Blockchain Papers

Mohammad Javad Jannati, Abolfazl Iraninasab, Mehrshad Eskandarpour

No abstract is available for this record.

Jia-Ying Lyu

Aim: This study examines whether and how the disposition effect shapes Ethereum investors’ selling decisions. It asks whether investors are more likely to realize gains than losses, whether this asymmetry strengthens during high-volatility periods, and whether it weakens around major protocol upgrades, including the Merge, Shapella, and Dencun. Methodology: The study builds a high-frequency address-day panel for 2020–2024 using public on-chain data and labeled centralized-exchange deposit clusters as conservative proxies for sell decisions. Rolling cost bases are reconstructed under FIFO and value-weighted rules, and unrealized gains and losses are linked to realized sales through discrete-time logit and Cox hazard models. The design also includes event windows and robustness checks. Findings: The framework is designed to identify three mechanisms: asymmetric realization of gains over losses, stronger gain realization under high volatility, and attenuation around major protocol-upgrade events. Implications: The study offers a transparent design for analyzing behavioral bias in crypto-asset markets with verifiable blockchain data. It is relevant to exchanges, regulators, and market designers concerned with investor behavior and risk management. Originality/value: The article extends behavioral finance to Ethereum by using public ledger data rather than brokerage records and by integrating behavioral bias, volatility regimes, and protocol events in one framework.

Alex J. Sinclair, Yuhan Zhang, Michael P. O’Connor, Li Wei

No abstract is available for this record.

Arthur Meunier

The advent of sufficiently powerful quantum computers poses an existential cryptographic threat to elliptic-curve-based public key infrastructure, upon which major blockchain networks depend for transaction security and identity. This paper conducts a rigorous comparative analysis of quantum risk exposure for Bitcoin and Ethereum, examining the structural, governance, and economic dimensions of post-quantum cryptographic (PQC) transition for each protocol. We analyze the mathematical incompatibility of leading NIST standardized PQC signature schemes with current blockchain scalability constraints, with particular attention to signature size inflation (30-100× current schemes), the loss of algebraic linearity preventing signature aggregation, and the resulting implications for block space, fee markets, node economics, and validator infrastructure. We subsequently contrast Ethereum's upgrade-oriented, stake-weighted governance model and its modular cryptographic architecture against Bitcoin's deliberately ossified, consensus-driven governance structure. Our findings indicate that while Ethereum possesses the structural and institutional prerequisites for a credible, phased transition to post-quantum cryptography, Bitcoin's governance model and architectural constraints render such a transition highly contested and potentially irresolvable without chain fragmentation. We conclude that Bitcoin's structural limitations, compounded by deep ideological fractures and the irreversible nature of PQC deployment, place it at significant risk of prolonged governance stagnation or chain split, undermining its position as a reliable store of value and 'digital gold' standard in the medium term.

FELIX REGAN JAYA

Penelitian ini bertujuan untuk menganalisis dan membandingkan kinerja investasi Bitcoin, Ethereum, emas, dan Indeks LQ45 selama periode 2020-2024 dilihat dari sisi return, risiko, dan rasio Sharpe. Data yang digunakan merupakan harga penutupan bulanan yang diperoleh dari situs resmi investing.com. Metode analisis yang digunakan yaitu uji ANOVA dilanjutkan dengan uji lanjut post-hoc Tamhane’s T2 dan Tukey HSD. Hasil penelitian menunjukkan bahwa secara agregat terdapat perbedaan return antar instrumen, namun perbedaan tersebut tidak signifikan secara statistik pada uji post-hoc. Risiko merupakan pembeda utama dalam perbandingan keempat instrumen, dengan Ethereum sebagai aset paling berisiko, disusul oleh Bitcoin, Indeks LQ45, dan emas sebagai aset paling stabil. Pada rasio Sharpe, hanya terdapat perbedaan antara aset Bitcoin dan Ethereum dengan Indeks LQ45, di mana Bitcoin dan Ethereum menunjukkan efisiensi kinerja lebih baik dalam menghasilkan return terhadap risiko dibanding Indeks LQ45.

