledger systems rely heavily on miners, who are a vital component of the cryptocurrency ecosystem. Most cryptocurrencies cease to exist within five years of operation [1] due to churning. Most current cryptocurrency analyses in the literature focus on mining pools and ignore the individual minersâ perspective and in-depth analysis of the churning phenomenon and its possible reasons. In this study, we conducted a longitudinal and overall study on two of the most growing cryptocurrency networks, namely Bitcoin and Ethereum. The Bitcoin dataset used spans over 12 years (2009-2021). Whereas the Ethereum dataset spans over 8 years (2015-2023), including the two versions of Ethereum (before and after the merge). Our goal is to uncover the factors that drive minersâ churning and reveal essential characteristics of cryptocurrency mining, such as network fairness and centrality. Generally, both networks experience a decline in active miners over time. Our results confirm the centrality of the Bitcoin and Ethereum networks, whereas Bitcoin is found to be more distributed and fairer than Ethereum in both versions. Also, in Bitcoin, solo miners are less centralized and experience a fairer distribution of blocks formation than pool miners, however, pool miners have more mining rewards on average. Also, pools are found to decrease churning for pool miners compared to solo miners. Moreover, it is found that minersâ waiting time is a significant factor in minersâ churning. The existing protocols used require improvements to increase network decentralization and fairness, as well as reduce minersâ churn.
Lalithambikai S, R Kavinkumar, Sowndariya K, Barath M ¡ 5 authors
While digital shifts have radically redefined modern governance and civil operations, the practice of casting ballots electronically continues to grapple with persistent obstacles concerning data transparency and operational robustness. Conventional, centralized digital voting systems typically harbor singular vulnerability points that attract cyber offensives, compounded by a distinct lack of mechanisms to rapidly manage arising voter concerns. In response to these pressing flaws, this study introduces a multifaceted architecture merging distributed ledger technologies with an intelligent, machine-learning-driven grievance resolution interface. Specifically, our model leverages a decentralised blockchain framework for immutable ballot storage, ensuring that individual vote modifications are virtually impossible and establishing a trustless verification environment devoid of centralized oversight. This schematic aims to seamlessly preserve data fidelity and supreme voter anonymity. Our comprehensive investigation of these distributed consensus rules and AI-guided triage methods indicates that unifying rigid cryptographic ballot handling together with responsive, automated complaint mechanisms dramatically elevates overall electoral resilience while reinforcing public faith in democratic workflows.
Electronic voting systems are designed to modernise democratic processes by providing efficient, transparent, and accessible elections. They promise rapid tallying, reduced human error, and increased participation. However, large-scale deployment remains hindered by unresolved concerns around security, privacy, scalability, and trust. Direct recording electronic machines suffer from limited verifiability. In Internet voting, the more fundamental risks stem from compromised end-user devices, difficulty in achieving end-to-end verifiability that ordinary voters can meaningfully check, and exposure to coercion and vote buying, rather than generic cyberattacks alone. Blockchain-based approaches, while offering immutability and public auditability, face significant scalability limits. Network throughput and latency constrain election-sized workloads, fee volatility creates cost uncertainty, and per-vote on-chain actions, such as posting ballots and verifying cryptographic proofs, incur prohibitive costs that grow linearly with the number of voters. The openness of public ledgers also leaks metadata that can erode privacy. Consequently, achieving accountability and transparency without sacrificing individual ballot secrecy and practical efficiency remains a central challenge. This thesis addresses these challenges by providing the first thorough analysis of a ranked-choice blockchain election protocol that had not been previously examined in detail. The analysis identifies critical limitations related to privacy and efficiency that weaken unlinkability and verifiability. Building on these findings, the first significant contribution of this thesis is the design of a new, verifiable, and privacy-preserving voting framework that eliminates the need for a trusted tallying authority. The scheme employs anonymous participation tokens and nullifiers to enforce one-time eligibility. At the same time, voters cast encrypted ballots accompanied by zero-knowledge proofs that confirm eligibility, correctness, and uniqueness without disclosing their identity or the content of their vote. Tallying is achieved through a decentralised threshold decryption process that ensures fairness and confidentiality. The second significant contribution of this thesis is an efficient proof-batching and verification mechanism that addresses the scalability bottlenecks of existing blockchain-based approaches. By aggregating multiple proofs off-chain and submitting a single, succinct batch proof with updated commitments, the protocol reduces on-chain verification to a near-constant cost per voter. This significantly decreases computational and financial overhead, enabling scalability to large elections. The proposed framework is analysed under realistic adversarial models and shown to achieve privacy, eligibility, uniqueness, and universal verifiability. Performance evaluation demonstrates that the batching mechanism substantially lowers costs compared to existing protocols. Overall, this research advances the state of the art in blockchain-based electronic voting by providing the first comprehensive evaluation of a ranked-choice protocol and proposing novel mechanisms that overcome its limitations, thereby laying a foundation for secure, transparent, and scalable digital elections.
