G. Sreenivasulu, Bathula Siva Nageswara Rao, C. Rama Krishna, Srikanth Lukka · 6 authors
This study presents a comprehensive comparative research of the significant blockchain consensus algorithms, such as Proof of Work, Proof of Stake, Delegated Proof of Stake, Practical Byzantine Fault Tolerance, Proof of Authority, and hybrid mechanisms, and the purpose of it is to assess the performance, safety and applicability of blockchain to the modern use of blockchain. The studies analyze the key metrics, including throughput, latency, resource consumption, finality behavior, and fault tolerance in various network conditions based on a quantitative, simulation-based methodology with the help of secondary datasets. The results indicate that there are high levels of performance differences among consensus algorithms, as permissioned and delegated algorithms show better efficiency, and low latency, whereas public mechanisms put more emphasis on decentralization, disregarding speed and energy efficiency. The paper identifies the trade-offs inherent to consensus design and points out that no one mechanism is optimal, instead it needs to be chosen based on applicationspecific factors to do with scalability, trust, security, and decentralization. These insights help gain better insight into the issue of consensus behavior and make future choices regarding building the blockchain system.
This paper introduces a robust, scalable, and flexible workflow architecture designed to overcome longstanding challenges in the financial services sector. Financial institutions often face operational bottlenecks due to fragmented legacy systems, redundant Know Your Customer (KYC) procedures, and manual, error-prone processes. To address these inefficiencies, we propose a secure, distributed architecture leveraging the Distributed Ledger Technology (DLT) of R3 Corda to ensure immutable, auditable, and tamper-resistant records. The system integrates RESTful APIs to abstract the underlying blockchain complexity, providing seamless interoperability between banking systems and third-party services. Key modules include automated KYC verification, loan processing, and document authentication, which collectively reduce processing times, lower operational risk, and enhance regulatory compliance. To ensure user accessibility, the system features an intuitive graphical user interface (GUI) developed with Bubble.io, creating a seamless and efficient mechanism for end-to-end loan life cycle management. The system's modular architecture is validated through extensive testing, including Cypress-based automation, and is designed for future scalability, positioning it as a forward-thinking solution for broader adoption of blockchain in digital financial services.
This paper proposes a Decentralized Autonomous Intelligence (DAI) architecture that overcomes the self-referential limitations of conventional AI and Web3 systems by dynamically grounding collective intelligence in physical reality. By coupling internal consensus with high-fidelity external data such as environmental, biological, and economic signals, the framework prevents value drift, Sybil manipulation, and speculative bias. The result is a reality-aligned, secure, and scalable intelligence system optimized for real-world utility and immediate deployment.
Financial transactions demand exceptionally robust security, especially in light of the rapid advancement of quantum computing, which poses a severe threat to classical cryptographic mechanisms used in modern banking systems. Among various financial operations, transaction processing remains the most critical and vulnerable component. To address this emerging challenge, we introduce a Distributed Ledger Technology (DLT)-based secure framework for quantum-resistant financial transactions. The proposed architecture leverages lattice-based cryptographic security to ensure resilience against quantum attacks while preserving essential security attributes such as privacy, accountability, and data integrity. Furthermore, to demonstrate its effectiveness, the proposed framework is also compared with existing solutions in the literature.
The rigorous security model of Bitcoin's UTXO architecture often comes at the cost of developer usability, forcing a reliance on manual stack manipulation that leads to critical financial vulnerabilities like signature malleability, unspendable states and unconstrained execution paths. Industry standards such as Miniscript provide necessary abstractions for policy verification but do not model the full imperative logic required for complex contracts, leaving gaps in state management and resource liveness. This paper introduces Bithoven, a high-level language designed to bridge the gap between expressiveness and formal safety. By integrating a strict type checker and a resource liveness analyzer with a semantic control-flow analyzer, Bithoven eliminates major categories of consensus and logic defects defined in our fault model prior to deployment. Our results indicate that this safety comes at modest cost: Bithoven compiles to Bitcoin Script with efficiency comparable to hand-optimized code, demonstrating that type-safe, developer-friendly abstractions are viable even within the strict byte-size constraints of the Bitcoin blockchain.
The growing threat of cyber-attacks and the fast development of quantum computing have rendered conventional methods of cryptography to be inadequate in ensuring the security of data transmission. In order to resolve this issue, this paper will present a Hybrid Quantum-Safe Cryptographic Framework, a mixture of Post-Quantum Cryptography (PQC), Blockchain, and Zero-Knowledge Proofs (ZKP) to achieve secure, verifiable, and privacy-preserving data sharing. The system utilises quantum resistance based on lattice-based encryption, decentralized identity and tamper-proof storage based on blockchain, and authentication based on ZKP, which does not reveal sensitive user information. Moreover, a Tamil-based linguistic encryption layer that is integrated with AES-256-GCM is added to increase the cryptographic complexity and security of localization. The experimental analysis of the system run on a Windows-based platform proves that the system can encrypt a 1 MB file on average time of 1.9 seconds, at the same time being highly secure and scalable. The access control based on the ZKP had an accuracy of verification 99.2 and the AI-based anomaly detector had an accuracy of detection 96.8 and low rate of false-positive. These findings prove that the proposed framework provides an effective, quantum-resistant, and privacy-aware implementation that can be used in secure systems like e-governance, legal documentation, sensitive data sharing systems.
