The set reconciliation problem, that consists in bringing two or more replicas of a set into agreement is present in all databases, distributed ledgers and any large scale synchronization systems.While the two party case is well studied, the multiparty one exposes a large design space of protocols whose communication cost varies drastically with topology, replica count and the level of similarity.A very slow space to search on by hand.This thesis investigates the use of an autonomous agent loop as a research tool to navigate that specific design space.This means using an agent to iteratively propose, implement and evaluate reconciliation protocols against a single measurable objective until convergence is achieved.In this case, the objective was the total bytes transmitted, including state and metadata, taken as a geometric mean over an evaluation matrix with eighteen cells and three seeds.The search yielded MultiReplica, a topology dispatched protocol that combines all neighbor Bloom filter exchange on star and tree topologies with pairwise distance doubling on chord and that reduces communication cost by roughly 30 % relative to the strongest hand designed baseline while scaling to replica counts at which the baselines exhaust memory.The contribution is twofold.On one side the discovered protocol itself and a reproducible demonstration that an autonomous agent loop can serve as a credible, auditable method for distributed systems protocol research.
Decentralized storage offers high availability and scalability. However, owing to the decentralized storage of data across multiple nodes, issues such as slow data access and complex operations arise, resulting in a poorer user experience compared to centralized storage. To address this, a data availability sampling technology is employed, which maintains the decentralized nature of the method while incorporating the advantages of centralized storage. In data availability sampling technology, multiple nodes obtain a smaller, randomly selected subset of data from a single data owner. This technology is often combined with erasure coding to enhance data availability. Based on data availability sampling technology, decentralized storage providers are introduced to serve users on a one-to-one basis, and data guarantors supervise storage providers and provide guarantees for user data. A comprehensive storage method is designed to achieve highly available data storage, and blockchain and smart contracts are employed to enhance decentralization. By supporting a repledging model and adopting a storage-proof algorithm with low computational resource consumption, the willingness of the nodes to join is increased. To resolve the contradiction between large data scales and the limited bandwidth resources of data guarantors, a delayed confirmation mechanism is proposed. Experimental and analytical results show that under this method, the probability of malicious node collusion is only 2.43×10<sup>-3</sup>, the probability of untrustworthy data availability sampling results is only 2.93×10<sup>-4</sup>, the number of data unavailability occurrences is 0 in 3 million simulation experiments, the number of centralized nodes is 0, and generating storage proofs for a 1 MiB file takes only 3.51 ms. This method achieves highly available data storage while improving user-friendliness and node-friendliness, providing a feasible technical path for optimizing decentralized storage.
Rithika S, Thrisha S, Uma Mageshwari M, Vaishali D · 5 authors
Peer-to-peer (P2P) interaction forms a foundational layer of Web3 ecosystems, enabling participants to exchange data directly without depending on centralized brokers. In practical deployments, however, end-to-end reachability is often obstructed by network address translation, firewalls, and transient routing paths, which pushes architects toward the use of intermediate relay nodes. Unfortunately, relays that behave inconsistently or act maliciously can introduce a range of undesirable effects, including dropped packets, elevated latency, selective forwarding, and denial-of-service conditions. To mitigate these risks, this work presents a reputation-aware relay selection framework that lever-ages a blockchain substrate to govern trust. Every participant in the overlay is issued a cryptographic identity; the quality of service delivered by each relay is then tracked at runtime through metrics such as delivery ratio, round-trip delay, and transmission failure rate. A smart contract layer aggregates these observations into a dynamic reputation score that is recorded on an immutable ledger. When a communication session is being established, relays with higher reputation are preferred, while those exhibiting suspicious or degraded behavior are deprioritized or excluded. Experimental results indicate that, compared with conventional relay-selection strategies, the proposed approach delivers higher reliability, lower effective latency, and stronger resistance to malicious participation, making it a practical candidate for secure Web3 P2P communication.
Transaction selection in parallel or DAG-based distributed ledger technologies (DLTs) is a crucial challenge that directly impacts throughput, fairness, and validator incentives. In these systems, validators independently choose transactions to include in their blocks, often relying on naive heuristics like uniform or proportional selection. This can lead to inefficient outcomes when validators prioritize their own rewards without considering collective impacts. We analyze two fee allocation mechanisms used in practice: Random Fee Allocation (RFA), where transaction fees are randomly assigned to one validator, and Collaborative Fee Sharing (CFS), where fees are distributed equally among all validators. Using a single-shot game-theoretic framework, we derive symmetric Nash equilibria (NE) for selecting transactions for both mechanisms and propose an optimization-based method to compute these equilibria. Numerical simulations demonstrate that the NE of CFS consistently achieves higher throughput and rewards compared to the NE of RFA, particularly under skewed fee distributions. Additionally, we compare these equilibrium strategies to naive benchmarks (uniform and proportional selection), showing that the proportional strategy outperforms the NE of RSA in many situations. These findings may provide actionable insights into the design of transaction selection and incentive mechanisms, enabling more robust and high-performance DAG-based DLTs.