For communication scenarios demanding extremely high information security and facing significant risks of data leakage, a covert communication scheme based on Ethereum virtual machine bytecode was proposed. By strategically allocating the storage space of smart contract variables, the scheme embedded covert data into contract bytecode and utilized the inherent characteristics of bytecode to set positioning markers, enabling efficient extraction by the receiver. Additionally, three ciphertext parsing modes were designed to accommodate transmissions of different data scales, further enhancing the security of encoded data. Theoretical analysis and extensive experimental results demonstrate that the scheme can effectively hide up to 170 bit of information per transaction. The structural similarity of opcode frequency distributions between the embedded contract and the original contract reaches up to 99.78%. The Pearson correlation coefficient of the high-frequency 3-gram opcode patterns between the normal and embedded contracts is 0.999 7 (<italic>p </italic>= 6.42Ă10âťÂšâ´), indicating that the embedding process does not introduce statistically significant differences in the local instruction sequence distribution. These results fully validate the strong concealment capability, transmission efficiency, and security of the proposed scheme.
Open access
Internet Traffic Analysis and Secure E-voting
Physical Unclonable Functions (PUFs) and Hardware Security
The proliferation of sophisticated AI and bot networks necessitates robust methods for verifying human uniqueness and liveness in digital ecosystems. Existing Proof-of-Personhood (PoP) solutions rely on centralized authorities, invasive static biometrics, or socially-correlatable data, creating vulnerabilities in privacy, security, and accessibility. We introduce the Entros Protocol, a decentralized framework for PoP and Self-Sovereign Identity built on Solana. The core innovation is temporal consistency: the assertion that human identity is best proven not by a static secret, but by the bounded, chaotic drift of biological and behavioral patterns over time. The framework captures multi-modal behavioral data (voice prosody, hand tremor, touch dynamics) during a configurable behavioral challenge, extracts a 308-dimensional feature vector, and produces a 256-bit locality-sensitive hash via SimHash. A Groth16 zero-knowledge proof verifies that consecutive fingerprints fall within a bounded Hamming distance without revealing either value. Attestations are anchored to non-transferable identity tokens (SPL Token-2022) with progressive Trust Scores. We provide formal security definitions, analyze the protocol against replay, synthesis, and Sybil attacks, introduce a graduated trust model distinguishing first-time liveness checks from sustained temporal consistency, and present benchmarks from a working implementation deployed on Solana devnet.
