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 vote—a 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
This paper investigates the strategic behavior of validators in blockchain systems utilizing the Proof-of-Stake (PoS) consensus mechanism through the application of game theory. A mathematical model of a non-cooperative game with complete information is proposed, where validators act as rational agents aiming to maximize their expected payoff by choosing between honest validation and malicious actions, specifically a double-spending attack. The model incorporates key economic parameters of the system: block and attestation rewards, transaction fees, operational costs, slashing penalties, and the probability of detecting protocol violations. Utility functions for two primary strategies – honest and attacking – are formalized, and conditions for the existence of Nash equilibrium, the central solution concept in game theory, are analyzed. The analysis demonstrates that under effective punishment mechanisms, the "all-honest" equilibrium is stable: an individual validator has no incentive to deviate from protocol-compliant behavior, as potential losses from penalties significantly outweigh any gains from a failed attack. Conversely, the "all-attackers" equilibrium, while theoretically possible, is practically unattainable due to the prohibitively high cost of acquiring a majority stake, rendering such a strategy economically infeasible. A quantitative example based on a hypothetical network of 1000 validators confirms these findings and highlights the critical importance of balancing incentives for honest behavior with strong disincentives for malicious actions. The study emphasizes the crucial role of economic security in PoS systems, where stability is ensured not only by technical safeguards but also by carefully designed economic mechanisms. The developed model can be used by blockchain protocol designers to calibrate consensus parameters, thereby promoting decentralization, resilience, and long-term network reliability. Future research can extend the model by incorporating heterogeneous validators, repeated games, and the analysis of other attack vectors. Keywords: Proof-of-Stake, validators, game theory, Nash equilibrium, economic security, slashing, double-spending attack, game model, blockchain, consensus.
Abstract: Remote electronic voting systems require tamper-evident records of ballot submissions, yet the ledger integrity problem - ensuring that the record cannot be silently altered after the fact - has received less formal treatment than ballot-phase cryptography. Existing approaches rely on distributed blockchain consensus, digital signatures on bulletin boards, or external hash-tree timestamping services, each introducing dependencies on specialized infrastructure, continuously trusted parties, or computationally intensive proof systems. This paper provides a formal security analysis of a hash-chained append-only ledger instantiated in a standard relational database with quorum replication, establishing that equivalent tamper-evidence guarantees are achievable under the sole assumption of collision resistance of the instantiated hash function. We define five security properties in the Bellare-Rogaway game-based framework. Tamper-evidence (Proposition 1) bounds any PPT adversary's advantage at 2q(λ) · Adv^CR_H, with a tight reduction to collision resistance. Fork-resistance (Proposition 2) establishes that an adversary corrupting fewer than a quorum threshold of replicas cannot cause divergent chain histories at honest replicas. Retrospective modification resistance (Proposition 3) establishes that post-close modifications are detectable by any auditor holding a real-time replica copy. Cross-ledger binding security (Proposition 4) extends these results to the dual-ledger construction of the Arcaunt architecture, in which a public ballot ledger and a temporal credential ledger are cryptographically bound at insert time, making modifications to either detectable through the other with advantage bounded by 4q(λ) · Adv^CR_H. Selector integrity (Proposition 5) establishes that the last-valid-vote rule - operating on insertion sequence rather than timestamps, making it immune to clock manipulation - is integrity-secure conditional on credential security, formally delineating the boundary between ledger and credential security domains. We apply an eight-metric comparative framework to seven e-voting integrity architectures - hash-chaining, bulletin boards, homomorphic tallying, mixnet-based systems, blockchain, KSI timestamping, and VVPAT hybrids - establishing three findings: tamper-evidence basis is universal but mechanism-specific; fork-resistance is architecturally necessary specifically for revoting-based systems; and auditability complexity is inversely correlated with cryptographic sophistication. The hash-chained relational ledger achieves collision-resistance-based tamper-evidence with O(n) verification accessible to any SQL-capable auditor - a design point unoccupied by existing systems under the same combination of properties. Prototype validation on a Firebird 5.0 implementation confirms that each proposition is instantiated by a specific database trigger mechanism, with 6ms mean ballot submission latency and O(n) verification complexity empirically confirmed.
