Modern decentralized computing relies on two core architectural pillars: peer-to-peer (P2P) network topographies and cryptographic distributed ledgers. While early logical overlays prioritized file distribution without structural validation, contemporary blockchain deployments demand a stateful, highly adversarial communication layer. This paper provides an exhaustive analysis of the structural intersection between P2P routing mechanisms and consensus verification. We dissect the operational evolution from stateless distributed file indexes to stateful, trustless ledgers. Furthermore, we model the mathematical dynamics of epidemic data propagation, isolate systemic network-layer threat vectors such as boundary routing manipulation and node isolation attacks, and critique structural solutions implemented to scale data dissemination without inducing centralization.
In highly dynamic and interference-prone environments, secure access to wireless communication spectrum and protection of user privacy present significant challenges. To address these issues, this paper proposes a novel framework called the Secure and Privacy-Enhanced Channel Transmission Architecture (SPECTRA). SPECTRA enables fine-grained access control policies defined by a trusted authority and enforces them through distributed Semi-Trusted Distributed Servers (STDSs) using Attribute-Based Encryption and Zero-Knowledge Proofs. This design allows for dynamic spectrum authorization without revealing the requester's sensitive attributes. Furthermore, the frequency-hopping process is modeled as a Markov Decision Process (MDP), and optimized through Proximal Policy Optimization (PPO) to adaptively enhance communication reliability and resistance to interference. SPECTRA also supports both secure replacement and secure incremental update mechanisms, incorporating hash aggregation and elliptic curve signature-based batch verification to improve the efficiency and security of multi-request authentication. Extensive simulations demonstrate that SPECTRA achieves high-accuracy access control, effective communication privacy preservation, and stable frequency-hopping performance under adversarial and uncertain conditions.
This thesis addresses two research areas: scalable distributed ledgers for micro-transactions, and the automation of assembly planning in manufacturing industries. Established blockchain solutions are robust and reliable. Being distributed and decentralized, they avoid a single point of failure, and fault-tolerant consensus mechanisms ensure that the system works as intended even when some participants are faulty or malicious. However, their main weakness is scalability. The two most popular and well-known blockchain solutions, Bitcoin and Ethereum, require all nodes to store all transactions, and their transaction throughput is far too low to compete with traditional, centralized transaction processing systems. To improve scalability, systems have been developed that split the network nodes into groups that can process transactions in parallel, a technique known as sharding. We propose a sharded system called ScaleGraph that uses a novel architecture with one transaction per block and one shard per account, designed to maximize parallelism. The design is inspired by concepts from distributed hash tables, particularly to define shards based on a logical distance metric for node IDs and account IDs. Nodes store and process only transactions involving those accounts that are close to the node according to the distance metric. This greatly reduces the storage burden on each node and allows any number of transactions involving distinct accounts to be validated in parallel. We also design a new cross-shard transaction commit protocol for this architecture. The protocol offers global serializability and inevitable atomic commit, without the need for an abort path. This is achieved using only shard-local consensus and certificate exchange, rather than global or joint cross-shard consensus. Manufacturing is a highly complex process in many industries and involves many different planning problems where increasing automation has the potential to make manufacturing more efficient. This thesis presents a proof-of-concept solution to the kitting layout problem, where a list of parts has to be placed on a kitting wagon for delivery to an assembly line station. However, some problems have proven difficult to automate in practice, despite decades of research. One such problem, assembly line balancing, is analyzed in depth. We identify fundamental challenges that make the goal of complete automation implausible in some industries, such as automotive manufacturing. Human intervention is thus unavoidable, suggesting that bridging the gap between theory and practice requires decision support systems for assisted, iterative, and interactive planning. The thesis also includes preliminary work on the product sequencing problem, limited to framing the use case, assumptions, and requirements. Subsequent ongoing work suggests strong parallels to assembly line balancing, indicating that the identified challenges and possibilities for addressing them reflect a broader pattern in industrial planning automation.
