Blockchain Papers

Jolhfred Alania-Chalan, Ivar Rodrigo Farfán-Muñoz, Angel F. Navarro-Raymundo, Jorge Nolasco-Valenzuela · 8 authors

No abstract is available for this record.

Mohit Tiwari

SARMF-Bench is a structured and reproducible benchmark dataset for smart contract vulnerability analysis. It consists of five minimal Solidity contracts representing canonical vulnerability classes: • Reentrancy • Arithmetic Overflow Behavior • Access Control Weakness • Unchecked External Call • Denial-of-Service Pattern Each contract is paired with machine-readable static analysis outputs generated using Slither v0.11.5. The dataset is designed to support controlled benchmarking experiments for: - Static analyzers - Symbolic execution engines - Fuzzers - AI-assisted smart contract security tools Related assets: GitHub repository: https://github.com/profmohit-edu/sarmf-framework Zenodo software DOI: https://doi.org/10.5281/zenodo.18754015 Reproducibility protocol: https://doi.org/10.17504/protocols.io.bp216eyxdgqe/v1 Mendeley dataset DOI (pending moderation): https://doi.org/10.17632/kd3vcpnn9v.1 HAL record: https://hal.science

P PAVITRA, GURURAJ MURTGUDDE

With the increased usage of Bitcoin and othercryptocurrencies, there is a need to address issues related tofraud detection in cryptocurrency systems. Such issuesinclude double-spending, money laundering, and accounthacking, among others, that Bitcoin needs to guard against.However, since Bitcoin is decentralised and transactions arenot reversible, the use of central-system approaches cannotbe applied; thus, an alternative approach must be adopted.The presented project offers a viable method of usingmachine learning for Bitcoin fraud detection. The frauddetection method is real-time, using ensemble stacking,which entails combining multiple machine learning modelsto enhance prediction capabilities. Algorithms to be usedinclude Random Forest, Gradient Boosting (XGBoost,LightGBM), Support Vector Machine (SVM), LogisticRegression, and Isolation Forest. In other words, multiplealgorithms will be used to examine Bitcoin transaction data,such as amounts transacted, transaction frequency, andtransaction patterns. Ensemble stacking allows the use of thestrengths of multiple algorithms, while the real-time functionenhances the applicability of the approach. Scalability isanother critical consideration, especially considering thenumber of Bitcoin users. This is why the use of a Flaskapplication server will be necessary for user datasubmissions, visualisation, and sending fraud notifications.Evaluation will be based on accuracy, precision, recall, andF1-score.Conclusion – The proposed solution appears quiteplausible as the fraud detection through machine learning isefficient, while scalability is one of the main features of theapproach.

Jacob Smagula

I argue that Bitcoin is the latest expression of the recurring American conflict over who controls the terms of money and property, and that the political coalition formed around Bitcoin shares the same characteristics as earlier coalitions formed around this struggle. I review three historical cases that each produced a coalition opposing the existing monetary order: the Bank War of the 1830s, the Free Silver movement of the 1890s, and the populist backlash against the Federal Reserve during the 1979 Farm Crisis and the 2008 Great Recession. I find that Bitcoin’s architecture, which allows for self-custody, permissionless access, and an algorithmically fixed supply, is an answer to the old conflict. Four qualities are found across each of the historical coalitions: relative economic insecurity, distrust of institutional management, ordinary Americans confronting the wealthy and powerful, and heterogeneous political affiliations. Using data from the Nakamoto Project's 2025 Bitcoin Adoption and Sentiment Study, I find each of the four qualities present in the contemporary Bitcoin coalition. I conclude that the Bitcoin coalition today resembles the pre-Bryan silver coalition of the 1880s rather than the consolidated movement of 1896, and its outcome may depend in part on whether it produces a unifying political champion.

Pedro Cosme

No abstract is available for this record.

Ping Cao, Wei Wang, Yiliang Liu, Zou Su

Distributed spectrum allocation for large-scale UAV swarm remains a challenging issue, due to spectrum allocation collisions and the high communication overhead required to reach consensus. To address these challenges, we propose a lightweight consensus protocol for distributed collision-free spectrum allocation (LCCFSA), where UAV nodes in the swarm form a blockchain and spectrum allocation consensus is reached on the chain. Specifically, a fast low-complexity allocation scheme is developed for each UAV based on an interference graph, where each UAV adaptively adjusts its occupancy area to avoid mutual interference. To further reduce the consensus overhead, we design a lightweight consensus protocol with a transaction-based blockchain ledger and provide a formal security analysis of the proposed protocol. A prototype is built to validate the feasibility of the proposed scheme. Simulation results show that the average consensus latency can be reduced by more than 20% in scenarios with 100 consensus nodes.

