Blockchain Papers

Achim Struve

No abstract is available for this record.

Mohammad Badhesha, Arun Sekar Rajasekaran, Ashok Kumar Das, Azees Maria · 6 authors

Authenticated key exchange and secure handover between vehicles and roadside units (RSUs) are essential for the reliability of vehicular networks. However, many existing approaches incur high computational and communication overhead or rely on re-authentication, which limits scalability under high mobility. Moreover, conventional schemes based on classical cryptography cannot withstand quantum adversaries, while lattice-based solutions overlook the need for efficient handover and strong privacy protection. To address these limitations, a lattice-based authentication and key agreement protocol that integrates non-interactive zero-knowledge (NIZK) proofs to enable seamless and post-quantum secure handover in both intra-domain and cross-domain vehicular networks (LAKAS-N) is proposed in this work. The scheme establishes mutual key exchange between vehicles and RSUs, eliminates re-authentication within a single domain, and preserves anonymity when transitioning across domains. Security is rigorously validated through informal and formal analyses, including Scyther-based verification, which confirms resistance against classical and quantum attacks. Lastly, a comprehensive evaluation shows that LAKAS-N achieves stronger security with substantially lower computational, communication, storage, and energy costs compared to state-of-the-art protocols, demonstrating its practicality for real-world vehicular networks.

Heath Emerson

No abstract is available for this record.

Massimiliano Concas

This project is the public home of Relational Calculus, a meta‑mathematical framework that replaces the brute‑force logic of absolute‑scale computation with dimension‑less, capacity‑anchored blueprints. At its heart lies a simple but radical axiom: every system possesses an intrinsic maximum—a “North Star”—and by expressing all observations as fractions of that limit, complexity collapses, efficiency soars, and transfer across domains becomes automatic. The collection gathers the complete stack: the foundational theoretical paper, a ready‑to‑run Relational Decoder (an open‑source algorithm that probes any black‑box function and extracts its dimensionless template), and five applied case studies that prove the principle in wildly different arenas—number theory (deterministic prime pair lattices), symbolic artificial intelligence (a geometric chess engine that exhibits emergent strategy with zero domain knowledge, gaining 90%+ efficiency), high‑energy physics (scale‑invariant jet tagging that transfers zero‑shot across collision energies with +14.5% AUC), quantum chemistry (80% error reduction in cross‑molecule transfer), and precision oncology (a lightweight XGBoost that achieves 98.4% cross‑species diagnostic accuracy under a 70% hardware‑signal collapse, completely erasing batch effects). A companion paper extends the logic to large language models, proposing Relational‑CoT as a drop‑in replacement for resource‑intensive chain‑of‑thought reasoning. Every work converges on the same empirical signature: >90% reduction in computational cost, genuine zero‑shot generalization across scales and species, and the proof that Green AI is not an aspiration but an engineering reality. An integrated STEM curriculum for ages 10–14 ensures that the relational lens is taught before the continuous one, inoculating the next generation against the wasteful “math of deviation.” All code, data, and executable papers are open‑source. The project is intended not as a scholarly gesture but as an enablement instrument for the industrial shift from the Age of Fire—where more compute meant more extraction—to the Era of Relation, where measuring how full a system is replaces the endless pursuit of how much.

Okan Dardağan

This thesis presents a comprehensive predictive maintenance system and application interface that integrates deep learning and blockchain technologies in order to enhance maintenance strategies in industrial systems. Traditional predictive maintenance systems have significant issues regarding data security and decentralization. This study aims to address these limitations by leveraging blockchain technology, with a specific focus on improving the reliability and verifiability of predictive maintenance processes. In this study, an LSTM-CNN hybrid model was developed to evaluate complex patterns in both time and features, thereby enabling high-accuracy fault prediction. The proposed model is designed to perform binary classification for fault prediction in industrial equipment. During the implementation phase of the study, an open-source dataset was used to train and test the developed model. The Randomized Search method was used in the hyperparameter optimization process to increase the prediction success of the proposed model. The hybrid model was trained with 5-fold cross-validation, and class weighting and threshold value optimization methods were applied to eliminate the class imbalance problem. In the threshold optimization phase, F1-score-based methods are applied to maximize recall at three predefined minimum precision levels (0.05, 0.2, and 0.85), while identifying the most balanced trade-off between precision and recall. In the proposed system, sensor data are stored in a database (SQLite3), and cryptographic proofs generated using zero-knowledge techniques are transmitted to the Ethereum network. The Poseidon hash function is used to ensure data integrity, and the Groth16 protocol is used for Zk-Snark proof generation. This approach enables secure verification of data validity without publicly disclosing sensor data and simultaneously addresses scalability concerns. The system architecture is designed to include manager, operator, and engineer nodes, and all smart contracts are implemented using Solidity. In addition, a graphical user interface is developed using the Tkinter library in Python. The experimental results demonstrate that the proposed LSTM–CNN hybrid model produces successful outcomes in terms of fault prediction performance. According to scenario where the decision threshold is optimized based on the F1-score, the model achieves an accuracy of 0.987, an AUC value of 0.979, and an F1-score of 0.794. In future studies, the proposed system is planned to be implemented on the Ethereum mainnet instead of a test network, with a comprehensive evaluation of on-chain operational costs. However, instead of Zk-Snark proofs, which have a centralized structure, the use of Zk-Stark proofs, which are transparent and do not violate the principle of decentralization, is planned.