Mohammad Y. Allaho, Mehmet H. Karaata, Israa A. Elgemiei
The distributed ledger systems rely heavily on miners, who are a vital component of the cryptocurrency ecosystem. Most cryptocurrencies cease to exist within five years of operation [1] due to churning. Most current cryptocurrency analyses in the literature focus on mining pools and ignore the individual miners’ perspective and in-depth analysis of the churning phenomenon and its possible reasons. In this study, we conducted a longitudinal and overall study on two of the most growing cryptocurrency networks, namely Bitcoin and Ethereum. The Bitcoin dataset used spans over 12 years (2009-2021). Whereas the Ethereum dataset spans over 8 years (2015-2023), including the two versions of Ethereum (before and after the merge). Our goal is to uncover the factors that drive miners’ churning and reveal essential characteristics of cryptocurrency mining, such as network fairness and centrality. Generally, both networks experience a decline in active miners over time. Our results confirm the centrality of the Bitcoin and Ethereum networks, whereas Bitcoin is found to be more distributed and fairer than Ethereum in both versions. Also, in Bitcoin, solo miners are less centralized and experience a fairer distribution of blocks formation than pool miners, however, pool miners have more mining rewards on average. Also, pools are found to decrease churning for pool miners compared to solo miners. Moreover, it is found that miners’ waiting time is a significant factor in miners’ churning. The existing protocols used require improvements to increase network decentralization and fairness, as well as reduce miners’ churn.
Traditional digital card games rely on centralized servers, introducing catastrophic single points of failure, while decentralized Web3 alternatives fail to achieve real-time viability due to prohibitive block latency. This paper introduces Panoptes, an optimized, hybrid cryptographic engine that enforces low-latency decentralized consensus for peer-to-peer state channels. Assuming a highly hostile user-space environment, Panoptes treats the host application space and its underlying managed runtime as fundamentally compromised.A bifurcated architecture is detailed utilizing a hardened native airgap and direct OS-level memory mapping to process ciphertexts, bypassing standard and predictable libc allocators. To mitigate automated memory scrapers and frustrate asynchronous Direct Memory Access (DMA) attacks, Panoptes implements a multiplexed decoy memory topology (The Vault). This architecture relies on strict virtual page guarding, offline decryption, and temporal starvation via millisecond-scale execution windows. The protocol replaces commutative encryption with a deterministic Hand Commitment Payload, utilizing X25519 KEM, XOR- based Secret Sharing, and ChaCha20-Poly1305 to enforce Strict Zero-Trust Consensus.
Traditional digital card games rely on centralized servers, introducing catastrophic single points of failure, while decentralized Web3 alternatives fail to achieve real-time viability due to prohibitive block latency. This paper introduces Panoptes, a highly optimized, hybrid Zero-Trust cryptographic engine that enforces microsecond-latency decentralized consensus for the CoronaPoker peer-to-peer network. Assuming a strict Ring-0 adversary model, Panoptes treats the host operating system and the Java Virtual Machine (JVM) as fundamentally compromised. We detail a bifurcated architecture utilizing a hardened native airgap that leverages OS-level stealth allocators to process ciphertexts without leaving plaintext residue in the managed heap. To mitigate OS-level memory scrapers and hardware-based Direct Memory Access (DMA) attacks, Panoptes implements a multiplexed decoy memory topology (The Vault). It is secured by strict virtual page guarding against software introspection, and heavily relies on offline decryption with immediate sub-millisecond zeroization to temporally starve asynchronous hardware-level carving. The protocol entirely replaces traditional commutative encryption with the deterministic Hand Commitment Megapacket, a flat-buffer payload leveraging X25519 KEM, Additive Secret Sharing, and ChaCha20-Poly1305 to ensure Byzantine fault tolerance without majority voting. We present formal implementations of our micro-architectural defenses, including Mixed Boolean-Arithmetic (MBA) for constant-time execution, direct cross-platform syscalls bypassing libc, OS-level DACL lockdowns, PEB cloaking, and asynchronous SipHash-2-4 binary attestation. Furthermore, we introduce a multithreaded Deadman Switch to detect CPU cycle drift via RDTSC. Evaluated under an exhaustive 42-point "Total Siege" adversarial framework, the engine demonstrates unparalleled resilience against hardware breakpoints, kernel introspection, inline hooking, and temporal drift attacks.