LokNirikshan: A Blockchain-Inspired Election Transparency and Management System LokNirikshan is a comprehensive, blockchain-inspired digital platform designed to enhance transparency, integrity, and efficiency in modern election systems. Traditional voting mechanismsâboth paper-based and electronicâoften suffer from limitations such as lack of transparency, centralized control, slow processing, and susceptibility to data manipulation. These challenges reduce public trust in electoral outcomes and highlight the need for more secure and verifiable solutions. This work proposes a hybrid approach that integrates key blockchain principlesâsuch as cryptographic hashing, Merkle tree-based verification, and audit trailsâinto a practical, scalable, and user-friendly web-based system. Instead of implementing a fully decentralized blockchain, which introduces complexity and performance constraints, LokNirikshan selectively adopts core concepts to achieve transparency and data integrity without compromising usability. The system supports the complete election lifecycle, including voter registration, constituency and booth assignment, political party onboarding, candidate nomination, election configuration, voting, result computation, and post-election verification. It incorporates role-based access control (RBAC) to manage different stakeholders such as voters, party representatives, party heads, and administrators, ensuring secure and structured interactions across the platform. A key innovation of the system lies in its verification layer, which utilizes Merkle trees to ensure data integrity. Election results are converted into cryptographic hashes and organized into a hierarchical structure, generating a root hash that acts as a tamper-evident reference. This allows independent verification of results without requiring access to the complete dataset, thereby promoting trust through transparency. Additionally, an open public verification portal enables users and observers to validate election outcomes in a decentralized manner. The platform is implemented using modern web technologies, with React and Vite for the frontend, Node.js and Express for backend services, and MongoDB for flexible data storage. Authentication and session management are handled using JSON Web Tokens (JWT), ensuring secure access control. The system also includes anomaly detection mechanisms to identify irregularities such as duplicate entries, missing records, and inconsistent data. Experimental evaluation was conducted using a simulated dataset of 500 voters across multiple constituencies. The system demonstrated high functional reliability, successfully executing all stages of the election process. Verification tests using Merkle proofs achieved 100% accuracy for valid records, while anomaly detection reached approximately 98% effectiveness. Performance analysis indicated efficient response times, with most operations completing within milliseconds. Despite its strengths, the system has certain limitations, including scalability constraints for large-scale elections, partial centralization, and basic identity verification mechanisms. Future enhancements may include full blockchain integration (e.g., Ethereum or Hyperledger), advanced cryptographic techniques such as zero-knowledge proofs, improved voter authentication, machine learning-based anomaly detection, and mobile accessibility. In conclusion, LokNirikshan demonstrates that a balanced integration of blockchain-inspired concepts with conventional web technologies can significantly improve the transparency and reliability of election systems. It provides a practical foundation for developing secure, verifiable, and scalable digital governance platforms, contributing to increased public trust in democratic processes.
The Blind Watchdog Protocol (BWP) constructs a directed oversight graph where each autonomous agent has exactly one hidden watchdog, but no agent knows who watches it. Compliance emerges through a Panopticon equilibrium â the mere possibility of observation makes defection irrational. A closed-form Nash equilibrium theorem (6-step proof, TLC model-checked: 2,071 states, zero violations) establishes that compliance is strictly dominant under configurable parameters. The protocol implements 10 composable plugins (reputation, staking, mixnet, rotation, correlation analysis, adaptive watcher allocation, conviction scoring, knowledge gating, hybrid oversight, and optimistic slashing) and maps 10 biological oversight mechanisms to executable code. Key results: 100% detection rate with 0% false positives across 1,000 deterministic simulation runs (p_d=1.0). Stress-tested with stochastic observation noise, collusion sweeps (10-40%), Dark DAO bribery economics, and latency profiling. Layered defense separates immediate containment (escalation levels 1-3) from delayed adjudication (optimistic slashing with challenge period). Three-tier Sybil resistance via admission staking, DID-based identity, and Proof-of-Personhood interface. Constant-rate dummy traffic for timing-analysis resistance. Standardized evidence protocol for dispute resolution. Dynamic VaR-coupled stakes for high-value environments. Three fundamental open problems are identified: out-of-band cryptographic bribery (Dark DAOs), the recursive final arbitrator problem, and the latency-anonymity-cost trilemma for LLM agents. The reference implementation (422 tests, 5,757+ LOC, Python) is licensed under PolyForm Noncommercial 1.0. This paper is a defensive publication of the protocol design, formal proofs, and empirical results.