Kyle Trinh

This thesis investigates how GossipSub configuration choices influence data dissemination for a Data-Availability Sampling (DAS) workload under strict consensus time bounds. Using a configurable PeerSim-based simulator, we model a FullDAS-like setting in which a block producer erasure-codes a blob into a 2D extended matrix of share segments, parti- tions row/column segments into topics (custody-style sharding), and executes a two-phase workflow: seeding, where share segments are disseminated over topic meshes, and sampling, where validators must retrieve uniformly random share segments within a T_DAS = 4 s deadline. We systematically vary topic granularity (TOPICS), segmentation (segment amount, SA), replication (K-copies), bandwidth caps, and omission fault rate α, and measure phase success rates, completion-time distributions (with emphasis on tail latency), bandwidth consumption, and duplication overhead. The results show that segmentation and replication dominate performance and overhead: increasing SA from coarse to moderate values reduces duplication with diminishing returns beyond SA ≈ 1-16, while larger K increases redundancy and overhead and mainly provide a robustness margin under adverse conditions. Seeding completes quickly and remains resilient for SA≥ 4 even at high omission, whereas sampling is tail-latency dominated and degrades more sharply as α increases, leading to widespread deadline misses near α = 0.5. Based on these findings, we adopt TOPICS= 256, SA= 8, K = 4, and a conservative per-node bandwidth cap of 60 Mbit/s for faulted multi-slot experiments to isolate GossipSub dynamics from bandwidth saturation.

haojia hong, Duan Jia, Wei Ren, Xi Liu · 5 authors

Proxy contracts support logic upgradeability and deployment reuse in decentralized application (DApp). However, the use of proxy mechanisms also introduces new security risks. Although prior work has explored the security of proxy contracts, most prior approaches either depend on source code or fail to handle complex proxy storage layouts at the bytecode level, reducing their applicability to real-world closed-source contracts. In this paper, we propose ProxyLens, a bytecode-level vulnerability detection framework tailored for Ethereum proxy contracts. Without requiring source code, ProxyLens integrates storage structure modeling, proxy pattern recognition, and vulnerability detection. It features (1) a slot recovery mechanism based on symbolic execution and taint analysis for precise variable layout inference, (2) a proxy identification and delegate slot tracing module for accurate proxy architecture recognition, and (3) a semantic-driven vulnerability detection engine that works independently of function names. Experiments show that ProxyLens significantly outperforms existing tools in storage slot recovery (F1 = 96.4%), variable type inference (accuracy = 63.0%), proxy pattern recognition (accuracy > 90% across multiple patterns), and vulnerability detection (e.g., function selector collision F1 = 98.77%, storage collision F1 = 79.50%). As a supplementary contribution, we have publicly released the prototype of ProxyLens.

Muhammad Faruq, Rahmad Abdillah, Nazruddin Safaat H., Pizaini

Smart contract vulnerabilities, particularly reentrancy, have caused hundreds of millions of dollars in losses across the Ethereum ecosystem. While static analysis tools dominate current auditing practice, empirical evaluations have consistently demonstrated their high false negative and false positive rates for reentrancy detection. Dynamic analysis, exemplified by property-based fuzzing with Echidna, offers an alternative by evaluating contracts through actual execution. However, systematic empirical evaluation of dynamic tools under controlled ground-truth conditions remains limited. This study adapts the bug injection methodology, previously applied only to static analysis evaluation, to assess Echidna's effectiveness in detecting reentrancy. A dataset of 50 Solidity contracts was instrumented with oracle properties and injected with two reentrancy variants, single-function and cross-function, producing 100 ground-truth contract variants. Three fuzzing configurations of increasing intensity were evaluated across three metrics: detection rate, activation rate, and average detection time. Results show that Echidna achieved 100% activation but detected only 20% to 42% of injected bugs depending on the configuration and variant. Nearly all detections occurred within the first 25 seconds of each campaign, with no benefit from extended timeouts. These findings reveal a fundamental gap between bug reachability and exploitability confirmation under standard fuzzing conditions.

Jun Young Byun, Yosep Na, Daehyun Kim, Hyun Ho Jeon · 6 authors

No abstract is available for this record.

Alicia Amores, Gabriel M. Ramírez V., Fernanda Gutiérrez-Gutiérrez, Jaime Díaz-Arancibia · 5 authors

No abstract is available for this record.

