In this paper, a scalable interoperable hybrid blockchain systems based on a novel seven-layer architecture is proposed. The model thereby solves the three problems that have restricted the development of traditional blockchains, i.e., low transaction throughput, inability of cross-chain communication, architectural rigidity, by clearly dividing responsibilities into separate layers dedicated to core infrastructure, operation systems, and application ecosystems. It applies a hybrid consensus approach where Proof of Stake (PoS) is adopted for global finality and Practical Byzantine Fault Tolerance (PBFT) is employed for shard-level consensus, offering energy efficiency as well as fault tolerance. With rollups, sharding, and interoperability protocols e.g. Polkadot, and IBC, it boasts high performance, modular extensibility and app-ability for real-world use-cases such as finance, IoT and healthcare. The proposed architecture would act as a basis for development in AI-driven smart contracts, privacy-preserving computation and quantum-secured consensus.
Proof-of-Stake (PoS) consensus protocols commonly employ epochs as temporal abstractions to simplify validator accounting, reward distribution, and slashing enforcement. These designs assume clean and synchronized state transitions across epoch boundaries. In practice, distributed systems exhibit asynchronous execution, delayed finality, and implementation divergence.This paper introduces and analyzes <b><i>Validator Epoch Reset Collisions</i></b>, a class of temporal desynchronization vulnerabilities in which validator state resets, reward counters, slashing windows, or participation flags become inconsistently applied across epoch boundaries. We demonstrate how such collisions create exploitable enforcement gaps that can be leveraged to evade penalties, duplicate rewards, or bypass participation requirementsâwithout violating protocol rules. We argue that epoch-based accounting introduces structural risks to economic security unless continuity-enforcing safeguards are applied.
Andrea Esposito, Francesco P. Rossi, Marco Bernardo, Francesco Fabris ¡ 5 authors
Algorand is a scalable and secure permissionless blockchain that achieves proof-of-stake-based consensus via binary Byzantine agreement and cryptographic self-sortition. In this paper we present a process algebraic model of the Algorand consensus protocol, which captures the behavior of participants in terms of the alternation of steps toward a committee-based agreement. We use the model to study the robustness of the protocol with respect to malicious participants, which may try to boy- cott the commitment of the proposed block, as well as the probabilities of committing the proposed block or an empty one after a boycott attempt. Our process algebraic model is translated into LNT, the language of the CADP toolset, to investigate robustness via a novel application of equivalence-checking-based noninterference analysis, which we have implemented in CADP through its script verification language SVL.
Andrea Esposito, Francesco P. Rossi, Marco Bernardo, Francesco Fabris
Algorand is a scalable and secure permissionless blockchain that achieves proof-of-stake-based consensus via binary Byzantine agreement BBAâand cryptographic self-sortition. In this paper we present a process algebraic model of the Algorand consensus protocol with the aim of enabling formal verification. Our model captures the behavior of participants in terms of the structured alternation of consensus steps toward a committee-based agreement. We verify the robustness of the protocol in the presence of coordinated malicious participants that may try to force the commitment of an empty block instead of the proposed one. The verification of our pure process algebraic model translated in the LNT language is conducted through a novel application of equivalence- checking-based noninterference analysis, which we have implemented in the CADP toolkit through its script verification language SVL.
Blockchain as a promising technology is gaining its popularity ever since proof-of-work based Bitcoin came to the world. Nevertheless, Bitcoin achieves consensus at an expensive cost of energy. Proof-of-stake is one of the solutions for such a problem. Participants of PoS protocols achieve dynamic-availability in permissionless settings. Parties can join and leave the protocol at their will without notifying others. However, such protocol relies heavily on a central clock, providing the function of synchrony by collecting the finish status of every honest participant. In our protocol, the global function maintains the round information for each participant no longer needed. We analyze and modify the round into real-time based round model. Message delivery delay is also taken into consideration of the round length. However, participant need the connection of a real-world time global clock which is crucial to calculate the current round. And round length also is adjusted due to the changing network situation at the start of every new epoch.
GLYPH is a transparent verification layer for Ethereum for trustless on-chain verification of heterogeneous proof systems. It unifies upstream SNARK and STARK settlement through a single packed arity-8 sumcheck verifier over p = 2^128 - 159, while preserving upstream assumptions. The design centers on a universal adapter surface, UCIR compilation, and a chain-bound artifact interface for stateless verification. Benchmark evidence in the whitepaper reports 29.45k total transaction gas in recorded testnet receipts. This record includes the whitepaper and the formal proof appendix.