In the classic model, data integrity assumes a simple sender-receiver channel where threats are limited and verifications are straightforward. However, the modern Internet has reshaped this paradigm. In an era of viral misinformation, encrypted messaging, and decentralized finance, integrity is no longer about just who sent the data, but what it really means and whether it can be trusted. For instance, can we verify the authenticity of a direct message screenshot? Is Signal's end-to-end encryption truly end-to-end when a central server distributes users' keys? Can decentralized protocols, which have attracted four trillions in capital, sustain trust under attacks that wipe out millions?In response, we present a modern perspective on data integrity across diverse systems, arguing for the need of comprehensive innovations from theory to practice along three axes: cryptographic foundation in which we borrow ideas from theoretical research and develop interesting cryptographic tools, protocol design in which we find and achieve novel application goals, and empirical security analysis in which we critically evaluate deployed systems to understand their strengths and exploit their blind spots.To ground these ideas, we discuss three cases: Cauchyproofs as a batch-updatable vector commitment, an analysis of proxying in TLS oracles revealing subtleties in AEAD context unforgeability, and attacks and improvements on the Tor directory protocol. These case studies illustrate both the fragility and opportunity in today's integrity landscape, and how an integrated approach can help guide us forward.
Transform the web into your data source. Chapter 10 introduces methods for extracting financial data and downloadable files from websites using Python tools such as BeautifulSoup and requests. Learners will practise legal and ethical scraping through examples based on demonstration sites. The chapter includes a compliance checklist covering permissions, terms of service, and data protection. It also introduces the use of application programming interfaces for accessing financial data, including cryptocurrency prices from CoinGecko.
Miksi is a decentralized blockchain protocol that uses zero knowledge proofs (ZKP) and cryptographic commitments to enable anonymous transactions within a secure decentralized network. The system consists of three components: the main application (miksi.ts), the ZKP circuits (deposit and withdraw.circom), and the smart contracts (Miksi.sol, deposit-verifier.sol, and withdraw-verification.sol). Each component plays a pivotal role in the overall security of the system, and we evaluate them for common vulnerabilities such as improper input validation, reentry attacks, and weaknesses in proof verification. Through this analysis, we highlight both the strengths and potential areas for improvement in ensuring secure, anonymous cryptocurrency transactions.Keywords: Ethereum, ZKP, blockchain, DeFi, anonymity, mixer
ABSTRACT E-voting in polarized contexts requires a strict balance between public verifiability, ballot secrecy, andcoercion resistance. Traditional centralized systems lack transparency, while fully decentralized modelsface scalability and privacy issues. This paper proposes a hybrid architecture compliant withOSCE/ODIHR standards [1] for low-trust environments. The protocol decouples identity from voting anoff-chain Oracle manages authorization via cryptographic tokens, while the Waves DLT acts as animmutable bulletinboard.Utilizinghomomorphicencryption[2],Zero-KnowledgeRangeProofs(ZKRP) [3],and Distributed Key Generation (DKG) [4], the system ensures End-to-End Verifiability (E2E) bydelegating tallying to auditable scripts. Finally, the study examines model limitations, specificallyregarding endpoint vulnerabilities and physical constraints on coercion resistance. KEYWORDS E-Voting, Distributed Ledger Technology, Homomorphic Encryption, End-to-End Verifiability, ZeroKnowledge Proofs PDF LINK: https://ijcionline.com/paper/15/15226ijci01.pdf VOLUME LINK: https://airccse.org/journal/ijci/Current2026.html MORE DETAILS: https://airccse.org/journal/ijci/index.html
Divya Badwaik, Namo S. Shende, Shantanu N. Wankhede, Prajwal V. Gourkhede ¡ 6 authors
The increasing demand for secure, transparent, and efficient electoral systems has led to the exploration of advanced digital technologies in voting processes. Traditional voting systems, including paper-based and electronic voting machines, are often associated with challenges such as lack of transparency, susceptibility to tampering, centralized control, and delayed result processing. To overcome these limitations, this paper proposes VOTECHAIN, a blockchain-based electronic voting system that leverages the decentralized and immutable nature of blockchain technology to ensure trust and security in elections. The proposed system is built on the Ethereum blockchain using smart contracts, which automate critical operations such as voter registration, candidate registration, vote casting, and result computation. Each vote is treated as a secure transaction and is recorded on a distributed ledger, making it tamper-proof and verifiable. The system ensures that each voter can cast only one vote while maintaining voter anonymity through cryptographic techniques. A web-based decentralized application (VOTECHAIN) is developed using Web3.js and MetaMask to facilitate user interaction with the blockchain network. The system is tested using Ethereum test networks, demonstrating efficient performance, secure transaction handling, and transparent vote counting. The results indicate that blockchain technology can significantly enhance the reliability and integrity of electronic voting systems.
