Blockchain Papers

Shuqing Cui

On August 28, 2026, Google, Microsoft, Anthropic, OpenAI, and 100 other companies signed an open letter warning of a large-scale AI attack. AI has created systemic risks in the digital world, but the physical world has no defense mechanism. This paper defines the Physical Ledger—a physical world namespace rooted in the Cui coordinate. The Physical Ledger DNS is not a copy of the domain name system; it is an object-addressing protocol for the physical world: every object (shelf position, robot, door, vehicle, starship) is assigned a unique Cui coordinate address. This paper presents a draft protocol for the Physical Ledger DNS, a catalog of 108 problems, the genesis valuation of $100,000,000, and a reward distribution scheme. It proposes the §13 security mechanism (Proof-of-Problem): a distributed firewall for the Physical Ledger DNS, powered by the 108 problems. The more solvers participate, the thicker the firewall. AI can attack digital protocols, but it cannot solve problems—because solving requires understanding the coordinate origin itself. The genesis valuation of the Cui-attribute Shell is defined as US$100,000,000, anchored at 2026-08-27. The appendix includes the Cui-coordinate naming rights and the passphrase lock (recognition of 1/7/8 for entry).

Henry Ohiani Ohize, Adeiza James Onumanyi, Lukman Adewale Ajao, Buhari Ugbede Umar · 9 authors

Despite significant advances in electronic voting technologies, voter accreditation in many electoral systems remains vulnerable to identity fraud, database tampering, equipment failure, and centralized security breaches. Existing accreditation solutions often rely on single-modal biometric authentication and centralized architectures, limiting their robustness, transparency, and public trust. This paper proposes a Blockchain-based Bimodal Voter Accreditation System (Block-BVAS), together with a practical framework for its deployment in electronic voting systems. The proposed system integrates multimodal biometric authentication using facial and fingerprint recognition with a private Ethereum blockchain and conventional cryptographic mechanisms to provide secure, tamper-resistant, and auditable voter accreditation to provide secure, decentralized, and tamper-resistant voter accreditation. A Raspberry Pi 5 serves as the embedded processing platform, demonstrating the feasibility of implementing the framework on cost-effective hardware. By combining distributed-ledger technology with encrypted biometric verification, the proposed architecture enhances the integrity, confidentiality, and immutability of election-related records while addressing limitations associated with single-factor authentication and conventional centralized record management. Experimental evaluation of the biometric authentication module performed effectively, with fingerprint recognition achieving an average authentication accuracy (AA) of 97.8% and facial recognition averaging 95.1%. The blockchain storage overhead (BSO) displayed a near-linear growth pattern relative to the number of transactions, consistent with theoretical expectations for blockchain architectures. Reliability analysis indicated system uptime exceeding 95%, with only minimal operational failures recorded during the test period. This blockchain implementation further demonstrated reliable transaction processing and secure record management, indicating the effectiveness of the proposed Block-BVAS in enhancing the security, transparency, and trustworthiness of electronic voter accreditation.

Abhishek Reddy Kankanala

The classical taxonomy of remote voting security requirements is organized into two levels: basic and counter-attack requirements. This classification has remained largely unchanged over a decade, even through scheme innovations such as verifiable re-voting, tally-hiding, and post-quantum protocols. However, this stability does not survive the new threat model of adversarial artificial intelligence (AI). A security requirement is considered promoted when AI raises the adversarial grade at which it must be defended above its original assumption. In this paper, we introduce requirement promotion as a framework for re-evaluating the classical taxonomy, contending that the destabilizing factor is not new cryptography but the emergence of a new adversary. We analyze five requirements under both AI-amplified threats and AI-enabled defenses, demonstrating that promotion fires selectively. Basic requirements such as privacy, fairness, and eligibility undergo tier promotion to counter-attack grade, driven by machine-learning-based deanonymization, pre-tally outcome inference, and synthetic-identity fraud. Incoercibility undergoes supra-tier promotion, surpassing the existing counter-attack toolkit, as deepfake-generated coercion evidence compromises the fake-credential assumptions of classical coercion-resistant schemes. Verifiability, where AI-based defense is robust, resists headline promotion but acquires a new sub-requirement at its seam with software independence: verifying the opaque machine-learning components in the audit pipeline itself. We then propose a reference architecture, integrating existing primitives such as lattice-based zero-knowledge proofs, deniable re-voting, statistical election forensics, and time-lock decryption into a layered design that addresses the promoted requirements, with explicit analysis of residual gaps.