Centralized exchanges (CEXs) dominate cryptocurrency markets due to liquidity and low latency, but their opaque internal ledgers create custodial risk. Meanwhile, privacy concerns motivate private exchanges that blind the platform to user balances and order flow. Recent work such as Pisces [1] explores private and compliable exchanges, but one critical piece in compliance, public verifiable full solvency, remains unresolved. When liabilities are hidden from the platform, the platform cannot construct plaintext-based commitments and cannot be trusted to disclose complete liability sets at audit time, creating a fundamental privacy–solvency conflict. We address this conflict by designing two systems that enforce both solvency and platform-side privacy: * **Audit-then-Check Private and Solvent Exchange System:** Uses an RSA accumulator to provide constant-size membership witnesses; users verify inclusion after the auditor publishes an audit snapshot, and omission yields publicly verifiable evidence. * **Certify-then-Audit Private and Solvent Exchange System:** Eliminates user participation by introducing trusted hardware that certifies each transaction acceptance via a monotonic counter log, enabling the auditor to verify completeness without learning transaction contents. We provide rigorous security analysis that formally establish privacy against a malicious platform and solvency soundness against a malicious user-platform coalition. We implement both schemes and evaluate performance against the state-of-the-art baselines. Our prototype achieves average per-procedure computation under 35 ms, communication bounded by 14 KB per operation. For solvency verification, our online prover time remains nearly constant across user scales, achieving a 41.6× speedup over the state of the art and a 268.6× speedup over deployed baselines at $N = 2^{14}$ users, demonstrating that frequent auditing remains feasible at scale.
Nur Haliza Abdul Wahab, Juniardi Nur Fadila, Nur Faszha Razali, Keng Yinn Wong
High transaction costs remain a major barrier to the scalability of Ethereum-based decentralized applications (DApps), particularly when smart contracts are computationally inefficient. Although the Solidity compiler optimizer can reduce bytecode size and improve some low-level patterns, it does not fully address structural inefficiencies in storage layout and state mutation. This study introduces controlled empirical research on the topic of manual smart contract refactoring approaches with the aim of quantifying their impact on gas usage and execution cost in the Ethereum Virtual Machine (EVM). The Remix Integrated Development Environment (IDE) and a synchronized Go-Ethereum (Geth) node (version 1.13.5) were configured to create a controlled experimental environment. This environment was connected to the Sepolia Testnet to approximate conditions similar to the Ethereum Mainnet. The role of high-cost storage operations such as SSTORE was analyzed using opcode-level transaction traces, which were collected using debug_traceTransaction. The proposed refactoring plan implies the alignment of storage slots by systematically packing the variables and data location optimization (calldata and memory) to minimize unnecessary memory allocation. The experiments show gas reductions of up to 40.68% for storage-intensive functions, with an average reduction of 28.5% across all evaluated test cases. Moreover, the findings at the opcode level have shown that it is possible to reduce the costs of unnecessary storage writes without impacting the correct functional performance of the execution. Overall, the findings show that storage-aware manual refactoring is a viable strategy for improving runtime efficiency and reducing the execution cost of Layer-1 smart contracts.