SOUJANYA SOUJANYA, N. JYOTHI N. JYOTHI, G. KUSHAL G. KUSHAL, M.THRILOCHAN M.THRILOCHAN ¡ 5 authors
The criminal activities in India are increasing at a rapid rate. Many of these activities go unreported. Even after having an online portal for the police for storing FIRs and NCRs, most of the FIRs are handwritten as a traditional practice. In most of the cases, the complainant has to be present in the police station to file a cognizable offense. An effective system for e-governance was started in 2009 named Crime and Criminal Tracking Network and Systems (CCTNS) for the entire country. However, it is a centralized system for a particular state. Thus, there is a need for a completely decentralized system for assuring that there is no central point of failure in the system and complaints are managed securely protected from unauthorized access. Our aim is to propose a blockchain-based solution to manage complaints against both cognizable and non-cognizable offenses. The FIR filed by the police will be encrypted, stored in the IPFS and hash is added to the blockchain network. If the police decide not to file the FIR under pressure or deny receiving any complaint, then the complainant will have strong proof against him/her as the complaint along with its timestamp was stored on the blockchain network. Having all the records stored in an immutable database would remove any chances of the FIR/NCR being tampered and going unnoticed. Keywords â Blockchain Technology, Police Complaint Management System, Smart Contracts, Distributed Ledger Technology (DLT), Decentralized Application (DApp), Data Integrity, Tamper-Proof Records, Immutable Audit Trail, Zero-Knowledge Proof (ZKP), Hyperledger Fabric and Permissioned Blockchain
Blockchain - based e-voting systems use decentralized ledgers to securely record encrypted votes, ensuring immutability, transparency, and tamper-proofverification without central authorities. These systems such as the existing BP-Vot framework integrate smart contracts, k,Îľ differential privacy, and self-sovereign identities (SSI) to balance transparency, security, and voter anonymity in remote elections. BP-Vot deploys on Hyperledger Besu, using a single pivot candidate to redistribute votes probabilistically (θ=1/d), achieving 98%+ vote approximation accuracy via Min-Max regression and 1s/TX latencyâ24% better than prior artâwhile proving robustness against reconstruction attacks. However, limitations include single-pivot privacy fragility in low- volume elections, partial reliance on election authority for key registration, and untested scalability beyond 50k votes or additional nodes.This work proposes a multi pivot parallel differential privacy extension, dynamically selecting multiple pivots for distributed noise injection, fully integrated with SSI Web3 wallets and immutable contracts. Benefits encompass superior anonymity for millions of votes, eliminated centralization risks, and optimized performance for national-scale deployments. Evaluation confirm linearprivacy/accuracy gains with vote volume, independent of candidate count, enabling GDPR-compliant, trustless e-voting superior to state-of-the-art. Keywords: Blockchain, e-voting systems, decentralized ledgers, BP-Vot framework, Hyperledger Besu, Min-Maxregression, SSI Web3 wallets
Y Liu, Zedan Zhao, Boyu Zhao, Na Wang ¡ 6 authors
Decentralized identity (DID) is a key infrastructure for Web3, granting users sovereign control over their private identity data. While existing DID systems like FADID-TT (WWW'25) realize anonymity and traceability within a single domain, the Web3 ecosystem is a multiverse of independent domains like DeFi, GameFi, and DAO. This multi-domain reality presents critical issues for current DID solutions. First, most existing solutions are built on the monolithic committee architecture, facing severe scalability bottlenecks as the committee size grows. Second, most existing solutions cannot offer strong cross-domain anonymity, where frequent cross-domain interaction inevitably exposes the user's privacy. Third, existing methods for tracing the identities of malicious users are inefficient.