Mobile communication channels have become a major target for large-scale and adaptive fraud, including impersonation, phishing, and unsolicited calls. Existing caller-verification frameworks depend on centralized heuristics and static credentials that fail to reflect behavioral trust or protect users in real time. This paper presents BTID (Behavioral Trust for Identity Decentralization) - a decentralized, privacy-preserving identity framework that derives caller reputation from verified behavioral feedback. BTID integrates Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) with a lightweight zero-knowledge-proof mechanism, enabling callers to prove that their behavioral reputation meets a callee's trust threshold without revealing their actual score or personal data. Each post-call rating is recorded as a cryptographic commitment and aggregated through a pairwise Sybil-resistant reputation model governed by exponential decay (λ = 0.0039, six-month half-life). A reference prototype demonstrates that the protocol is implementable and logically sound even under high-cost and high-latency conditions on public ledgers. On modern lightweight networks such as Algorand or IOTA, the same architecture can achieve sub-second verification and near-zero cost. Beyond its technical contribution, BTID also reframes the role of the blockchain itself. Rather than treating decentralization as an ideological end, this work demonstrates that a tamper-proof and privacy-preserving public ledger can serve as a shared, universal database accessible to all participants and not as a silo controlled by industrial conglomerates. In doing so, BTID shows that the blockchain can function as a neutral trust infrastructure capable of addressing a real and universal problem in mobile communication: establishing behavioral trust without sacrificing privacy.
The integrity of democratic voting systems is increasingly threatened by security vulnerabilities, lack of transparency, and trust deficits, making electoral processes susceptible to manipulation. To address these concerns, Binance Smart Chain (BSC) introduces a blockchain-powered voting framework that leverages the Proof of Staked Authority (PoSA) consensus protocol to enhance security and decentralization. To further fortify the system, ResNet-101, a deep learning-based convolutional neural network (CNN), is integrated for facial recognition authentication, ensuring voter legitimacy and eliminating identity fraud. Additionally, one-time password (OTP) authentication and live location tracking strengthen the system against unauthorized access and proxy voting. By combining blockchain technology, biometric verification, and AI-driven facial authentication, BSC establishes a highly secure, transparent, and tamper-proof voting system. This approach aims to restore public trust in electoral processes, setting a new benchmark for secure and verifiable digital voting systems in democratic governance.
Alinsha S, A Althaf, Chris P Reji, Fahad Mohammed A · 6 authors
Electronic voting techniques have gained popularity as a contemporary alternative to traditional paper-based elections because of their effectiveness and accessibility. The current electronic voting methods, however, have significant security flaws, such as multiple voting, identity theft, centralized control, and a lack of transparency. Despite the fact that blockchain technology is decentralized, immutable, and auditable, many blockchainbased voting systems merely employ cryptographic credentials and lack robust voter identification verification processes. The blockchain-based electronic voting system SecureVote, which incorporates multi-factor verification and facial biometric authentication, is proposed in this study. Ethereum smart contracts are used by the system to guarantee transparent result calculation and tamper-proof vote storage. SecureVote employs one-time password (OTP) validation as a secondary authentication method in conjunction with client-side facial recognition and deep learning-based feature extraction. The suggested design makes use of Web3.js and a decentralized application (DApp) concept for safe wallet-based transaction signing and blockchain interaction. High authentication reliability, avoidance of double voting, and effective transaction processing with low gas overhead are all demonstrated by the experimental results. SecureVote combines biometric multifactor authentication with blockchain immutability to enhance the reliability, transparency, and integrity of remote voting.