Aparna Singh, Surbhi Sharma, Surabhi Solanki, Mamta Narwaria

Biometric authentication provides high convenience with the drawback of privacy leakage, replay attacks, and centralized control over biometric templates. This paper introduces an Ethereum-based decentralized biometric authentication framework that uses Elliptic Curve Digital Signature Algorithm (ECDSA), InterPlanetary File System (IPFS) storage, and an on-chain challenge–response protocol. In the proposed model, encrypted biometric templates are stored of-chain in IPFS, whereas their content identifiers (CIDs) are registered in Ethereum smart contracts. Every authentication attempt necessitates a new on-chain nonce and an ECDSA signature of the concatenation of the CID and the nonce, authenticated through Ethereum’s built-in method, ecrecover. The design supports explicit replay protection, revocation, and public auditability. Deployment of the prototype on Ganache and MetaMask reveals that the scheme provides secure, transparent, and tamper-proof authentication with minimal gas consumption on FVC2004 datasets and reasonable storage usage on Ethereum.

Robiah Arifin, Wan Azelee Wan Abu Bakar, Mustafa Man, Mohamad Afendee Mohamed · 5 authors

The issue of fake certificates has been widely identified, and their prevalence has increased significantly in recent years. This growing trend has become a global concern due to its adverse impact on educational standards. A key factor contributing to the problem is the continued reliance on manual processes for issuing and verifying certificates. To address these challenges, this study proposes the use of an authority round (AuRa) consensus algorithm for managing certificate data on the Ethereum blockchain. AuRa, a member of the proof of authority (PoA) family, facilitates consensus among nodes distributed across multiple servers and networks. This mechanism plays a vital role in preserving the integrity and decentralization of the blockchain while ensuring the security of transactional data. Furthermore, the study investigates how AuRa enables efficient certificate data transactions within a private Ethereum environment. It also evaluates the algorithm's performance in terms of transaction speed per second (TPS) and throughput per second (TGS), demonstrating its effectiveness for managing certificate transactions on a blockchain network. Then the TPS and TGS results substantiate the suitability of AuRa for digital certificate generation, evidenced by its stable and efficient performance within a controlled private server environment.

Gopal Ojha

The Ethereum Virtual Machine (EVM) is a stack-based virtual processor that executes smart contract bytecode sequentially. While this design ensures determinism and correctness, it inherently limits instruction throughput. This paper presents a feasibility study of instruction-level pipelining within the EVM interpreter architecture. By analyzing the internal execution flow of the EVM as implemented in the Go-Ethereum (geth) client, the study identifies the program counter dependency, particularly under jump instructions, as the principal control hazard preventing naïve pipelining. A two-stage pipelined execution model is proposed, separating opcode fetch and decode from execution and program counter update, with a feedback mechanism to preserve EVM semantics. The work focuses on architectural feasibility rather than performance evaluation and optimization, demonstrating that pipelining inside the EVM interpreter is conceptually possible under controlled synchronization. Limitations, design challenges, and future research directions are discussed.

Dongxu Li, Yang Ji, yr N

No abstract is available for this record.

Ye Tian, Liangliang Song, Yuanyuan Ma, Yanbin Wang · 7 authors

No abstract is available for this record.

Shuyi Miao, Wangjie Qiu, Xiaofan Tu, Yunze Li · 6 authors

With the rapid advancement of Web 3.0 technologies, public blockchain platforms are witnessing the emergence of novel services designed to enhance user privacy and anonymity. However, the powerful untraceability features inherent in these services inadvertently make them attractive tools for criminals seeking to launder illicit funds. Notably, existing de-anonymization methods face three major challenges when dealing with such transactions: highly homogenized transactional semantics, limited ability to model temporal discontinuities, and insufficient consideration of structural sparsity in account association graphs. To address these, we propose GradWATCH, designed to track anonymous accounts in Ethereum privacy-preserving services. Specifically, we first design a learnable account feature mapping module to extract informative transactional semantics from raw on-chain data. We then incorporate transaction relations into the account association graph to alleviate the adverse effects of structural sparsity. To capture temporal evolution, we further propose an edge-aware sliding-window mechanism that propagates and updates gradients at three granularities. Finally, we identify accounts controlled by the same entity by measuring their embedding distances in the learned representation space. Experimental results show that even under the conditions of unbalanced labels and sparse transactions, GradWATCH still achieves significant performance gains, with relative improvements ranging from 1.62% to 15. 22% in the MRR and from 3. 85% to 7. 31% in the F_1.