The current internet architecture was fundamentally designed for deterministic data packet transport and applicationlevel request-response interactions, not for the semantic exchange, verification, governance, and replay of autonomous machine reasoning. As autonomous AI agents scale globally to orchestrate critical infrastructure, medical networks, corporate supply chains, and legal workflows, traditional integration patterns create structural bottlenecks. These limitations introduce severe risks of cognitive fragmentation, black-box opacity, and cascade errors across organizational boundaries. This paper proposes the Cognitive Internet Layer (CIL), a protocol-oriented overlay architecture positioned above conventional network transport and below autonomous AI applications. CIL introduces the Reasoning Exchange Protocol (REP) to route structured decision envelopes containing reasoning metadata rather than raw payloads. To resolve real-world deployment trade-offs, the framework integrates Zero-Knowledge Proofs (ZKPs) for privacy-preserving verification and a Tiered Execution Architecture to isolate highthroughput edge transactions from deep asynchronous multi-agent consensus validation.
This thesis presents the design and implementation of a mobile application for the Android platform aimed at advanced Bitcoin asset management. Its main features are support for multisignature transactions in an M-of-N scheme according to the BIP-48 and BIP-67 standards, and a coin control feature for manual selection of transaction outputs, allowing the user to optimize fees and preserve privacy. A key security element is the integration of the Trezor hardware wallet via the Trezor Connect protocol; private keys never leave the device. The PSBT format (BIP-174) is used to distribute partially signed transactions among cosigners; the application supports native SegWit addresses P2WP- KH and P2WSH. The backend is implemented as a set of microservices in Kotlin/Ktor, the frontend is a native Android application built with Jetpack Compose. Functionality was verified by unit tests of key components and by an end-to-end multisig scenario on the Bitcoin testnet.
Enterprises are rapidly shifting from human-interpreted dashboards to Autonomous Analytical Entities (AAE) that execute decisions directly on production systems. This transition introduces a new failure mode—Agentic Divergence—where decentralized agents act on misaligned, drifted, or out-of-scope data products and metadata, leading to high-impact errors at scale. This paper proposes the Autonomous Analytical Coherence (AAC) framework, centered on an Analytical Control Plane (ACP) that inserts a mandatory, machine-enforced governance layer between AAEs and decentralized data products. The ACP mandates Agentic Data Contracts (ADC) as runtime dependencies and enforces Kullback–Leibler (KL) divergence-based drift checks within Trusted Execution Environments (TEE) to safeguard both analytical coherence and data sovereignty. Simulation-based experiments across finance and logistics workloads indicate that AAC reduces erroneous autonomous transactions by 77% compared with uncoordinated agent deployments, with only a 25 ms median increase in latency. These results demonstrate that treating governance as a runtime dependency is a practical path toward safe, high-stakes autonomous analytics in enterprise data meshes.
Card-based zero-knowledge proof (ZKP) protocols allow a prover to convince a verifier that it knows a witness of a given statement, without revealing any information, using a physical deck of playing cards. Previous studies have focused on puzzles with a specific connected component, such as a simple cycle and a polyomino. In this study, we propose a unified approach to handle a family of connected components, including a tree, path, cycle, and polyomino. This approach achieves this verification in O(mn) steps relative to a given grid size m × n. Using this approach, we construct a card-based ZKP protocol for Nurimeizu, where the goal is to find the shortest path on a given grid.
This project explores the Groth16 zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) protocol, with an emphasis on accessibility and practical understanding. It begins with a review of zero-knowledge proofs, non-interactive zero-knowledge proofs, and zk-SNARKs, followed by a structured explanation of the Groth16 construction, from Rank-1 Constraint System (R1CS) and Quadratic Arithmetic Program (QAP) representations, to the full formulation incorporating trapdoor elements and zero-knowledge randomness that is supported with a working Python implementation over the BN254 elliptic curve. These theoretical concepts are then applied in SudoZKu, a browser-based Sudoku game that demonstrates a complete end-to-end zk-SNARK real-world implementation pipeline. This system uses Circom for circuit design and snarkjs for Groth16 proof generation and verification, illustrating how high-level computations can be translated into succinct, verifiable proofs within a practical setting. Experimental evaluation then compares Groth16 and another zk-SNARK known as Permutations over Lagrange-bases for Oecumenical Non-interactive arguments of Knowledge (PLONK). Results show that Groth16 achieves approximately 1.9x smaller proofs and up to 16x faster proof generation than PLONK, while both are able to complete verification under 65 milliseconds. The project then concludes by analysing the key trade-offs for Groth16, including trusted setup requirements and a lack of post-quantum security, and outlines future research directions such as on-chain verification and privacy-preserving uses of Groth16.