Open access
2 source records
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Kenneth Richard Dike, Ugbari Augustine, Martha Ozohu Musa
Delays and security remain major issues in traditional manual voting, while in the emerging electronic voting, trust and privacy remain issues in its adoption. This research presents the design and development of a secure electronic voting protocol that combines biometric verification of a standard identity with cryptography to preserve election integrity. This research follows the Design Science Research Methodology, producing the protocol as an artefact, beginning with quick work on it and iteratively improving it during development. The proposed architecture uses a combined National Identity verification and Liveness detection procedure for user authentication, ensuring voter uniqueness and preventing impersonation. It also integrates the RSA blind signature protocol to prevent direct linking of votes to their voters. It uses Paillier encryption to safeguard votes both in transit and at rest, and this encryption scheme has a homomorphic property that enables aggregation of encrypted votes and decryption of the final tally. It uses the SHA-256 cryptographic hashing algorithm, the HMAC authentication technique and the AES-GCM encryption to secure the integrity of data. It also uses zero-knowledge proofs to demonstrate the correctness of encrypted votes and decrypted tallies. Testing showed that it prevented a photo spoofing attempt and also blocked authentication using a person’s mother’s identity data. Also, when the blinded vote is compared with the unblinded, via local logs on the development system, there is no direct link. The whole system shows a secure electronic voting protocol that is easy to use and can be trusted.
Traditional paper-based voting system for student organization leaders election has issues related to security, transparency, and trust. This research addressed these issues by implementing a blockchain on e-voting system utilizing smart contracts to ensure the security and transparency of the voting process. The system was developed using the agile software development life cycle (SDLC) methodology and was tested using black-box and system usability scale (SUS) method to evaluate its functionality and usability. Security testing was conducted through unit testing on the smart contract and block verification within the Sepolia network. The results showed that the decentralized e-voting system could prevent vote manipulation and detecting duplicate voters, as evidenced by the unit testing of the smart contract, which confirmed that recorded votes could not be manipulated and attempts to submit multiple votes were detected and rejected. Meanwhile, system transparency was demonstrated through direct verification using a block explorer, showing that the entire voting process and the smart contract code were publicly accessible and transparent. The system was successfully simulated on a small scale within a student organization, and usability testing using the SUS method was conducted with 30 respondents. The test resulted in a score of 72 points, indicating that the system was in the good category and was well accepted by users. Therefore, the decentralized approach in this e-voting system has been proven to enhance transparency and overcome the problems of security issues in the voting process.
Attiq Ur Rehman, Shuai Lü, Muhammad Usman, Zaheer Ahmad Gondal · 7 authors
Abstract The integration of Cloud computing with the Internet of Things (IoT) has greatly increased the scale and complexity of sharing data in Cloud-based Internet of Things (CIoT) environments. However, this growth brings challenges with regard to security of sensitive data, privacy, access control management, and accountability. In this paper, we propose Block-chain Enabled Secure and Anonymous Data Sharing (BS-ADS), which is a framework that tries to overcome these challenges by combining Aggregate Key Searchable Encryption (AKSE) and blockchain-based auditing, edge-assisted revocation and accountable anonymity. BS-ADS eliminates the need for centralized trust by using blockchain to store encrypted metadata such as ciphertext hash and revocation identifier. This provides trust and transparency which are decentralized without revealing plaintext data. The frame-work includes the support of linkable ring signatures and zero-knowledge proofs to maintain user privacy while allowing for traceability and therefore allowing for the detection of malicious behavior to take place without the need of the loss of anonymity. Furthermore, edge nodes are responsible for the encryption up-dates in case of revocation, and they remove the computational load from the resource-constrained IoT devices. The performance of BS-ADS was evaluated in terms of encryption overhead, ciphertext size, and the communication cost. Experimental results demonstrate the effectiveness of BS-ADS in terms of encryption overhead, which reduces the encryption overhead by 30–40%, while guaranteeing efficient keyword-based search and data retrieval. Additionally, it offers a 20–30% reduction in communication overhead in multi-user scenarios, maintaining constant communication cost per operation (O(1)). The system is also proven secure against selective chosen-ciphertext attacks (SIND-CCA), replay attacks, Sybil attacks, and man-in-the-middle attacks. This work introduces a novel architecture for secure, scalable, and accountable data sharing in CIoT, incorporating efficient revocation mechanisms and privacy-preserving search. BS-ADS provides significant improvements in efficiency, security, and privacy, offering a promising solution for large-scale CIoT applications.