<b><i>Zombie Validator Resurrection</i></b> is a core consensus-layer exploit in Proof-of-Stake (PoS) and alternative Layer-1 networks where inactive, slashed, or economically abandoned validators regain influence without restoring proportional economic security. Through protocol gaps, state resets, or weak liveness enforcement, validators that should be neutralized re?-enter consensus, undermining safety assumptions and enabling stealth attacks. This paper formalizes the structural conditions enabling zombie validators, analyzes common resurrection mechanisms, and examines systemic risks to consensus integrity. We propose mitigation strategies to enforce validator lifecycle accountability and safeguard decentralized networks against stealth reactivation attacks.
Distributed ledger technologies rely heavily on consensus mechanisms to maintain a synchronized, tamper-resistant, and decentralized state across a network of mutually untrusted nodes. Conventionally, analyses of these mechanisms concentrate on cryptographic security, equilibrium in game theory, and network latency but often consider system dynamics to be linear predictable or stationary. This paper applies chaos theory to provide an integrated complex systems framework for the nonlinear, dynamic behaviors of three classical blockchain consensus paradigms: Proof of Work (PoW), Proof-of-Stake (PoS), and Byzantine Fault Tolerance (BFT). Through nonlinear feedback loops modeling transaction flows, validator behaviors, and fork-generation processes under the right boundary conditions local computational or stake centralization, sudden network propagation delays, and targeted malicious adversarial perturbations- we prove that deterministic chaos is self-generating. Employing state-space reconstructions, sensitivity analyses to initial conditions, and qualitative descriptions of phase trajectories, this work charts the transition between stable decentralized consensus phases as echoed through chaotic divergence or quasi-permanent chain splits. Results identify major flaws in classical protocols and provide principles to design the next-generation robust chaos-tolerant distributed architectures.
The finite 1-bullet silent duel is considered, involving two duelists who shoot with exponentially-convex accuracy through a uniformly quantized time. The duel is a symmetric matrix game whose optimal value is 0, and each of the duelists has the same optimal behavior, whether it is in pure or mixed strategies. The actual beginning is never optimal in the duel. Apart from the very end of the duel, the conditions for the optimal time moment existence are found. Numerical experiments confirm that the optimality can be manipulated by changing the accuracy factor that scales the payoffs. The results are applicable in systems under limited or censored communication with uncertainty, latency, and lucrative delayed actions. Some examples of such set-ups are time-sensitive information release (privacy and censorship), queueing and load balancing (information science and telecommunication systems), and block proposal timing for decentralized consensus protocols (in Proof-of-Work and Proof-of-Stake).
Steps 18 and 19 explained how blockchain uses hash puzzles (proof of work) and rewards, together with randomness, to reach consensus. However, proof of work consumes a noticeable amount of electrical energy, which in turn may have negative side effects (e.g., higher energy prices or the environmental impact of energy production). For this reason, this step will introduce you to one of the main alternatives to proof of work, that is, proof of stake. Additionally, the general idea of alternative ways to achieve consensus in blockchain systems is presented.
Decentralized applications often require reliable information about external events whose outcomes are uncertain at the time of reporting but verifiable after settlement. Existing oracle mechanisms typically rely on trusted data providers, token-weighted voting, staking, dispute games, or prediction-market incentives. These approaches may allocate influence according to wealth, identity count, or discrete votes rather than calibrated informational quality. This paper introduces Proof of Market Consistency (PoMC), an information-weighted oracle mechanism for decentralized event resolution. Admitted reporters submit probabilistic forecasts about event outcomes. Reports are evaluated ex post using strictly proper scoring rules, and each reporter accumulates information capital through a multiplicative update rule based on predictive performance. Oracle outputs are obtained by aggregating reports with information-capital weights. We establish four main properties. First, strictly proper scoring rules provide one-shot incentives for truthful probabilistic reporting. Second, under stationary reporting performance, information capital concentrates on the most accurate reporters while uninformative reporters lose influence. Third, the update rule admits an online-learning interpretation and yields a sublinear regret bound relative to the best reporter in hindsight. Fourth, because purely reputation-based systems are vulnerable to Sybil attacks, we introduce a minimal stake-gated admission rule that bounds identity creation while leaving oracle influence determined by predictive accuracy. PoMC is not a replacement for block-level consensus protocols. Rather, it is a properscoring and online-learning layer for decentralized oracle resolution. The mechanism separates economic admission from informational authority: stake limits identity creation, while calibrated predictive performance determines influence.