Haosu Cheng, Guanquan Shi, Kangkang Zhang, Wenyu Zhang

No abstract is available for this record.

L Blanco, Cristian J. Vaca-Rubio, Jorge Baranda, Farhana Javed · 40 authors

UNITY-6G introduces a AI-natively framework that unifies terrestrial (TN), non-terrestrial (NTN), and non-public networks (NPN), treating connectivity, computing, and intelligence as interdependent resources. The architecture utilizes an Inter-Domain Management Orchestrator (IDMO) based on Service-Based Management Architecture (SBMA) principles to coordinate services across heterogeneous domains. A core pillar of the framework is its AI-native design through autonomous agentic AI workflows following a standardized MS–AE–DE–ACT (Monitoring, Analytics, Decision, and Actuation) logical patterns. To enhance resource efficiency and sustainability, the architecture integrates Digital Twins (DT) for proactive system modeling and semantic communications to prioritize task-relevant information transfer. Security is addressed through a Trust Architecture leveraging Distributed Ledger Technology (DLT) for cross-domain auditability. The framework's utility is validated through proof-of-concepts targeting sustainable disaster handling, immersive XR/holographic communications, and time-sensitive services for Industry 4.0. The presented advances establish a foundation for the continuous development of high-performance, autonomous 6G systems.

Rajesh Bose, Shrabani Sutradhar, Arfat Ahmad Khan, Sandip Roy · 7 authors

ABSTRACT The promise of blockchain applications is transformative in terms of certificate verification and managing digital identities in the various fields, such as education, healthcare and land records. Nevertheless, current blockchain‐based certificate solutions have serious shortcomings: most are based on simple cryptography protection with no privacy‐preserving systems, have low throughput (16.67 TPS in typical Ethereum‐based systems), have unpredictable response times under varying loads, are not standardised across industries and are expensive to operate due to gas fees. Besides, the current implementations are mostly either theoretical or without performance tests in practice. This paper fills these gaps by suggesting a Plonk‐based system that incorporates zero‐knowledge proofs, digital signatures and trusted identity verification to improve the efficiency, security, and privacy of the verifiable credential digital identity verification and management systems (VC DIVMS). It was implemented at JIS University, India, with 50 transactions per minute (an improvement of 200% over Ethereum), an error rate of 244–1277ms in response times under load conditions (24‐33 faster than Ethereum) and high‐level privacy through ZKP. Contrary to currently used models that are sector‐specific, the offered Plonk framework offers a single, scalable, privacy‐focused model that can be applied in areas of education, healthcare, or credit verification. Intense testing ensured both resilience, scalability and compatibility with a demanding environment, making Plonk a strong and secure substitute to decentralised identity verification and credential management that is resistant to tampering.

Henry Zhu

This thesis advances privacy-preserving solutions essential for addressing contemporary technological challenges in smart cities, decentralized systems, and algorithmic decision-making processes. Firstly, we introduce a hybrid sensing framework integrating Internet of Things (IoT) sensors and crowdsensing techniques to overcome limitations inherent in traditional methods. The hybrid sensing model incentivizes voluntary user contributions to complement fixed-location IoT sensors, ensuring reliable and comprehensive data collection while maintaining user anonymity through a privacy-preserving protocol. We implement this model in a smart parking application, demonstrating significant improvements in data accuracy and user engagement. Secondly, we propose a decentralized anonymous crowdsourcing system leveraging blockchain technology, which removes reliance on centralized intermediaries, thereby enhancing transparency and mitigating biases. Our system integrates anonymous payments using the Zerocoin protocol framework, eliminating the need for worker identity registration and trusted setups, thus fostering genuinely anonymous participation. Empirical analyses confirm that our approach maintains practical efficiency in transaction verification and moderate blockchain gas costs. Lastly, we tackle fairness and transparency in algorithmic decision-making processes, addressing public concerns regarding inherent biases and opaque computational practices. We develop a privacy-preserving, publicly verifiable framework that combines succinct zero-knowledge proofs with blockchain infrastructure, allowing independent verification of algorithmic fairness without exposing sensitive inputs or decision-making algorithms. Our concrete instantiation employs a restricted KZG polynomial commitment scheme alongside the Sonic zk-SNARK protocol, demonstrating small proof sizes, efficient verification, and practical deployment feasibility. Collectively, this thesis contributes significantly to the field by providing robust, scalable, and privacy-conscious technologies tailored for contemporary smart city applications and decentralized computational ecosystems.

Rubén Armañanzas

No abstract is available for this record.