In democratic systems, secure and transparent voting mechanisms are essential to maintain public trust and electoral integrity. Traditional paper-based and centralized electronic voting systems often face challenges such as limited transparency, risk of data manipulation, and dependence on centralized authorities. To address these issues, this project proposes a decentralized blockchain-based voting system designed to enhance security, transparency, and reliability. The system is developed on the Ethereum blockchain, where each vote is recorded as an immutable transaction to prevent tampering or duplication. Smart contracts written in Solidity automate essential election functions including voter registration, vote validation, and result computation. A web-based interface built using React.js and Web3.js enables secure interaction with the blockchain, while wallet-based authentication ensures that each authorized user can cast only one vote The system is implemented and tested in a controlled environment to evaluate performance, accuracy, and resistance to double voting.
Zibin Lin, Taotao Wang, Shengli Zhang, Long Shi · 6 authors
Web 3.0 platforms need an onboarding mechanism that can admit real users at scale without forcing them to reveal identity documents or pay one on-chain verification cost per user. Existing approaches typically rely on KYC-style disclosure, per-request on-chain verification, or trusted batching, making onboarding cost and latency difficult to predict under bursty demand. We present \textbf{ZK-AMS}, a credibly anonymous admission infrastructure that maps Personhood Credentials to anonymous on-chain Soul Accounts. Rather than introducing a new primitive, ZK-AMS composes zero-knowledge credential validation, permissionless batch submission, recursive proof aggregation, and anonymous post-admission account provisioning into one end-to-end workflow. Its key design feature is a confidential batching pipeline in which admission instances of a common relation are folded off-chain under multi-key homomorphic encryption, allowing an untrusted batch submitter to coordinate aggregation without direct access to individual user witnesses during batching; the confidentiality scope is characterized explicitly in the security analysis. The resulting batch is settled on-chain with constant verification cost per batch rather than per admitted user. We implement ZK-AMS on an Ethereum testbed and evaluate admission throughput, end-to-end latency, gas consumption, and parameter trade-offs. Results show stable batch-verification gas across evaluated batch sizes, substantially lower amortized on-chain cost than the non-recursive baseline, and practical cost-latency trade-offs for high-concurrency onboarding in Web 3.0 platforms.
Disha Pardeshi, Sujata Sathe, Viha Bakshi, Ananya Mary Sebastian
AbstractThe growing need for secure and transparent electoral systems highlights the challenges faced by Non-Resident Indian (NRI) voters. Current rules requiring physical presence at polling stations limit participation, despite rising registrations. In our proposed blockchain-based voting framework, votes are transmitted through a secure virtual private network (VPN) and authenticated at the Election Commission of India (ECI) gateway node. After authentication, the votes are verified across multiple blockchain nodes using a consensus mechanism. Once validation is completed, the votes are permanently recorded in the distributed ledger, ensuring that they cannot be altered or removed. Smart contracts are employed to automate the vote-counting process, reducing manual intervention and minimizing the possibility of human error. The final election results are then made available through the ECI dashboard, enabling transparency and easy verification by authorized stakeholders.The proposed framework aims to improve accessibility for Non-Resident Indian (NRI) voters by enabling secure remote participation while preserving voter anonymity. By strengthening trust in the electoral system and encouraging wider participation, the solution supports improved electoral integrity. Overall, the integration of blockchain technology into the voting process contributes toward building a more transparent, secure, and inclusive democratic system in India.Keywords: Blockchain, NRI Voting, Distributed Ledger, Electoral Integrity, Consensus Mechanism, Immutability, Voter Anonymity.
This paper reviews 40 studies on blockchain-based e-voting proposals, specifically focusing on authentication and related trade-offs. A data-based examination of the evidence showed that password-based mechanisms, although popular, detected only 85% of the attacks. In contrast, Zero-Knowledge Proofs (ZKPs) have a detection rate of 99% but only a completion rate of 72% for usability, implying that security and usability are strongly inversely correlated (r=-0.67). For instance, hybrid approaches such as ZKPs with biometrics or Decentralized Identifiers (DIDs) with multi-factor authentication are considered secure (96%-99%) but not very user-friendly (80%-85%). Homomorphic encryption and other technologies have been cited as privacy aids in the literature. In addition, technical design alone cannot overcome the deep-seated sociopolitical challenges of enduring digital divides and citizen mistrust, which are slow to change within large populations, or regulatory dissonance between local and national systems, as illustrated in the cases of Estonia's i-Voting and an aborted Swiss pilot. "The trade-off between security, privacy, usability, and cost is always fluid. More integrated and effective interdisciplinarity is needed to ensure that important issues for social and political life, such as democratic legitimacy, are adequately addressed in post-quantum cryptography and artificial intelligence research. Planning prophylactic measures is necessary in the context of emerging threats from quantum computing and AI-produced deepfakes. While there are alternatives to post-quantum cryptographic ciphers, these incur computational overhead. Therefore, making e-voting secure will rely not only on new technology but also on understanding the social and political effects of that technology, being aware of how it might be put into practice, and focusing on a design that meets the needs of all voters.