Information Elicitation Without Verification (IEWV) refers to eliciting high-accuracy solutions from crowd members when the ground truth is unverifiable. While prior research on IEWV has focused on central entities providing incentives to motivate effort exertion, this work explores the less-studied decentralized setting, which is increasingly relevant in machine learning, crowd decision-making, and autonomous organization applications. We model membersâ strategic interactions as a two-stage game, where each member decides her incentive contribution strategy in Stage I and her effort exertion strategy in Stage II. We examine two types of incentive allocation mechanisms: Equal Allocation (EA), where each member receives an equal proportion of the total incentives, and Output Agreement (OA), where a member receives incentives if her solution matches a reference solution generated by other members. This paper first analyzes the two-member case and provides closed-form equilibrium results. For more than two members, we use a binomial approximation to simplify the combinatorial computation of the majority voting problem and characterize the symmetric Nash equilibrium under EA. For OA, we derive equilibrium results for effort exertion and propose an algorithm for the incentive contribution game due to discontinuous payoffs. Our results show that OA outperforms EA in the aggregated team solution accuracy at equilibrium. Furthermore, we reveal that higher member ability beyond a certain threshold may lead to reduced effort exertion under EA, and that smaller teams achieve better accuracy when the effort cost is high due to less free-riding behavior. Numerical and empirical simulations validate our theory.
ZKVault is a privacy-preserving decentralized KYC system aimed at eliminating redundant identity verification and reducing the risks associated with centralized data storage. The project leverages zero-knowledge proofs and blockchain technology to enable users to prove specific identity attributes without exposing sensitive personal information. It ensures secure, tamper-proof, and reusable verification across multiple platforms while maintaining user privacy and regulatory compliance. Experimental results demonstrate efficient performance, with proof generation taking approximately 1.8 seconds and verification under 50 milliseconds, making ZKVault a scalable and practical alternative to traditional KYC systems.
Farhana Javed, Engin Zeydan, J Mangues-Bafalluy, Kapal Dev
Consumer electronics increasingly execute integrated sensingâcommunicationâcomputingâcontrol (ISCCC) loops locally, making trust, revocation, and audit at the moment of action the bottleneck. We propose an architecture that maintains action-time authorization on the household gateway while synchronizing cross-vendor trust state off-path through a permissioned trust registry. Devices do not write to the ledger; instead, the gateway periodically anchors succinct commitments (Merkle roots and policy/model digests). We implement a proof-of-concept registry on an IOTA DLT and evaluate three aspects. First, for off-path anchoring, we show that under microbursts of size-triggered commit batches the ledger time-to-confirmation remains narrow and milestone-dominated (median around 3.9â4.0 s and 95th percentile around 4.2 s at a âź10 s coordinator cadence), with no sensitivity to burst size. Second, for registry reaction, we observe that revocation reaction time scales predictably with the snapshot cadence plus a few seconds of confirmation and probing delay: tightening the snapshot period from 60 s to 15 s shifts the empirical reaction-time distributions as expected. Third, for partition tolerance, we show that across normal, impaired, offline, and recovery phases, local decision latency remains in the sub-millisecond range (with only a few milliseconds of conservative extra latency when snapshots age) and anchoring resumes within the same 1â5 s confirmation envelope once connectivity returns. Overall, the results confirm that action-time decisions remain within tens-of-milliseconds budgets, while trust synchronization is predictable and tunable. In this setting, snapshot cadences of approximately 10â15 s for âhotâ items (keys and ownership) and at least 60 s for âwarm/coldâ items (recalls and model checkpoints) provide a practical balance between revocation speed and polling cost. The open-source implementation is available at: https://github.com/ farhanajaved/PDL-Trust.
A majority of well-known blockchains supports Non-Fungible Tokens (NFTs) operations via smartcontracts. Smart contracts often allow users to store arbitrary logic and code for a small programon the blockchain, and run it on the validator nodes when a monetary transaction is made to thecontractâs account. The use of smart contracts creates extra complexity in the blockchain protocolwhen allowing concurrent smart contract execution between shards alongside monetary transactions.To reduce the complexity of the blockchain protocol, native tokens and operations could be supportedby the blockchain, albeit restricting developers to a predefined set of functions and operations. Nativetoken operations can serve as a secure complement to the versatility of Turing-complete smartcontracts, providing robust, predefined primitives that could reduce the surface area for smart contractvulnerabilities. This project introduces a native token model that is centered on unique, non-fungible tokens thatsupport three primary use cases: ownership, rights and authenticity. By requiring bilateral transferconsent, and supporting optional clawback and freeze mechanisms, for revocable rights and non-transferable tokens respectively, the model bridges the gap between blockchains and legal frameworks.Additionally, an indirect transaction cost mechanism is implemented to protect the blockchain networkagainst Denial-of-Service attack during non-monetary operations. The project is supported by an emulator implementing monetary and token operations, alongsidea implementation design of how the token protocol could be integrated within ScaleGraph. The emulatorâs throughput displays a slightly degraded performance of token transfer operations of ~150TX/s on average, compared to monetary transfers in the current implementation. Despite this, theemulator maintains a high average throughput of ~1300 TX/s with load generators of both monetaryand token transfer operations, when tested on a VPS with 2 vCPUs and 4GB of ram.If the token operation properties and performance compared to monetary transaction are transferableto ScaleGraph, native tokens could be a preferred way of implementation of tokens independentlywether or not with implementation of smart contracts.