Prof. M. S. Bhosale, Abhishek Kangude, Vedant Khandare, Sunil Kajave
Abstract: In modern digital governance, ensuring secure, transparent, and tamper-proof elections remains a critical challenge. Traditional voting systems, whether paper-based or electronic, suffer from issues such as centralized control, lack of transparency, and vulnerability to tampering. This paper proposes a Blockchain-Based Decentralized E-Voting System that utilizes Ethereum smart contracts, MetaMask authentication, and a Flutter-based frontend to provide a secure and transparent voting mechanism. Each vote is recorded as an immutable blockchain transaction, ensuring integrity, verifiability, and prevention of double voting. The system eliminates the need for third-party intervention and enables real-time result verification. Experimental results demonstrate improved security, reliability, and scalability, making the system suitable for modern digital election processes. Keywords: Blockchain, E-Voting, Smart Contracts, Ethereum, MetaMask, Decentralization, Web3
This paper analyses MicroMix, a noncustodial Ethereum mixer that unlinks deposits from withdrawals using browser-side zkSNARKs, a centralised relayer, and on-chain enforcement via Semaphore and Mixer contracts. The study formalises core acceptance conditionsâvalue conservation, nullifier uniqueness, externalânullifier scoping, and signal bindingâand evaluates risks that persist despite sound cryptography, including timing correlation in small anonymity sets, Sybil pool distortion, singleârelayer censorship, ETH payout liveness under gasâstipend limits, ERCâ20 heterogeneity, circuitâverifier input/order mismatches, and crossâchain replay. The work proposes concrete mitigations: randomised scheduling and probabilistic batching, multiâdenomination support, decentralised relayer participation with user-paid fallbacks, guarded call patterns with reentrancy protection, SafeERC20 enforcement and token whitelisting, strict publicâinput ordering and signalâtoâfield mapping, a fixed mixer-scoped external nullifier, and chain-bound proofs. With these measures, MicroMix can preserve unlinkability while improving liveness and correctness in adversarial environments, advancing practical, privacyâpreserving withdrawals on Ethereum.
A hybrid analytical framework is developed for the forensic investigation of Bitcoin transaction networks, addressing the inherent challenges posed by the decentralized and pseudo-anonymous characteristics of blockchain systems. While Bitcoin transactions are publicly accessible, detecting illicit activities within complex transaction graphs remains a significant challenge. Existing approaches typically depend on isolated techniques, such as rule-based methods or standalone machine learning models, which often lack sufficient effectiveness.The proposed framework combines graph-based network analysis, statistical modeling, and machine learning to enhance detection capability. Transactions are represented as a directed graph, where wallet addresses function as nodes and transactions as edges. From this representation, structural, behavioral, and temporal features are systematically extracted and integrated into a unified dataset. A Random Forest classifier is subsequently employed to categorize wallet addresses as either normal or suspicious.This integrated approach improves accuracy, scalability, and robustness, facilitating efficient analysis of large-scale blockchain data and enabling more reliable identification of fraudulent activities in real-world forensic investigations.
The value of proof-of-work cryptocurrencies critically depends on miners having incentives to follow the protocol. However, the Bitcoin mining protocol proposed by Nakamoto (2008) and implemented in practice is well known not to constitute an equilibrium: Eyal and Sirer (2018) construct a profitable deviation called ``selfish mining'' which relies on strategically delaying disclosure of newly mined blocks rather than publishing them immediately. We propose inertial mining, a novel mining protocol. When miners follow inertial mining, they produce the outcome intended by Nakamoto, i.e., a single longest chain. But unlike the Bitcoin mining protocol, inertial mining constitutes an equilibrium (assuming no miner controls more than half of the mining power). Indeed, neither selfish mining nor any other deviation is profitable. Furthermore, inertial mining only changes miners' behavior in the event of off-path forks, and can be implemented in Bitcoin without any changes to its consensus mechanism or blockchain architecture.