Oscar Revelo Sánchez, Alexander Barón Salazar, Manuel Bolaños González
This systematic review examines recent advances in blockchain-based electronic voting systems, motivated by the need for more transparent, secure, and verifiable electoral processes. The rapid growth of research between 2022 and 2025 highlights blockchain as a promising foundation for addressing long-standing challenges of integrity, anonymity, and trust in digital elections, particularly in academic contexts where pilot deployments are more feasible. The review followed PRISMA 2020 guidelines and applied the evidence-based methodology proposed by Kitchenham & Charters. Searches were conducted in six major databases, yielding 861 records; after removing duplicates and applying eligibility criteria, 338 studies were retained. Data were extracted using a structured template and synthesised qualitatively due to the conceptual and methodological heterogeneity of the evidence. The included studies reveal significant progress in blockchain architectures, smart contracts, and advanced cryptographic mechanisms—such as blind signatures, zero-knowledge proofs, and homomorphic encryption. Multiple authentication and verification strategies were identified; however, real-world validations remain limited and largely confined to small-scale academic pilots. Overall, blockchain-based voting systems demonstrate conceptual advantages over traditional and conventional electronic models, especially regarding transparency and auditability. Nevertheless, the field requires stronger empirical evaluation, greater scalability, and clearer regulatory alignment to support broader institutional adoption.
This study presents HoloCyberChain, an entropy-driven blockchain framework for decentralized cyber-threat intelligence with formal verification and privacy preservation. Each cyber event is encoded as a four-dimensional entropy fingerprint capturing structural, temporal, behavioral, and propagation uncertainty. A novel Shannon–β hybrid distance integrates residual-entropy geometry with β-divergence-based distributional separation, yielding a unified statistical–topological measure of threat dissimilarity. Residuals are transformed into calibrated novelty probabilities through a logistic uniqueness gate, while a proof-of-detection consensus protocol enables publicly verifiable and Byzantine-resilient acceptance of novel intelligence. Privacy is maintained using zero-knowledge entropy proofs, and accepted threats are organized into a spectral threat-intelligence graph that preserves family-level separability. Simulation experiments demonstrate reliable discrimination (ROC-AUC ≈0.81, PR-AUC ≈0.77) and stable calibration under noise and concept drift. Real-world validation using the CICIDS-2017 dataset (225 745 flows, 79 features; 97 718 benign and 128 027 DDoS flows) confirms that DDoS traffic exhibits higher Shannon–β entropy, with right-shifted density profiles, higher medians, and tighter interquartile ranges relative to benign traffic, indicating that the proposed entropy formulation preserves separability under realistic traffic imbalance. These empirical results align with theoretical guarantees and simulation findings, establishing HoloCyberChain as a reproducible, entropy-verified foundation for scalable and privacy-preserving cyber-threat intelligence sharing.
In digital security, anonymous credential systems are essential to ensure secure and private interactions. These systems have practical applications in various fields, such as online voting, healthcare, and financial services. However, due to high computational overhead and complex architecture, traditional anonymous credential systems often suffer from efficiency and scalability issues. To address these challenges, we propose an innovative approach that combines advanced cryptographic techniques such as randomized BLS aggregate signatures and optimized zero-knowledge proof usage mechanisms to achieve secure and private identity authentication with minimal overhead. We introduce HPPCS (High-Performance Privacy-Preserving Credential System), an anonymous credential framework that leverages randomizable aggregate signature technology to achieve efficiency and strong security. We conducted a security and experimental analysis of the HPPCS framework, and the results showed that HPPCS improves the efficiency of credential generation and verification while ensuring original security. This work establishes a powerful and practical framework for privacy-centric identity authentication systems.
