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51,074 results · page 200 of 2,129
Christoph H.-J. Braun, Jesse Wright, Tobias Käfer
No abstract is available for this record.
Rajshree Srivastava, Yugal Kumar, Kunal Kumar, Usha K · 5 authors
Disasters and pandemics have adverse effects on both lives and economies, requiring timely and adequate funding for relief efforts. However, traditional donation systems often face challenges such as funding delays and public distrust. This paper proposed Funding Blocks (FunB)s, a decentralized donation software built on the Tezos blockchain (TzBlockchain). It ensures transparency, accountability, and security in a trustless environment. Smart contracts powered by the Tezos network’s proof-of-stake consensus algorithm facilitate automatic tamper-proof execution of donation transactions. This helps in eliminating intermediaries and reducing administrative costs. The platform’s decentralized nature enhances scalability and resilience, enabling swift response to global calamities. It offers a user-friendly interface for direct contributions, incorporating mechanisms to verify and validate charitable organizations. It also provides real-time tracking of funds, ensuring transparent visibility to donors. By leveraging blockchain technology, FunBs addresses funding challenges, accelerates response times, and enhances the efficiency of disaster relief efforts. This model contributes to creating a sustainable and resilient funding ecosystem that empowers individuals and organizations to make secure and transparent contributions during crises
R. Gurunath, Debabrata Samanta, B. P. Etemi
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.
Steven Paul Nohr
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 requirements—without violating protocol rules. We argue that epoch-based accounting introduces structural risks to economic security unless continuity-enforcing safeguards are applied.
Asma Graja
No abstract is available for this record.
Daniel J. Moroz
A key scientific question underlying the blockchain ecosystem is to what extent the core security properties of the protocols hold when assuming rational validators in the presence of capable economic attackers. To what degree and at what cost can these systems be disrupted? In this thesis, I analyze the underlying economic security properties of three of the most fundamental decentralization consensus algorithms: proof of work (PoW), proof of stake (PoS), and oracle information aggregation. In Chapter 2 of this work, I counter a prominent narrative that PoW is inherently flawed in an environment in which double-spend attacks are possible. By considering counterattacks, I recover PoW robustness against reorganization attacks through a game-theoretic model. In particular, I consider hashrate markets as a potential vector of attack and show that PoW remains robust in this case. In Chapter 3 of this work, I show novel chain reorganization and finality-delay attacks on the PoS mechanism of Ethereum. These attacks are deviations from the ’honest’ staking strategy, and I show that for participants staking a substantial percentage of the network’s staked assets, these attacks can be cheap and destructive to the network. In Chapter 4 of this work, I design an incentive mechanism for the information aggregation of noisy signals that is highly resilient to bribery. I establish the asymptotic strength and limitations of this mechanism against various classes of bribery including an attacker able to condition bribes on individual reports and on the outcome of the information aggregation. I achieve strong protection even in the latter case. To do this, I assume the presence of a source of truth (SoT) that is prohibitively expensive for typical use but can be invoked infrequently. This robustness to bribes is achieved even while in equilibrium there is no invocation of the SoT.
Joshua Shen
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.
Christos Makridis, Soulla Louca, Roman Beck
Blockchain, originally developed to solve the double-spending problem in digital currencies like Bitcoin, has evolved into a foundational technology with broad applications across public and private sectors.Its key features-immutability, decentralized trust, and cryptographic security-enable authenticated data sharing without the need for a central authority.This is particularly valuable in systems like supply chains, where participants may not know or trust each other.Smart contracts further enhance blockchain's utility by automating agreements through code, reducing uncertainty and fostering trust among stakeholders.The rise of the decentralized web, combined with emerging technologies like IoT, AI, and AR/VR, signals a wave of disruptive innovation whose full impact is yet to be seen.Given the rapid pace of development, academic research is essential to understand and guide blockchain's evolution.Conferences are especially important for timely knowledge dissemination, as they can keep up with the fast-moving nature of the field better than traditional journals.This mini-track builds on a series of successful sessions from HICSS conferences (HICSS-51 through HICSS-58), which have focused on blockchain's impact in areas such as fintech, transformation, and innovation.Over the years, it has served as a valuable forum for exploring blockchain technology and its implications for process improvement and innovation.For the current edition, six accepted papers contribute to expanding the academic understanding and supporting broader adoption of blockchain solutions.The first paper, "Playing Strategic Games in The Open Network (TON): Analyzing the Robustness of Proof-of-Stake Slashing Incentives", by Sascha Hgele, analyzes how rational validators in the TON blockchain respond to slashing penalties in a proof-of-stake system.Using a game-theoretic model, it reveals that when penalty enforcement is uncertain, validators strategically weigh risks and rewards, which impacts
Pankhuri Gupta, Akshat Sinha, Harsh Rawat, Aaditya Kumar Jha · 5 authors
No abstract is available for this record.