K501 is a deterministic temporal-structural integration framework designed to provide append-only state anchoring, canonical serialization, and hash-bound integrity across heterogeneous systems. The framework does not replace existing infrastructures such as databases, version control systems, or distributed ledgers. Instead, it operates as an optional structural overlay layer that encapsulates states in a formally defined frame model with explicit time anchoring (UTC + Unix Epoch). K501 focuses on: Deterministic canonical serialization Append-only historical discipline Explicit temporal positioning Snapshot-based integrity Cross-system structural interoperability The specification defines minimal compliance requirements for structural integration without modifying internal operational semantics of integrated systems. K501 is intended as a neutral structural discipline for temporal knowledge stabilization and reproducible state documentation. Peace 🕊️ Frames stehen nicht isoliert! Das ist eine formal belastbare Beschreibung. Keine Überhöhung.Kein AGI.Keine Spekulation.Aber diese hier ist solide. 🕊️
K501 is a deterministic temporal-structural integration framework designed to provide append-only state anchoring, canonical serialization, and hash-bound integrity across heterogeneous systems. The framework does not replace existing infrastructures such as databases, version control systems, or distributed ledgers. Instead, it operates as an optional structural overlay layer that encapsulates states in a formally defined frame model with explicit time anchoring (UTC + Unix Epoch). K501 focuses on: Deterministic canonical serialization Append-only historical discipline Explicit temporal positioning Snapshot-based integrity Cross-system structural interoperability The specification defines minimal compliance requirements for structural integration without modifying internal operational semantics of integrated systems. K501 is intended as a neutral structural discipline for temporal knowledge stabilization and reproducible state documentation. Peace 🕊️ Frames stehen nicht isoliert! Das ist eine formal belastbare Beschreibung. Keine Überhöhung.Kein AGI.Keine Spekulation.Aber diese hier ist solide. 🕊️
This thesis deals with the implementation of a system for acquiring and processing transactions from various cryptocurrency blockchains. The aim of the thesis is to design and implement a system as a library that provides a unified interface for working with multiple blockchain networks. A key feature of the proposed system is its modularity, which enables future expansion to support additional cryptocurrencies. The thesis describes the architecture of selected blockchains and analyzes existing methods of obtaining data from these networks. Based on an analysis of available tools, Tatum.io was chosen as a suitable platform, as it offers interfaces for communication with a large number of blockchains. Subsequently, a general library model with an adapter-type architecture was designed, where each adapter ensures communication with a specific blockchain. The implementation was carried out in the Typescript language. The resulting library allows the user to track transactions based on specified parameters, which are: tracked address, time range (or block range), and blockchain type. The contribution of this work is the creation of a universal interface between the user and various blockchains without the need for detailed knowledge of them.
Spot trading on decentralized exchanges (DEXs) remains materially inferior to centralized exchanges (CEXs) in throughput, latency, and market-maker tooling, ceding global spot liquidity to opaque, non-custodial intermediaries. We present Vela, a spot exchange engine designed from first principles to recover CEX-grade performance while preserving the verifiability and self-custody properties of a DEX. The core engine is an optimized Rust state machine running entirely in memory, achieving a median per-operation latency of 1.08 microseconds (p50) — 4.7 times faster than the prior state of the art — and 57,300 operations per second under a realistic mixed market-making simulation across ten simultaneous markets. Exchange state is maintained in a Merkle Patricia Trie whose root is periodically committed to an underlying blockchain, anchoring state integrity to an external consensus mechanism. Verifiability is achieved through an optimistic zero-knowledge proving scheme: state updates are assumed valid by default, with a seven-day challenge window during which any party may submit a proof of incorrect execution, and an on-demand fast-finality path for users requiring immediate settlement. We introduce two features novel to DEX design: (1) a market-maker credit system enabling capital-efficient cross-market quoting analogous to CEX credit lines, implemented natively within the matching engine's state transition function with atomic collateral enforcement; and (2) private L3 market data feeds authenticated via server-issued nonce challenges and wallet signatures, substantially reducing market-maker exposure to adverse selection. We describe the full architecture, five performance optimizations including a Delta elimination that reduces p99.9 tail latency by 73%, flamegraph profiling findings, and decentralization mechanisms including forced inclusion via a delayed inbox. The Vela engine is released as open-source software under the MIT license at github.com/arpjw/vela.
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.
<b><i>State and event validation</i></b> are fundamental for ensuring the correctness and integrity of system states as they transition across decentralized networks. In decentralized systems, such as blockchain or distributed ledgers, maintaining state consistency, triggering actions based on events, and validating those actions across nodes require robust consensus protocols. This paper explores the architecture of state and event validation mechanisms, addressing challenges such as node synchronization, consensus-based event ordering, and error handling in invalid state transitions. By examining the role of validation in maintaining trust and reliability, we highlight its importance in secure and scalable decentralized applications, including smart contracts, financial transactions, and IoT systems.
This paper presents the post-quantum integrity architecture designed and being implemented within Smart Astro among the rst known platforms delivering Deterministic Engine Computed, AI-Narrated, Blockchain-Veried life guidance at scale. Smart Astro operates across 18 active life-decision intents and over 40 auspicious-timing categories, serving users globally through a real-time, pay-per-question model. Classical asymmetric cryptography underpinning current blockchain infrastructure is vulnerable to Shor's algorithm on fault-tolerant quantum computers. Smart Astro addresses this proactively by integrating NIST-standardised post-quantum cryptographic primitives FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), and FIPS 205 (SLH-DSA) alongside a Solana-anchored proof chain already live in production. The central architectural contribution is a layered separation of concerns: the deterministic engine computes a structured, repeatable output; cryptographic proof generation runs asynchronously outside the delivery path; the AI narration layer is isolated from the proof chain; and only a commitment hash is written to the Solana ledger, with the full postquantum signature bundle stored o-chain. Every paid answer carries an independently veriable SA-PROOF identier with zero personally identiable information (PII) on-chain. A hybrid ML-DSA + SLH-DSA signature scheme provides defence in depth against both lattice cryptanalysis and harvest-now-decrypt-later adversaries. This architecture establishes a replicable standard for cryptographic integrity in AI-narrated deterministic knowledge systems.