Peer-discovery protocols within P2P networks are often vulnerable: because creating network identities is essentially free, adversaries can eclipse honest nodes or partition the overlay. This threat is especially acute for blockchains, whose security depends on resilient peer connectivity. We present AetherWeave, a stake-backed peer-discovery protocol that ties network participation to deposited stake, raising the cost of large-scale attacks. We prove that, with high probability, either the honest overlay remains connected or a $(1{-}δ)$-fraction of nodes in every smaller component raise an attack-detection flag -- even against a very powerful adversary. To our knowledge, AetherWeave is the first peer-discovery protocol to simultaneously provide Sybil resistance and privacy: nodes prove they hold valid stake without revealing which deposit they own, and gossiping does not expose peer-table contents. A cryptographic commitment scheme rate-limits discovery requests per round; exceeding the limit yields a publicly verifiable misbehavior proof that triggers on-chain slashing. Beyond deposit and slashing, the protocol requires no on-chain interaction, with per-node communication scaling as $O(s\sqrt{n})$. We validate our design through a mean-field analysis with closed-form convergence bounds, extensive adversarial simulations, and an end-to-end prototype built by forking Prysm, a leading Ethereum consensus client.
Abstract Blockchain-based token systems face a fundamental scalability challenge known as the back-to-genesis problem : verifying a token’s provenance requires tracing its complete transaction history from issuance to the present. For fungible tokens, where transaction inputs can be combined and split, this history forms a directed acyclic graph whose size grows exponentially with the transaction chain length. We propose a lightweight token validation system that achieves efficient peer-to-peer (P2P) and offline verification by combining three design elements: (i) encoding tokens as UTXO-based non-fungible instruments with fixed denominations, which restricts each token’s history to a strictly linear chain; (ii) SPV-style Merkle proof verification against locally stored block headers; and (iii) a distributed hash table (DHT) that stores compact proofs for each token’s transaction history, shared peer-to-peer among participants. We formalise the structural difference between fungible and non-fungible token histories, show that the crossover point at which exponential fungible-token verification exceeds the linear NFT cost occurs at chain length ≈ 6 using empirically measured blockchain branching factors, and describe a periodic reminting mechanism that bounds chain lengths and enables predictable maintenance. We analyse the security properties of the system under a threat model that addresses DHT availability, proof freshness, eclipse resistance, and double-spend risks in offline operation. The system requires no trusted third party, no zero-knowledge proof infrastructure, and no modifications to the underlying blockchain consensus protocol, making it suitable for deployment on resource-constrained devices and a practical architecture for central bank digital currency (CBDC) implementations. Performance benchmarks on commodity hardware, including a Raspberry Pi 4 and an Android smartphone, confirm that verification completes in under 6 ms for typical payment scenarios, validating the system’s practicality for real-world deployment.
Censorship resistance is a core value of Web3, yet practical access to decentralized websites remains dependent on centralized gateways such as ipfs.io, .link, and .limo, which are susceptible to regulatory takedowns and availability limitations. This paper investigates the technical barriers to truly censorship-resistant access in decentralized web architectures and presents an engineering-driven analysis of dweb3.wtf, a dedicated rendering gateway developed within the Web3Compass infrastructure. The system directly interfaces with decentralized name systems such as ENS and Unstoppable Domains, autonomously resolves content hashes via on-chain resolvers, and renders the associated IPFS-hosted sites via self-hosted infrastructure. By eliminating reliance on third-party APIs and centralized frontends, the gateway offers a robust alternative to Web2-style intermediaries. This paper presents the architecture, implementation, and performance characteristics of dweb3.wtf, evaluating its effectiveness in ensuring access continuity, domain coverage, and reduced external dependency.
The InterPlanetary File System (IPFS) has been extensively promoted as a decentralized, censorship-resistant, and fault-tolerant storage protocol. This paper systematically dismantles these claims by demonstrating four critical and compounding vulnerability classes: (1) the structural dependency on centralized pinning services such as Pinata, Infura, and Web3.Storage, where compromising a single provider's dashboard or API effectively eliminates supposedly “immutable” content; (2) the futility of self-hosted pinning nodes as a mitigation strategy, given their susceptibility to targeted Distributed Denial-of-Service (DDoS) attacks capable of rendering them permanently unreachable; (3) the catastrophic implications of a cryptographic backdoor or collision discovery in SHA-256 or SHA-3 (Keccak), which would enable arbitrary content substitution while preserving valid Content Identifiers (CIDs), thereby destroying IPFS's fundamental integrity guarantees; and (4) the vulnerability of distributed pinning strategies to gossip-protocol-based reconnaissance attacks, wherein a state-level adversary (e.g., NSA, GCHQ, or equivalent) can enumerate all nodes hosting a target CID by compromising a single peer and leveraging protocol-level metadata propagation to systematically identify and neutralize every replica simultaneously. We formalize each attack vector with mathematical models, provide proof-of-concept algorithms, analyze the compounding effects of multi-vector attacks, and demonstrate that even the most sophisticated defense-in-depth strategies fail against a sufficiently resourced adversary. Our analysis conclusively establishes that IPFS, as deployed in practice, provides no meaningful censorship resistance and constitutes what we term Decentralization Theater—a system that employs the aesthetics and terminology of decentralization while maintaining the vulnerability profile of traditional centralized architectures, augmented by a dangerous false sense of security.