Mohammad Rafiqul Islam, Silicon-Saffat TRISDUCTION

The P versus NP problem, formalized by Cook (1971) and designated a Clay Millennium Prize Problem in 2000, asks whether every computational problem whose solution can be verified in polynomial time can also be solved in polynomial time. For fifty-five years the problem has resisted all single-axis formal resolution attempts. Three independently proven barrier results have demonstrated that all currently known classes of mathematical proof technique are structurally incapable of settling the question within the formal axis alone. This paper presents a unified geometric determination of both P = NP and P ≠ NP using the Trisduction ENGINE, an epistemic certification architecture operating across three orthogonal warrant-vectors: Formal (V_F), Empirical (V_E), and Phenomenological (V_P). Version 10.0 introduces two architectural upgrades over prior versions: Rule 9 Axiomatic Quarantine, which formally removes the Turing Machine abstraction from the framework's admissible baseline and replaces it with the Tri-Layer Plenum topology; and the Meta-Epistemic Hierarchy (Geometry > Mathematics > Logic), which resolves the recurring drift pattern in which formal demands were treated as epistemically superior to geometric physical measurement. The two audits are presented as a single master document to make the asymmetry between the claims structurally transparent: P = NP carries zero positive warrant across all three axes and is stopped at Gate 2; P ≠ NP passes all twelve gates with three fully independent, orthogonal warrant-vectors. The determination is explicitly non-deductive. It does not constitute a traditional mathematical proof and does not satisfy the Clay Mathematics Institute's criteria. GOL [⟀] is defined as the strongest achievable non-deductive epistemic warrant: the geometric fact that three orthogonal planes exhaust all degrees of freedom in the epistemic space, leaving no room for the alternative claim to occupy. The paper's central phenomenological contribution is the dual anchoring of V_P through the Zero-Knowledge Proof conviction gap and the Frame-Independent Observer actualization boundary. Both sources survive the Linguistic Isolation Test against V_F and V_E vocabulary, the Deletion Test, and four rounds of post-certification stress-testing documented in the appendices. The Convergence Dissolution Test finds irreducible residue in all three vectors under the strongest single-factor account. The Living Verifiable Proof — the Engine's simultaneous perfect verification capacity and structurally total generative incapacity at the Isometric Plenum boundary — provides continuously falsifiable phenomenological evidence that checking does not entail finding.

Cheng Chen, Gangqiang Yang, Hongchao Zhou, Hailiang Xiong · 5 authors

Zero-Knowledge Proofs (ZKPs), particularly zk- SNARKs, are extensively employed in privacy-sensitive applications, but proof generation in such protocols imposes significant computational overhead. A major performance bottleneck is Multi-Scalar Multiplication (MSM), a highly compute-intensive operation on elliptic curves. While existing work focuses on specialized curves such as BLS12-377, which support more efficient elliptic curve arithmetic, there is limited exploration of MSM on general-purpose curves such as BLS12-381, which lack such optimizations and make parallelization more difficult. It faces the following challenges: imbalanced resource usage in modular multipliers, performance disparity between elliptic curve operations, and under-utilization of point addition unit in scheduling. To tackle these challenges, we propose FlexMSM, a flexible and scalable FPGA-based accelerator to accelerate MSM. FlexMSM innovates three techniques. First, we present a reconfigurable modular multiplier based on our proposed Hybrid-Weight Modular Multiplication algorithm, which strikes a balance between hardware cost and the number of MSM cores deployed on a single FPGA. Second, we propose a unified point addition scheme and design a fully pipelined point addition (PADD) unit. This design eliminates timing mismatch between pipeline stages and shortens the critical path. Third, we introduce dual-decoupled scheduling strategy for the bucket aggregation phase in Pippenger algorithm, which reduces pipeline stalls and improves the utilization of the PADD unit in MSM. To the best of our knowledge, FlexMSM is the first work to support up to double MSM cores for BLS12-381 curve on a single Xilinx UltraScale+ VU13P FPGA, leading to remarkable performance enhancements compared to existing works for input sizes from 218to 226. For the degree of 220, FlexMSM with two cores on a single FPGA achieves speedups of 19.29× over Hardcaml, 8.57× over if-ZKP, 2.14× over OPTIMSM on FPGA, 6.57× over ASIC-based work PipeZK, and 9.29× over GPU-based work GZKP.

Shuhui Zhang, Xiaochen Wang, Lianhai Wang, Shujiang Xu · 6 authors

No abstract is available for this record.