René Dechamps Otamendi

No abstract is available for this record.

Ion-Iulian Marinescu, Alexandra Horobet

No abstract is available for this record.

Jasper Pan, Lebathong Dong

No abstract is available for this record.

E. Nsekela, W. Deferme, N. Chacha

Rapid urbanization in Tanzania has increased municipal solid waste generation and placed growing pressure on urban waste-management systems that remain focused mainly on collection, transport, and disposal. Given the high organic fraction of municipal waste generation. This paper examines Resource recovery from municipal waste through cost-effective biogas technologies in Tanzania, focusing on policy and institutional frameworks that support or constrain decentralized municipal organic waste-to-biogas systems that use appropriate standard procedures. The findings show that Tanzania has a broad policy framework for environmental protection, renewable energy, private-sector participation, and resource recovery, but this foundation has not been well translated into practice. Key constraints include fragmented mandates, limited biogas-specific standards, weak organic waste segregation, inadequate financing mechanisms, and insufficient formal inclusion of communities and informal waste actors. The paper argues that improving decentralized biogas implementation requires converting existing policy commitments into enforceable, financed, and locally coordinated municipal resource-recovery systems

JongHyup Lee

Decentralized finance (DeFi) agents automate multi-transaction workflows such as swapping, lending, and vault management, but they also create process-level risk. A run can consist of individually valid calls while still becoming economically unsafe because an intermediate step leaves latent authority, weakens execution constraints, or accepts unverified external evidence. Existing defenses are often mismatched to this process-level risk. Off-chain preflight checks alone cannot protect against runtime deviations from the intended plan, and coarse on-chain allowlists are too weak to express the call-level intent that matters in DeFi. We present CheckpointAgent, a workflow-security architecture for checkpointed DeFi-agent execution. It composes manifest commitments, smart-account policy guards, post-state predicates, and attestation-gated advancement to constrain a run step by step and tie checkpoint advancement to verifiable evidence. Rather than judging safety only after a workflow finishes, CheckpointAgent checks whether each step remains consistent with the intended workflow and stops execution when the required conditions no longer hold. In the author-curated 27-scenario local-chain suite, the strongest evaluated setting preserves all 5 benign runs and prevents unsafe completion in all 22 adversarial runs, stopping them either through on-chain enforcement or through trusted-attestation advancement under the configured attester assumption. Under explicit trust assumptions and within the measured workflows and snapshots, checkpointed execution can materially reduce process-level risk without modifying target protocols.

Nitika Sharma, Rohan Patel, Hardikkumar Jayswal, Nandini Sherwani

No abstract is available for this record.

Rajesh Tanti, Smita Rai Agrawal, Bhupendra Meena, Sonali Pathak · 6 authors

The smart contracts facilitated by blockchains allow the decentralized and automated implementation of digital contracts, yet the current security measures in this space are mostly geared towards vulnerability detection and post-implementation functionality, which do not provide much defence against runtime attacks. The paper analyses the concept of smart contracts as a unified approach to cybersecurity, and provides a Hardened Smart Contract Model (HSCM) as a proactive and runtime security quotient model. The suggested model places policy-conscious logic, formal safety requirements, risk aversive execution, upgradability under control by governance, and unchangeable auditability directly in the design of contracts. The framework guarantees the elimination of unauthorized access, re-entrancy and logic abuse by providing runtime verification and automated response measures that avert such violations even before state transitions take place. A fair amount of experimental confirmation on an Ethereum-compatible system proves that there is a high security guarantee with tolerable load overhead, the deployed smart contracts could be hardened.

Yulun Miao

No abstract is available for this record.

Junjie Zhou, Xiangguo Zhao, Xin Yao, Xin Bi · 5 authors

No abstract is available for this record.

Ahmad Awwad Albnian, Mosab Fawzi Ahmed Alhafnawi, Khaled Bakhit Al-Dajjah

No abstract is available for this record.

Dona Budi Kharisma, Ifan Arsyad

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Morena Barboni, Filippo Lampa, Andrea Morichetta, Andrea Polini

No abstract is available for this record.

Svetlana Marković, Radovan Vladisavljević, Marko Marković

Smart contracts are one of the most prevalent and important blockchain-based technologies in the field of financial security, as the automatic execution of predefined rules provides additional efficiency, lowers costs and minimizes the involvement of intermediaries. This research will examine the use of smart contracts for process automation, risk reduction and organizational restructuring in the financial sector. In particular, the interaction between centralized and decentralized financial systems, the technology behind the implementation of blockchain and security issues associated with the use of smart contracts will be considered. At the same time, escrows will be presented as an example of the practical use of smart contracts for financial operations. The results of this analysis will show that smart contracts can be used as a means to increase the reliability of financial operations; however, their widespread use depends on proper regulation, security assessment and integration with the existing financial infrastructure.

Abdelhak Kaddari, Tarik Chanyour

No abstract is available for this record.

S. Gayathri, Mangaiyarkarasi T

No abstract is available for this record.

Poulami Mishra, Rituparna Bhattacharya

No abstract is available for this record.

Abhinav Dubey, Krishan, Renu Mishra, Ramneet

No abstract is available for this record.

Xiaofei Luo, Junhao Wu, Bo Xie, Jian Zheng · 6 authors

No abstract is available for this record.

Colin Winter

No abstract is available for this record.