This paper introduces DNET (Dual Network Exchange Technology), an interface architecture that unifies Settlement, Exchange, and Record generation into a single transaction structure for digital payments. Modern payment systems often treat exchange and settlement as separate backend processes, leading to fragmented identifiers, inconsistent idempotency behavior, and operational divergence across implementations. DNET resolves these issues by binding Payment Intent, Exchange Decision, and Settlement Outcome under a single TxID, enabling atomic SERâcoupling across Web2 and Web3 environments. The architecture provides a protocolâlevel foundation for multiâasset payments, ensuring traceability, auditability, and interoperability while reducing operational complexity. This work positions DNET as an OSâlayer interface for value transfer, offering a structural standard for future financial infrastructure.
Federated Learning (FL) has emerged as a distributed platform for machine learning models that ensures usersâ data privacy, however trained models are vulnerable to challenges such as unreliable clients, single points of failure (server), data poisoning, and trust issues among clients. To address these issues, DLT (Distributed Ledger Technology) offers resilience by providing transparency among clients, decentralized model aggregation, and tamper-proof transaction recording. Integrating DLT with FL not only ensures secure and verifiable model updates but also enhances fault tolerance through consensus mechanisms. This research is an attempt to explore how blockchain-based DLT architecture can strengthen the resilience of trained models by providing security and reliability in heterogeneous environments. The chapter discusses the components of the DLT-based architecture and how resilience is ensured.
The contemporary distributed systems are becoming highly dependent on strong security protocols to secure sensitive information, maintain continuity services, and sustain the trust of people in highly networked systems. With the increasingly advanced cyber threats, centralized security architectures are increasingly limited in ensuring confidentiality, integrity, and availability. This paper explores the idea of Distributed Ledger Technology (DLT) as a new security paradigm to improve trust and resiliency of distributed infrastructures. A systematic review of the literature has been done, with the establishment of a conceptual framework to serve as an assessment of how mechanisms of DLT can be applied to overcome the fundamental security issues. The review summarizes the recent empirical and theoretical research results to evaluate the efficiency of blockchain and ledger technologies associated with securing distributed systems. The findings show that classifications of immutability and cryptographic access controls in data integrity and decentralized consensus models enhance the availability and security of data, respectively. Nonetheless, trade-offs were discovered that were never previously anticipated, specifically, scalability and security. When more transaction throughput is achieved, decentralization tends to decrease, and the risk of vulnerabilities also increases. Also, energy usage and latency are significant issues for large-scale deployments. On the whole, this paper has concluded that even though DLT has significant security advantages, its implementation should be well-coordinated with system needs and operational limitations. The results provide useful advice to secure system designers who want to optimize performance, cost, and resilience of the next generation distributed environment (
Resilience is the ability of a (distributed) system to withstand any stressful situation without imposing massive restrictions and, above all, without long-term consequences. Permissioned distributed ledgers based on state machine replication (SMR) offer a promising approach to achieving high resilience and fairness in federated systems. SMR provides a fault-tolerant service for clients by relying on all replicas being in a consistent state. The consistent state is achieved through a consensus algorithm, typically an atomic broadcast, that decides on a total order of client requests. In the Byzantine fault model, replicas are assumed to be potentially malicious; a Byzantine fault-tolerant (BFT) protocol withstands a fixed share of malicious actors. Classic BFT SMR protocols require $n>3t$ replicas and multiple rounds of communication to withstand $t$ faulty replicas, making the implementation complex and limiting achievable throughput and increasing latency. Trusted Execution Environments (TEEs) allow to implement SMR in the so-called hybrid fault model in which replicas are assumed to be potentially Byzantine but the TEE is restricted to only fail by crashing. In the hybrid fault model, SMR requires less communication and can be implemented with a fault tolerance of $n>2t$ replicas. While many proposals aim to optimize BFT SMR by using TEEs, they still rely on a so-called leader that coordinates the agreement process among the replicas. The leader is known to be a bottleneck and, if it fails, the system has to recover from the failure and elect a new leader. The additional