Divesh Sarkar, Manish Sarkar
No abstract is available for this record.
Zulkarnain Muhamad Sori, Damar Hulan Osman, Mohamad Nazzeer Hamzah
No abstract is available for this record.
Octavian Untila
Current approaches to verifying AI training data compliance face a fundamental tension: copyright holders need to know whether their content was used in training (EU AI Act, Article 53(1)(d)), while model providers need to protect their training data as trade secrets (GDPR, trade secret law). Existing zero-knowledge proof systems for machine learning (ZKML) address this partially by providing proofs of non-membership for exact data points. However, real-world training pipelines involve tokenization, chunking, paraphrasing, and augmentation, rendering exact-match proofs insufficient. We identify a gap in the literature: no existing system combines semantic fingerprinting with zero-knowledge proofs to enable semantic non-membership verification. We propose an architecture for Zero-Knowledge Semantic Non-Membership (ZK-SNM) that enables a model provider to prove, without revealing any training data, that no document in their training corpus is semantically similar to a queried document above a specified threshold. We discuss the technical challenges, including the computational cost of similarity search within ZK circuits, and propose mitigation strategies based on locality-sensitive hashing and hierarchical verification. This position paper establishes the problem formulation and proposed architecture; experimental validation is left to subsequent work.
Nai‐Wei Lo, Cheng-I Lin, Chih-Chieh Chang, Chi-Yang Chang · 5 authors
The growing frequency of malicious attacks on Internet of Things (IoT) devices has rendered conventional approaches with static label-dependent risk assessment models obsolete, especially when coping with unknown and continuo... | Find, read and cite all the research you need on Tech Science Press
Christopher Schulze
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.
Priya Patel, Nitesh Sureja
Ensuring transparency, security, and privacy in agricultural food supply chains is critical for maintaining consumer trust, regulatory compliance, and data integrity. Traditional centralized traceability systems suffer from several limitations, including data tampering risks, single-point failures, and potential privacy leakage. To address these challenges, this research proposes a privacy-preserving blockchain-based traceability framework that integrates the InterPlanetary File System (IPFS) with Zero-Knowledge Proofs (ZKPs). The framework leverages the Ethereum blockchain for immutable record-keeping, while zk-SNARK-based proofs enable compliance verification without revealing sensitive underlying data. A prototype was implemented using Solidity smart contracts and Python-based zk-SNARK circuits. Experimental evaluation across varying record sizes, from 50 to 200, demonstrates high security and efficiency, achieving 100% success in detecting simulated tampering attempts. Performance metrics indicate a highly scalable system with an average end-to-end latency of approximately 0.33 seconds, rapid proof generation times of approximately 0.0002 seconds, and near-constant verification times averaging 0.027 seconds. Furthermore, the system maintains a consistent simulated transaction cost of 20.40$ per proof, regardless of the total records processed. Overall, the proposed approach provides a robust, scalable, and computationally efficient solution for modern agri- food supply chains, successfully balancing data confidentiality with rigorous cryptographic integrity.
Hideaki Miyaji, Hayato Takayama, Hiroshi Yamamoto
Digital systems increasingly rely on user location data, raising significant privacy concerns. This study proposes a privacy-preserving location data utilization system that eliminates the need for dedicated base stations by integrating blockchain technology with zero-knowledge proof scheme. Our system converts data from smartphone trajectory data into zero-knowledge proof values and records only these proof values on the blockchain. Thus, the system enables verification of user movement without revealing sensitive information. By integrating the entire process with smart contracts on the blockchain, our system automates transaction processing and monetary transfers without relying on any specific organization. We conduct an experimental evaluation on the blockchain using trajectory data collected from a smartphone application.