Hang Liu, Yang Ming, Chenhao Wang, Yi Zhao

Vehicle platoon, an increasingly significant technology in vehicular ad hoc networks (VANETs), effectively reduces energy consumption and environmental pollution, mitigates traffic congestion, and enhances road capacity and traffic safety. Collaborative communication between platoons is available to promote the reliability of data dissemination, ameliorate driving strategies, and further strengthen traffic efficiency. Nevertheless, existing efforts for secure multi-platoon data dissemination still face the following issues: (i) lack of a direct authorization strategy for platoons working on different systems; (ii) no effective mechanism to protect vehicle privacy during platoon communications; (iii) absence of a practical verification approach for cross-system ciphertext transformation. This paper builds a privacy-preserving and verifiable cross-system authorization (PVCA) scheme to mitigate the above issues. Specifically, we first put forth the optimized anonymous identity-based broadcast encryption (IBBE) and policy-hiding attribute-based encryption (ABE) protocols to adapt platoon communications while protecting identity and attribute privacy. After that, the authorized token bridging the proposed protocols is designed to enable ciphertexts of IBBE format to be transformed into new ciphertexts of ABE format, enabling flexible authorization. Furthermore, inspired by the Fujisaki-Okamoto transformation, we devise an efficient zero knowledge proof of knowledge protocol, making our PVCA achieve verifiability and fairness. Rigorous security proof and analysis demonstrate that our PVCA is not only secure against chosen plaintext attacks and collusion attacks, but also satisfies the necessary security requirements. We implement a prototype of PVCA (on a desktop computer and Raspberry Pi) and provide a simulation utilizing NS-2 to validate its feasibility for platoon communications in VANETs. The results indicate that, compared to the state-of-the-art ciphertext transformation solutions, PVCA reduces the running time for original ciphertext generation, transformation, and decryption by at least 91.57%, 49.87%, and 50%, respectively, while compressing the original ciphertext and authorization token sizes by over 78.07% and 15.20%.

Austin Harshberger

No abstract is available for this record.

Meng-Lin Huang, Xiaodan Zhang, Wei Mi, Huimei Liao · 5 authors

No abstract is available for this record.

Zhang Dayong, Nur Haliza Abdul Wahab, Juniardi Fadila, Arafat Al-Dhaqm · 8 authors

No abstract is available for this record.

Md. Hussain Ansari

Democratic governance depends fundamentally on the integrity of electoral processes, as public trust in democratic institutions is only as strong as the systems that underpin them. Conventional voting mechanisms whether paper-based or early digital systems face growing scrutiny regarding transparency, auditability, and resistance to manipulation, with high-profile electoral controversies in recent years intensifying calls for more robust and verifiable alternatives. This paper proposes and evaluates a blockchain-powered electronic voting (e-voting) system designed to overcome these longstanding limitations by leveraging the core properties of distributed ledger technology: immutability, decentralization, and cryptographic verifiability. The proposed architecture integrates Ethereum-based smart contracts for automated ballot management, zero-knowledge proof (ZKP) protocols for voter privacy, and a permissioned blockchain layer for regulatory compliance. Together, these components form a cohesive framework that seeks to balance openness with accountability. A comparative evaluation against existing solutions demonstrates measurable improvements in security, voter anonymity, and system auditability. Scalability constraints, regulatory considerations, and real-world deployment challenges are also examined with candor, acknowledging that no technological solution is without friction. The analysis concludes that blockchain-based e-voting represents a technically viable and socially consequential advancement in democratic infrastructure one with the potential to restore and reinforce public confidence in electoral outcomes worldwide.

Renu Mishra, Mamta Narwaria, Murari Kumar Singh, Vimal Dwivedi · 6 authors

No abstract is available for this record.

Timothy D. Williams

No abstract is available for this record.

Xiao Wei

With the rapid increase of terminal devices in the Internet of Things (IoT), it has become a significant challenge to achieve real-time and privacy-preserving data aggregation. To address this challenge, edge computing has emerged as an effective paradigm to reduce latency, where a privacy-preserving data aggregation scheme is exploited to preserve data privacy. However, most existing privacy-preserving data aggregation schemes are limited by fixed data dimensions, low scalability, and high communication or computational overhead. To address these shortcomings, this paper proposes a multidimensional privacy-preserving data aggregation scheme that supports flexible dimension expansion and privacy protection in edge computing systems. The scheme integrates the Chinese Remainder Theorem (CRT) with an elastic modulus set to efficiently pack multidimensional data. This design enables terminal devices to add new data dimensions without interrupting current operations or modifying historical data. Furthermore, by exploiting Bulletproofs-based zero-knowledge proofs and Bellare-Neven (BN) signatures with half-aggregation, the proposed scheme enables lightweight and scalable batch verification of data integrity and authenticity. These mechanisms effectively reduce the verification workload and communication bandwidth in large-scale deployments. In addition, an optimized Paillier homomorphic encryption algorithm is used to enable efficient aggregation of encrypted multidimensional data. Experimental results and theoretical analysis show that the proposed scheme significantly reduces computational and communication costs compared with existing methods.

Yihang Wu

No abstract is available for this record.

Hu Liu, Jie Li, Meng Zhao, Haibin Zheng · 6 authors

No abstract is available for this record.