coordination required to elect a new leader can cause significant performance degradation, limiting the achieved resilience. Asynchronous protocols based on directed acyclic graphs (DAGs) eliminate the reliance on distinguished replicas by allowing all replicas to participate equally in the agreement process. While asynchronous approaches and the hybrid fault model independently contribute to increasing the resilience of BFT SMR systems, their combination has largely been unexplored. This dissertation aims to fill this gap by answering the following research question: What is the achievable performance and resilience of DAG-based, hybrid fault-tolerant state machine replication and under which preconditions can the leaderless nature be safely exploited to maximize throughput? We proceed in three steps to enhance the resilience and performance of BFT SMR systems and to identify potential trade-offs that arise from the assumption of TEEs and asynchrony in BFT SMR. First, we investigate the fit of TEE-based SMR for consortium-operated applications using the example of Mobility-as-a-Service ticketing systems. We propose an SMR application that uses TEEs to protect sensitive customer and mobility provider data while limiting possibilities for fraud by both customers and mobility providers, and ensuring correct billing. We find that as long as secure multiparty computation is not competitive in terms of performance, TEE-based SMR can provide significant advantages in terms of efficiency and resilience while providing reasonable confidentiality guarantees. We describe the characteristics of the Mobility-as-a-Service use case and identify similar use cases from other domains, e.g., central bank digital currencies, allowing us to conclude that our findings generalize. In the second step, we establish the foundation for a comprehensive analysis by proposing and proving TEE-Rider, the first hybrid fault-tolerant, asynchronous, and DAG-based atomic broadcast protocol. TEE-Rider builds upon the DAG-Rider protocol family and an optimized, DAG-aware, and TEE-based causal order broadcast we propose and prove. We then identify fundamental issues that arise from the combination of TEEs and asynchrony in BFT SMR. These are the impossibility of a fault-tolerant setup and the impossibility of garbage collection. Furthermore, we prove that for partially synchronous, TEE-based reliable broadcast it is impossible to reinitialize a TEE after a crash without relying on the participation of all $n$ replicas. We conclude the theoretical contributions with the proposal of the NxBFT SMR framework. Following an assumption-algorithm co-design, NxBFT is built upon TEE-Rider for the "Not eXactly Byzantine" (NxB) operating model to maximize throughput without sacrificing resilience. Moreover, NxBFT leverages SMR state transfer to circumvent the limitations imposed by TEEs and asynchrony and provides, under the assumption of partial synchrony, garbage collection, recovery, and reconfiguration. Finally, we contribute an extensive empirical evaluation. To this end, we develop the ABCperf evaluation framework focusing on the fair and straightforward comparison of fault-tolerant SMR and agreement protocols. We investigate the performance characteristics of NxBFT and find that cryptographic operations for signature creation and verification are the main bottleneck. We compare the performance of NxBFT with the state-of-the-art leader-based, hybrid fault-tolerant protocols MinBFT and Chained-Damysus and investigate the impact of the SMR client model (BFT vs. NxB), payload sizes, network sizes, network latencies, and crash faults. While all algorithms can benefit from the NxB client model, NxBFT achieves the highest throughput in all scenarios with up to $\sim500\,000$ requests per second. All algorithms show an improvement of the end-to-end latency when using the BFT instead of the NxB client model. When small latencies are required, MinBFT and Damysus are at an advantage with Damysus showing competitive throughput and impressively low latencies for small deployments. In contrast to leader-based approaches, NxBFT's performance is almost not impacted when actual crash faults occur.
Transaction fees are a core economic mechanism in blockchain systems, intended to price scarce blockspace and align resource consumption with economic cost. However, in Proof-of-Stake (PoS) and decentralized finance (DeFi) environments, fee mechanisms can be exploited to impose asymmetric and persistent economic harm without violating protocol rules. This paper defines <b><i>Gas Fee Drain Loops</i></b>, commonly referred to as <i>grief attacks</i>, as a class of economic exhaustion attacks that weaponize execution costs, transaction ordering, and revert semantics to drain capital from targeted participants. We analyze the structural conditions that enable such attacks, demonstrate why conventional fee market assumptions fail under adversarial strategies, and show how gas griefing degrades security through economic exclusion rather than consensus failure. Finally, we propose a logic-layer mitigation model that bounds execution costs, restores economic symmetry, and preserves open participation under adversarial conditions.