Secure multiparty computation (MPC) over Z2kis more efficient than computations over fields, and studying MPC protocols under malicious security has practical application value. Malicious security with a dishonest majority over rings remains challenging. The most popular approach is SPDZ2k, however, this is a specific protocol that does not support the transformation of any existing semi-honest MPC protocols into malicious security protocols. The zero knowledge proof (ZKP)-based compiler satisfies this requirement. Existing state-of-the-art protocols have logarithmic online communication overhead in terms of the circuit size |C|, and their direct application to rings is nontrivial as they were originally designed for finite fields. In this work, we investigate the communication overhead to develop malicious security protocols. We bridge the gap between malicious security with abort and semi-honest security, by constructing a “GMW-style” verification protocol to achieve malicious security in a dishonest majority setting. This approach incurs a constant online communication overhead by enhancing the machinery of zero-knowledge fully linear interactive oracle proof (zk-FLIOP). Additionally, we extend the zk-FLIOP to work over any ring by invoking reverse multiplication friendly embeddings (RMFEs). Our results show that the online communication complexity of the verification process depends on only the security parameter, the number of parties, and the ring size. Furthermore, for small-scale circuits over Z2, we designed a distributed lookup table argument where both the total communication complexity and the computational cost are independent of the circuit size but of the input wires.
Ioannis Tzannetos, Danai Balla, Aris Pagourtzis, Vassilios Vescoukis
Non-fungible tokens (NFTs) have created vibrant digital marketplaces where unique assets are exchanged across domains such as art, gaming, and music. While current infrastructures are optimized for pairwise, currency-backed trades, they provide limited support for multi-party swaps of indivisible assets based on user preferences. In practice, liquidity is not always desirable—participants may wish to exchange directly for assets they deem equally valuable, bypassing auctions or currency markets. In this paper, we propose BarterSwap, a protocol to address this gap by leveraging the Top Trading Cycles (TTC) algorithm to enable efficient multi-party NFT exchanges on Ethereum. Our protocol identifies preference-based dependencies among users and executes swaps without requiring external liquidity. We implement and deploy our solution on the Ethereum blockchain, demonstrating that it remains practical for a reasonably large number of participants. Finally, we release our implementation publicly and provide a detailed cost analysis, offering a concrete path toward fair and efficient preference-based NFT exchanges.
This technical report presents the reference implementation of Ternary Moral Logic (TML) within the Ethereum Virtual Machine (EVM) ecosystem. It addresses the limitations of traditional "Code is Law" architectures by introducing a finite state machine that enforces a mandatory third state—the "Sacred Zero" or Epistemic Hold—allowing smart contracts to pause execution when pre-defined ethical conditions are unmet. The report moves beyond theoretical ethics to specify the Solidity design patterns, storage layouts, and cryptographic verification methods required to make TML enforcement non-bypassable and auditable. Key Technical Contributions: Finite State Machine (FSM): Implements a mandatory "Sacred Zero" state (State 0) that acts as an "Epistemic Hold," distinguishing between valid (1), invalid (-1), and uncertain (0) transaction states. Dual-Lane Latency Architecture: Defines a "Fast Lane" for synchronous, clear-cut transactions and a "Slow Lane" for ambiguous cases requiring governance or oracle resolution, preventing head-of-line blocking. Cryptographic Provenance: Utilizes EIP-712 typed data signing to bind off-chain AI/Oracle verdicts to on-chain execution, preventing replay attacks and ensuring distinct domain separation. Privacy Preservation: Integrates Zero-Knowledge Proofs (ZK-SNARKS) to verify the execution of moral logic models without revealing sensitive input data or proprietary model weights ("Glass Box" architecture). Immutable Core Pattern: Rejects standard upgradeable proxy patterns in favor of an "Immutable Core" architecture to eliminate administrative "God Mode" and ensure constitutional constraints cannot be bypassed by key holders. Formal Verification: Demonstrates safety and liveness properties (e.g., "No Silent Pause," "Eventual Resolution") using TLA+ (Temporal Logic of Actions) to mathematically prove the system's robustness.
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.
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.
This paper introduces a secure state-sharding solution for permissionless blockchains that supports both payment transactions and general Ethereum-like smart contracts. The secure partitioning of the blockchain into distinct shards continually adapts to the current transaction workload, encompassing both user and smart contract transactions. A novel two-phase commit protocol guarantees the correct execution of smart contracts distributed across different shards. Notably, this protocol offers, for the first time, support for smart contracts with nested calls across shards, without any limitation on the depth of the calling graph. An experimental study highlights the benefits of the adaptive behavior of shards during the distributed execution of such nested smart contracts.