Public discourse plays a critical role in shaping trust, legitimacy, and governance dynamics within decentralized Web3 ecosystems. However, existing studies often examine Web3 discourse through isolated lenses such as sentiment or topic modeling, which limits their ability to capture how emotional expression and communicative purpose jointly convey strategic intent. This study proposes a three-stage decision analytics framework that transforms unstructured Web3 discourse into diagnostic signals by jointly modeling industry domain, emotional tone, and communicative purpose. The analysis draws on 10,840 user-generated posts collected from X, Reddit, YouTube, and the ENS DAO forum, using a human-in-the-loop annotation process combined with transformer-based text classification models. The framework is evaluated using a domain-adapted language model and a general-purpose baseline, with robustness assessed through five-fold cross-validation. The results indicate that curiosity and optimism frequently align with promotional intent in infrastructure and application-oriented domains, whereas skepticism and concern are more prevalent in governance-related discourse. These findings demonstrate that emotional tone and communicative intent operate as structured, decision-relevant signals rather than incidental sentiment. The proposed framework supports systematic, diagnostic monitoring of narrative dynamics as decision support, enabling organizations, platform operators, and governance stakeholders to identify emerging legitimacy risks and shifts in community trust within decentralized environments.
Blockchain-based electronic voting systems that use zero-knowledge proofs (ZKPs) have been proposed as good candidates to provide both transparency and privacy of ballots. However, a fundamental challenge remains unmet in all existing schemes: the secure generation and protection of the voter's cryptographic secret key.In this paper, HME-KG (Hybrid Multi-Source Entropy Key Generation) is presented, a new credential derivation method which utilizes a cryptographically secure random salt, the national identity number of the voter and a per-device Client Device Secret (CDS) to derive a deterministic, brute-force-resistant secret key. HME-KG is integrated into BAVS-ZK, a complete anonymous blockchain voting framework employing AES-256-GCM encrypted credential storage, a Circom-based Groth16 zk-SNARK voting circuit, and on-chain nullifier verification via Ethereum Sepolia smart contracts. Security analysis demonstrates that HME-KG achieves voter determinism, cross-voter uniqueness, single-source failure resistance, and collision resistance under the security assumptions of SHA-256. Experimental evaluation on a 10,000-voter simulation confirms a 0.9998 scalability coefficient, 1.2-second proof generation, and 306,720 gas per voteâa 38.6% reduction compared to the Open Vote Network baseline. To the extent of current literature, BAVS-ZK is the first blockchain e-voting system to provide a complete, formally specified, and experimentally validated voter credential derivation and protection scheme.
Human-friendly identifiers such as email addresses and phone numbers are convenient payment targets, but direct mappings from identifiers to blockchain addresses make balances and transaction histories enumerable by anyone who knows the identifier. We present HFI-Pay, a relay-assisted protocol for privacy-preserving identifier-routed cryptocurrency payments. The relay resolves the identifier off-chain and registers only a random intent identifier, a per-intent blinded binding rho_i, and the quoted payment tuple on-chain; no identifier or reusable recipient tag is published before claim. In a verified-quote deployment, the sender verifies an attested quote proving that rho_i was derived from the same hidden binding handle as the recipient's attested binding-key commitment, preventing relay-side recipient substitution before funding. Claims are authorized by a zero-knowledge proof, instantiated through ZK-ACE, that the claimant controls the deterministic identity whose epoch-scoped handle opens the blinded binding and authorizes release of the quoted asset and amount to a chosen destination. We define observer-model games for enumeration resistance and pre-claim unlinkability, state the composition needed for post-quote claim correctness, and characterize relay compromise and post-claim linkability. Keywords: identifier-based payment, privacy-preserving, verifiable quote, blinded claim binding, zero-knowledge authorization