This chapter starts at the foundation—the problem blockchain is actually built to solve. Before any protocol detail makes sense, you need to understand why trust breaks down across a network of strangers, why decades of serious attempts at digital cash kept failing at the same point, and how Bitcoin’s combination of proof-of-work and a longest-chain rule finally closed the gap. The Byzantine Generals Problem is not a historical footnote here; it is the precise shape of the consensus challenge that every distributed ledger must answer. By the end of this chapter, you will have covered:
We present Processual Memory Architecture (PMA), a computational framework that unifies data storage and computation by representing all information as transformation functions rather than static state, rendering the traditional ontological distinction between them architecturally unnecessary. In PMA, storing information means encoding it as a mathematical transformation that produces the data when applied to a standardized canonical input; reading means applying the transformation; and computing means composing transformations. This inversion of the conventional von Neumann paradigm yields five emergent architectural properties—structural auditability, transparent reasoning, enforced constraints, tamper evidence, and reversibility—that collectively enable verifiable computation: systems that can mathematically verify the integrity and correctness of their own reasoning chains. We provide a complete mathematical specification of PMA over Galois fields GF(2k) with roundtrip exactness guarantees, constructive algorithms for both invertible and non-invertible encoding modes, and a reference permutation-based embodiment with explicit bit-level storage formats. We analyze thermodynamic properties under reversible logic implementation, demonstrating that PMA operations on adiabatic substrates can approach within 10× of the Landauer limit at the localnode level. We then present the integration architecture for PMA with artificial general intelligence (AGI) safety frameworks, showing how transformation-based reasoning enables safety constraints that are structural rather than advisory—creating systems where unsafe behavior is computationally undefined rather than merely prohibited. We discuss applications to financial auditing, medical AI verification, and autonomous systems governance, and compare PMA's approach to verifiable computation with existing paradigms including blockchain, zero-knowledge proofs, and mechanistic interpretability.
This paper specifies the Inference Battery Token (IBT), an ERC-20 on Base that mints when the inference orchestrator verifies a failed AI response, compensating the subscriber and capturing a structured DPO preference pair in one operation. Minting occurs through two pathways: automatic spot-checks that re-execute sampled requests on trusted nodes, and subscriber-initiated flags confirmed through the same re-execution pipeline. Each verified failure mints tokens proportional to the compute cost wasted, ranging from 1 IBT for embeddings to 20 IBT for extended reasoning. Subscribers redeem IBT for battery credits, permanently burning tokens. A genesis allocation of 10,000,000 IBT bootstraps exchange liquidity, network operations, community grants, and early investor capital with 12-month vesting. Because minting depends on AI failure rates and redemption increases with adoption, circulating supply contracts as models improve. Contributors who serve compute earn platform credits and elect payouts in USD or IBT, with a 15% bonus for token election. Hardware contributors may also earn IBT by generating zero knowledge proofs for the verification system during idle GPU windows. Revenue from selling accumulated failure records to frontier labs through the data access tiers described in the companion paper provides fundamental backing for token value.
Zhang Dayong, Nur Haliza Abdul Wahab, Juniardi Fadila, Arafat Al-Dhaqm · 8 authors
Practical Byzantine Fault Tolerance (PBFT) serves as a cornerstone consensus protocol for distributed systems. However, its inherent limitations, including quadratic communication complexity, scalability bottlenecks, and insufficient privacy protection, hinder its applicability in large-scale and privacy-sensitive environments. This study presents a systematic and comprehensive review of cryptographic advancements aimed at addressing these challenges. By analyzing peer-reviewed literature from 2015 to 2025, we demonstrate that the integration of Verifiable Random Function (VRF) and Boneh–Lynn–Shacham (BLS) aggregate signatures effectively reduces PBFT's communication complexity from O(N²) to O(N) or even O(logN), significantly enhancing scalability and reducing consensus latency. Moreover, advanced cryptographic schemes such as zero-knowledge proofs, homomorphic encryption, group signatures, ring signatures, hash ring, threshold signatures, attribute-based Encryption and lattice-based cryptography are shown to substantially strengthen consensus efficiency, privacy preservation and node security. Despite these improvements, trade-offs arise in terms of computational overhead and system complexity. The findings provide critical insights into the synergetic application of cryptography within PBFT-based systems and offer future directions for constructing scalable, secure, and privacy-preserving distributed architectures, particularly in Internet of Things and other resource-constrained scenarios.