Supriya Khadka, Dhiman Goswami, Sanchari Das

Digital identity verification often forces a privacy trade-off, where users must disclose sensitive personal data to prove simple eligibility criteria. As blockchain applications integrate with regulated environments, this over-disclosure creates significant risks of data breaches and surveillance. This work proposes a general Selective Disclosure Framework built on Ethereum, designed to decouple attribute verification from identity revelation. By utilizing client-side zk-SNARKs, the framework enables users to prove specific eligibility predicates without revealing underlying identity documents. We present a case study, ZK-Compliance, which implements a functional Grant, Verify, Revoke lifecycle for age verification. Preliminary results indicate that strict compliance requirements can be satisfied with negligible client-side latency (< 200 ms) while preserving the pseudonymous nature of public blockchains.

Tomasz Mroziewicz, Robert Ślepaczuk

This study introduces a novel approach to walk-forward optimization by parameterizing the lengths of training and testing windows. We demonstrate that the performance of a trading strategy using the Exponential Moving Average (EMA) evaluated within a walk-forward procedure based on the Robust Sharpe Ratio is highly dependent on the chosen window size. We investigated the strategy on intraday Bitcoin data at six frequencies (1 minute to 60 minutes) using 81 combinations of walk-forward window lengths (1 day to 28 days) over a 19-month training period. The two best-performing parameter sets from the training data were applied to a 21-month out-of-sample testing period to ensure data independence. The strategy was only executed once during the testing period. To further validate the framework, strategy parameters estimated on Bitcoin were applied to Binance Coin and Ethereum. Our results suggest the robustness of our custom approach. In the training period for Bitcoin, all combinations of walk-forward windows outperformed a Buy-and-Hold strategy. During the testing period, the strategy performed similarly to Buy-and-Hold but with lower drawdown and a higher Information Ratio. Similar results were observed for Binance Coin and Ethereum. The real strength was demonstrated when a portfolio combining Buy-and-Hold with our strategies outperformed all individual strategies and Buy-and-Hold alone, achieving the highest overall performance and a 50 percent reduction in drawdown. A conservative fee of 0.1 percent per transaction was included in all calculations. A cost sensitivity analysis was performed as a sanity check, revealing that the strategy's break-even point was around 0.4 percent per transaction. This research highlights the importance of optimizing walk-forward window lengths and emphasizing the value of single-time out-of-sample testing for reliable strategy evaluation.

Matthew Lorig

We formulate and solve stochastic control problems that model the core yield-generating strategy of the Ethena protocol, a decentralized finance (DeFi) stablecoin that earns yield by combining a long position in staked Ethereum (stETH) with an equal-sized short position in ETH perpetual futures. The combined position is delta-neutral with respect to the ETH spot price, yet earns carry from two sources: staking rewards on the stETH leg, and funding-rate payments received from long perpetual holders when the perpetual trades at a premium to spot. A key feature of our model is that the control -- the rate of simultaneously buying stETH and shorting the perpetual -- exerts two distinct types of price impact. \textit{Permanent} impact shifts the mid-market prices of both legs, compressing the basis and permanently eroding future funding income. \textit{Temporary} impact reflects execution slippage on each leg. We study both an infinite-horizon discounted problem and a finite-horizon problem in which the protocol maximizes total wealth up to a fixed date $T$, subject to a terminal cost for liquidating any remaining position. In both cases the optimal control is obtained explicitly.