Pankaj Kumar, Arun K H, Yogesh N, Prakash Babu · 8 authors
The growing dependance on data-based decisionmaking in healthcare has brought attention to the vital importance of secure, privacy-preserving and collaborative learning techniques. Traditional centralized learning approaches in medical data often raise concerns regarding patient privacy data leaks and even regulatory troubles. Federated learning came as a good solution, where it allows model training in different hospitals without sharing the sensitive patient data. However, federated learning has its problems - it can be mislead with fake updates, the model can even be poisoned and it is really hard to trust every participants involved. In this work, we present fed-chain, a secure and scalable framework which brings together federated learning, blockchain and zero-knowledge-proofs(ZKPs) preserving the privacy of patient's data in healthcare. Blockchain here adds decentralized trust, immutability and makes model updates transparent to review while ZKPs helps in proving correctness without leaking personal data. We are implemented this framework for heart disease prediction where multiple hospitals train the model together but the data stays confidential. Our experimental results shown better accuracy, more strength against attacks and even low communication cost compared to other FL setups. Overall, the systems gives a safer approach for working together on healthcare data, allowing hospitals and research centers to generate valuable predictions using these models while keeping the patient data private and safe.
Steven Paul Nohr
Airdrops are widely used in blockchain ecosystems as mechanisms for token distribution, user bootstrapping, and governance decentralization. These mechanisms frequently rely on balance or stake snapshots taken at specific blockchain heights or epochs to determine eligibility. However, snapshot-based distribution introduces a critical temporal vulnerability: the assumption that momentary state accurately represents sustained economic participation.This paper defines and analyzes <b><i>Airdrop Snapshot Spoofing</i></b>, a class of temporal state manipulation attacks in which adversaries exploit the gap between snapshot definition, execution, and settlement to illegitimately capture token allocations. We demonstrate that such exploits are not edge cases but structural weaknesses inherent to snapshot-based systems across Proof-of-Stake (PoS) and tokenized networks. We further argue that snapshot spoofing represents a core-layer economic security failure rather than a marketing or distribution flaw, and we outline mitigation strategies based on time-weighted enforcement and validator-level continuity checks.
Steven Paul Nohr
<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.
ANDERSON J
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.
Vadim Romanuke
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).
Vikas Reddy Mandadhi
No abstract is available for this record.
Mohammad Fairus Bin Zulkifli, Rabiah Abdul Kadir, mohamad nazir ahmad
Growing reliance on digital knowledge sharing across academic, corporate, and public sectors has raised serious concerns about data integrity, trust, and security. Blockchain consensus mecha-nisms offer a promising path forward through decentralized, transparent, and tamper-proof frameworks. This systematic review examines how these mechanisms enhance trust in knowledge sharing platforms, focusing on four directions: how these mechanisms are applied within knowledge sharing con-texts, the challenges they introduce for knowledge sharing de-ployment, and the advantages they provide to trust-based knowledge sharing ecosystems. Following PRISMA 2020 guide-lines, three databases Scopus, IEEE Xplore, and Web of Science were searched, and peer-reviewed studies published between 2020 and 2025 were selected for analysis. In terms of knowledge sharing applications, blockchain consensus mechanisms build trust through multiple co-occurring pathways, including distrib-uted verification, transparency, cryptographic security, immu-tability, incentive alignment, and smart contract automation. Algorithms such as Proof of Work, Proof of Stake, Delegated Proof of Stake, and Byzantine Fault Tolerance variants are widely adopted, each offering different trade-offs between secu-rity, efficiency, and scalability. In terms of challenges, scalabil-ity, energy consumption, and integration complexity with exist-ing systems remain the most significant barriers to adoption. In terms of advantages, blockchain consistently delivers stronger data security, greater transparency, and reduced dependence on centralized authorities across knowledge sharing contexts. This review concludes that blockchain consensus mechanisms offer layered and compounding trust benefits, yet technical and or-ganizational barriers continue to limit widespread deployment. Future research should focus on energy-efficient protocols, scalable architectures, and real-world effectiveness studies.
Moin A. Yahya, Erwin Kwok
When Ethereum (ETH) shifted from a Proof of Work (PoW) protocol to a Proof of Stake (PoS) protocol, not all users were enthused. We use Ethereum’s shift from PoW to PoS as a case study for the broader question of whether developers of a blockchain owe its members certain fiduciary or fiduciary-like duties. We argue that if done properly, in accordance to the rules governing the blockchain, then developers do not necessarily owe fiduciary responsibility to other members of the chain, but they nonetheless may owe fiduciary-like responsibilities to users inadvertently and negatively impacted. We argue these users may be entitled to an oppression claim akin to what minority shareholders may be entitled to in the corporate law context.