For the past three decades, the architecture of the internet has rested on two primary pillars - communication on the World Wide Web and Value such as Bitcoin/Distributed ledgers. However, a third critical pillar, Private Coordination has remained dependent on centralised intermediaries, effectively creating a surveillance architecture by default. This paper introduces the 'Stateless Pattern', a novel network topology that replaces the traditional 'Fortress' security model (database-centric) with a 'Mist' model (ephemeral relays). By utilising client-side cryptography and self-destructing server instances, we demonstrate a protocol where the server acts as a blind medium rather than a custodian of state. We present empirical data from a live deployment (https://signingroom.io), analysing over 1,900 requests and cache-hit ratios to validate the system's 'Zero-Knowledge' properties and institutional utility. The findings suggest that digital privacy can be commoditised as a utility, technically enforcing specific articles of the universal declaration of human rights not through policy, but through physics.
ABSTRACT Over the years, numerous efforts have been undertaken to accurately forecast traffic conditions and thereby preventing additional congestion. However, existing crowd management techniques focus on recognizing and counting the crowd while leaving the security of crowd information. A typical crowd management system is centralized and faces challenges, such as contributor selection reliability, fair payment evaluation, privacy concerns and high deployment costs. This study investigates security concerns in crowd management and evaluates the potential of blockchain technology to improve crowd management security. Combining the power of blockchain (decentralization and security) and smart contracts, this work proposes a secure crowd management architecture named . The framework operates on blockchain, utilizes cryptographic algorithms, and incorporates reputation management along with credit distribution through smart contracts. effectively safeguards crowd data while its revenue structure entices users to actively contribute to the system. has been simulated on GoQuorum's Ethereum private blockchain, using elliptic curve signatures for secure and efficient processing. Its performance was tested with RAFT, PoA and IBFT consensus mechanisms where RAFT led in throughput, IBFT lagged and PoA offered a middle ground. PoA stands out for balancing scalability and security, supporting network growth while preserving identity‐based validation and data integrity.
Bitcoin custody systems are constructed under conditions of full knowledge and activated under conditions of partial knowledge. The person who designs a custody arrangement understands its components, dependencies, and intended operation. The person who later encounters that system—often an executor, trustee, or heir—must interpret and operate it without access to the designer's contextual understanding. This paper defines a descriptive framework for examining Bitcoin custody systems under stress conditions at a point in time, producing reference records for later interpretation. The framework treats examination as observation rather than evaluation: it records what exists, what dependencies connect components, and how the system behaves under modeled stress scenarios. It explicitly excludes advice, recommendations, certification, and adequacy assessment. The framework introduces four modeled outcome states—survives, constrained, blocked, and indeterminate—that describe observed system behavior without normative judgment. It defines stress conditions including owner absence, cognitive unreliability, device loss, institutional delay, and coordination failure. It specifies what reference artifacts examination produces: system snapshots, scenario-bound observations, dependency maps, and assumption registries. The paper addresses how professionals—attorneys, fiduciaries, advisors—can engage with examination records without overstepping interpretive boundaries. It distinguishes what records can establish (what was described, what was modeled, what assumptions applied) from what records cannot establish (adequacy, correctness, future outcomes). The framework is offered as a reference for professional contexts where Bitcoin custody must be understood by parties other than its original designer.
Tato práce se zabývá problematikou šíření transakcí v bitcoinové peer-to-peer síti, jejich monitorováním a měřením doby potřebné na jejich propagaci pro různé kombinace parametrů bitcoinových uzlů a sítě. Cílem této bakalářské práce je pochopit principy a mechanismy používané v bitcoinovém protokolu pro šíření transakcí v síti. Na základě získaných informací je navržen a implementován simulační model, který umožňuje sběr statistických dat o procesu šíření transakcí mezi uzly. Součástí práce je také vytvořený analyzační skript, schopný identifikace uzlů, kterými byly dané transakce vytvořeny.