Qin Wang, Minfeng Qi, Guangsheng Yu, Shiping Chen

Non-fungible tokens (NFTs) on Ethereum currently follow a binary mobility paradigm: ERC-721 enables unrestricted transfers, whereas SBTs (ERC-5192) prohibit transfers entirely. We identify a design gap in which no standard mechanism supports bounded transferability, where ownership mobility is allowed but limited to a finite number of programmable transfers. We study counted NFT transfers and introduce ERC-7634 as a minimal realization compatible with ERC-721. The design augments each token with a transfer counter and configurable cap L, allowing ownership to evolve under a finite transfer budget. ERC-7634 defines a minimal extension interface with three lightweight functions (transferCountOf, setTransferLimit, and transferLimitOf), two events, and native-transfer hooks, requiring fewer than 60 additional lines of Solidity while preserving full backward compatibility with existing NFT infrastructure. We analyze behavioral and economic consequences of counted transfers. Our results reveal (i) a mobility premium induced by remaining transfer capacity, (ii) a protocol-level costing signal that can deter wash trading in cap-aware markets through irreversible budget consumption, (iii) bounded recursive collateralization enabled by limited ownership turnover, and (iv) associated security and gas-cost implications, including wrapper-bypass trade-offs. Evaluation on calibrated simulations shows that moderate limits (e.g., L = 10) affect fewer than 15% of tokens under representative transfer distributions, while repeated manipulation becomes unprofitable after a few cycles in a cap-aware pricing model; the additional gas overhead remains below 11% per transfer. We further position ERC-7634 within the NFT mobility design space, derive practical cap-selection guidelines, and discuss post-cap ownership outcomes including soulbound conversion, auto-burn, and provenance freeze.

Chaimae El Filali, Imad Bourian, Khalid Chougdali

Authentication is becoming essential due to the expansion of the Internet of Things (IoT) applications in smart cities, supply chain, and healthcare. In the healthcare sector, hospitals use centralized server-based systems to manage user information and patient medical records. However, this approach may lead to scalability, interoperability, security and privacy challenges. To address these issues, this paper presents a blockchain-based multi-factor authentication (MFA) framework for IoT healthcare systems. The framework uses the Ethereum blockchain and smart contracts to improve authentication security and minimize unauthorized access risk. It also uses the InterPlanetary File System (IPFS) to securely and efficiently store sensitive medical data. Performance and security are evaluated to show the effectiveness, reliability, and feasibility of the proposed system.

Saha Reno, Mohammad Jishan Ahmad Shipu, Sumaiya Hussain Tanha, Mohammad Molla Habib

ABSTRACT Securing satellite data transactions is critical as satellite communication supports global connectivity, navigation, earth observation and aviation. Sensitive inter‐satellite data requires robust protection, and aircraft‐ground station links must prevent hazards. Vulnerabilities could breach security protocols, compromising confidentiality and incurring legal consequences. This paper presents the first integration of proof‐of‐authority (PoA) consensus, ERC1155 multi‐token standard and threshold cryptography for satellite data transactions. Unlike prior blockchain‐based proposals that rely on single‐key encryption or energy‐intensive proof‐of‐work (PoW), our system (i) uses ERC1155 to batch different data types in one contract (reducing gas costs by 40%), (ii) distributes private keys via Shamir's secret sharing (k‐of‐n) to eliminate single points of failure and (iii) implements dynamic share rotation during orbital handovers (98% success). Simulations show 12.5 ms average latency, 50 messages/second throughput and 40% lower gas costs versus PoW systems (0.0006 ETH/message). Threshold cryptography increases cracking complexity to operations, while PoA, under our simulation assumptions, achieves 100% detection of man‐in‐the‐middle attacks and 0% success for reentrancy/Sybil attacks. Dynamic share recovery during orbital handovers attains 98% success, outperforming traditional methods in resilience and efficiency.

Ziwen Chen

No abstract is available for this record.

D C Saputro, Noor A Setiawan, Azkario Rizky Pratama, Avinanta Tarigan

The increasing adoption of blockchain technology in education has introduced alternative approaches to identity verification beyond centralized credential systems. This study proposes and implements a decentralized authentication mechanism for Moodle LMS using ERC-721 non-fungible tokens (NFTs) verified through MetaMask. Developed as a proof-of-concept following a design science methodology, the system links on-chain identity tokens to Moodle accounts without storing usernames or passwords. The architecture integrates Ethereum smart contracts, nonce-based digital signature verification, and Moodle’s Role-Based Access Control (RBAC) framework. Functional testing confirms that access is granted exclusively to users possessing valid ERC-721 tokens and verified wallet signatures. Replay attack simulations demonstrate effective resistance through nonce validation, while ensuring that no sensitive credential data is exposed during the authentication process, in contrast to default Moodle login mechanisms. Performance evaluation using Apache JMeter indicates stable operation under moderate loads. Although scalability and token management limitations remain, the results demonstrate the technical feasibility and enhanced security advantages of NFT-based authentication for learning management systems.