The growing popularity of blockchain technology has underscored the need for robust network security. However, public blockchain networks remain vulnerable to attacks in which adversaries exploit numerous nonfunctional peer connections to disrupt block propagation across the entire network. In this article, we propose a practical nontargeted delay attack method and validate its feasibility, scalability, and significant impacts on blockchain networks of varying sizes, including EthereumPoW (ETHW) and premerge Ethereum Mainnet. In the ETHW network with 95 nodes, our adversarial peers introduce delays ranging from 0.33 to 2.8 s for half the nodes, with nearly one-third experiencing delays exceeding 5.9 s, derived from the 90th percentile of delay times. When in the premerge Ethereum network with 5739 nodes, over 80% of peers experience prolonged block propagation, resulting in a 77% increase in delay time, underlining the attacks' scalability and efficacy in large-scale environments. We also optimize the Ethereum client Geth by relaxing certain connection restriction, significantly reducing attack costs. Delving deeper, we analyze the implications of delay attacks on proof-of-work (PoW) and proof-of-stake (PoS) consensus mechanisms, illustrating how attackers can gain extra revenues through such attacks. Specifically, we propose a novel combined strategy to facilitate reorganization attacks under PoS. These findings highlight the urgent need to strengthen network-layer defenses and reinforce peer-to-peer (P2P) network protocol security against real-world delay exploits.
We present a lightweight, probabilistic mechanism for certifying aligned storage between participants in decentralized systems. Participants respond to randomized suffix queries by performing forward scans over their locally stored data and returning short response sequences. A verifier observes only overlap statistics between responses. We prove that the overlap probability is bounded above by the minimum storage density among participants, ensuring that high observed overlap implies all parties store a large fraction of the underlying dataset. This bound holds regardless of adversarial strategy: a single well-provisioned participant cannot "carry" an under-provisioned partner. The protocol's "+1" advancement rule introduces pointer desynchronization that causes naïve Binomial models to overestimate tail probabilities by 2–3×. We establish rigorous security bounds through systematic simulation of Poisson-walk dynamics. For example, observing 10 or more matches out of 12 recorded elements rules out minimum density below 0.6 at the 2.4% significance level. Independent repetition amplifies confidence exponentially. The mechanism requires no cryptographic commitments per element, no global verifier, and reveals only O(m) randomly-selected elements per interaction. We analyze several natural adversarial strategies—fabrication, selective answering, collusion, Sybil attacks—and show that none can increase overlap probability beyond what storage density allows. From a mechanism-design perspective, repeated suffix-walk interactions induce a game where aligned storage is the dominant strategy, enabling emergent consensus without central coordination. The protocol serves as a foundation for proof-of-aligned-storage in distributed systems and provides consensus weight based on demonstrated storage rather than computational power or stake. Throughout this paper, "proof" refers to statistical evidence under a well-validated probabilistic model, not a cryptographic zero-knowledge proof.
Tato práce se zabývá problematikou šíření transakcí v bitcoinové peer-to-peer síti, jejich monitorováním a měřením doby potřebné na jejich propagaci pro různé kombinace parametrů bitcoinových uzlů a sítě. Cílem této bakalářské práce je pochopit principy a mechanismy používané v bitcoinovém protokolu pro šíření transakcí v síti. Na základě získaných informací je navržen a implementován simulační model, který umožňuje sběr statistických dat o procesu šíření transakcí mezi uzly. Součástí práce je také vytvořený analyzační skript, schopný identifikace uzlů, kterými byly dané transakce vytvořeny.
Bitcoin is considered an anonymous transaction technology. Transactions are not directly linked to real names or physical identities of users. However, each transaction is recorded in the blockchain, which is publicly available and allows anyone to perform detailed analysis. This bachelor thesis deals with the issue of attributing cryptocurrency wallets to specific nodes in the Bitcoin peer-to-peer network. The aim of the thesis is to examine the process of transaction propagation between nodes, identify factors influencing their order and propagation speed, and propose methods that will allow estimating the original node responsible for creating or first sending the transaction. The theoretical part describes the basic mechanisms of transaction propagation in the network and analyzes anonymization and deanonymization techniques. The practical part focuses on the design and implementation of heuristics combining propagation time profiles with topological information about the network. For this purpose, a modular platform was developed in the .NET environment, which enables the analysis of data from the P2P network. The contribution of this work is the combination of theoretical principles of transaction propagation with the practical use of data from a real network and the extension of existing methods for analyzing anonymity in the Bitcoin cryptocurrency environment.
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.
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.