Bitcoin's limited programmability and transaction throughput have historically prevented native Bitcoin from participating in decentralized finance (DeFi) applications. Existing solutions depend on honest-majority thresholds, or centralized custodial entities that introduce significant trust requirements. This paper introduces Bitcoin Smart Accounts (BSA), a novel protocol that enables native Bitcoin to access DeFi through trust-minimized infrastructure while maintaining self-custody of funds. BSA achieves this through a combination of emulated Bitcoin covenants using Partially Signed Bitcoin Transactions (PSBTs) and Taproot scripts, a Trusted Execution Environment (TEE)-based arbitration system, and destination chain smart contracts that enable DeFi platforms to accept self-custodial Bitcoin as collateral without necessitating protocol-level modifications. The setup leverages liquidity secured by the Lombard Security Consortium which provides a twofold advantage: for a DeFi protocol, liquidators rely on fungible assets with deep liquidity to quickly exit positions, while for a depositor, the general trust assumptions of honest majority (m-of-n) are reduced to existential honesty (1-of-k). We present the complete protocol design, including the Bitcoin architecture, the TEE-based arbitration mechanism, and the Smart Account Registry for protocol management. We provide a security analysis that demonstrates the correctness, safety, and availability properties under our trust model. Our design enables native Bitcoin to serve as collateral in lending markets and other DeFi protocols without requiring users to relinquish custody of funds.
Blockchain technology has transformed distributed systems by enabling mutually untrusted nodes to reach agreement without a central authority. Such trustless decentralized paradigm relies on the robustness of system design mainly from two components: the consensus layer governing block production and the data layer governing data consumption. However, these pillars of robustness could be undermined in a Byzantine environment, where adversarial participants may strategically misbehave, leading to biased data production and compromised data access. This thesis systematically addresses robustness vulnerabilities across both layers, ensuring that blockchain systems remain fair, predictable, and verifiable throughout the entire data lifecycle. At the consensus layer, we first address selfish mining in Proof-of-Work (PoW), which allows adversarial miners to gain disproportionate revenue. We introduce an unfairness metric based on the divergence between computing power and mining revenue, and propose Tit-for-Tat (TFT), a block-promotion strategy that detects suspicious forking behavior and selectively delays block propagation. To optimize this defense, we formulate the Delay Vector problem and develops efficient approximation algorithms. Second, we study block withholding in Byzantine Fault Tolerant Proof-of-Stake (BFT-PoS), where proposers may delay blocks to extract additional Maximal Extractable Value (MEV). To restore predictable block generation, we propose InTime, an incentive mechanism that rewards timely proposals according to transaction arrival rates observed across the network. InTime combines an Arrival Rate Incentive, a Committee Time Witness workflow, and a Shift-Mean Estimation algorithm to collect and verify timing information under adversarial conditions. At the data layer, we propose the Merkle Bloom Filter Tree (MBFT), a framework for authenticated aggregate queries with keyword and range predicates. MBFT supports efficient verification for complex on-chain queries, including time-window queries, while controlling storage overhead. We design a novel Merge Bloom Filter (MBF) for space-efficient handling of dynamic sets during query authentication.
Despite its serious consequences, network partitioning remains one of the most overlooked threats in blockchain systems. When a blockchain network splits into disconnected segments-due to routing failures, deliberate attacks, or infrastructure outages-nodes in each segment continue building their own version of the ledger independently. When connectivity is restored, one chain must be discarded, and any transactions recorded only on the discarded chain are lost. If an attacker deliberately timed payments to both sides of the partition simultaneously, those payments may succeed on both chains-a double-spend. The severity of this threat varies by consensus design. Public proof-of-work chains like Bitcoin face double-spend risk. Proof-of-stake networks like Ethereum risk finality delays and validator penalties. Permissioned systems like Hyperledger Fabric halt block production entirely. Despite these distinct consequences, the research literature treats these platforms in isolation. This survey unifies the analysis. We review over twenty peer-reviewed works (2002-2024), covering distributed systems theory, deliberate attack vectors, consensus protocol behavior, and detection and mitigation strategies. We present a comparative taxonomy, identify four open research problems, and conclude that existing mitigations are largely reactive and platform-specific-a cross-platform approach to partition resilience is still needed.