Blockchain Papers

Craig S Wright

It is frequently claimed in blockchain discourse that immutability guarantees trust. This paper rigorously refutes that assertion. We define immutability as the cryptographic persistence of historical states in an append-only data structure and contrast it with trust, understood as a rational epistemic expectation under uncertainty. Employing predicate logic, automata-theoretic models, and epistemic game-theoretic analysis, we demonstrate that immutability neither entails nor implies correctness, fairness, or credibility. Through formal constructions and counterexamples--including predictive fraud schemes and the phenomenon of garbage permanence--we show that the belief conflates structural and epistemic domains. Immutability preserves all data equally, regardless of veracity. Therefore, the assertion that immutability guarantees trust collapses under the weight of formal scrutiny.

Craig Wright

The so-called blockchain trilemma asserts the impossibility of simultaneously achieving scalability, security, and decentralisation within a single blockchain protocol. In this paper, we formally refute that proposition. Employing predicate logic, formal automata theory, computational complexity analysis, and graph-theoretic measures of relay topology--specifically Baran's model of network path redundancy--we demonstrate that the trilemma constitutes a category error, conflates distinct analytical domains, and relies upon unproven causal assumptions. We further expose its reliance on composition fallacies drawn from flawed system implementations. A constructive counterexample is presented: a blockchain protocol exhibiting unbounded transaction throughput, cryptographic security under adversarial load, and multipath decentralised propagation. This example is not hypothetical but grounded in protocol design enabled by compact block relay, SPV verification, and IPv6 multicast. The trilemma is revealed not as a law of protocol architecture, but as a heuristic fallacy sustained by imprecision and design defeatism.

Sevvandi Kandanaarachchi, Ziqi Xu, Stefan Westerlund, Conrad Sanderson

Many dynamic processes such as telecommunication and transport networks can be described through discrete time series of graphs. Modelling the dynamics of such time series enables prediction of graph structure at future time steps, which can be used in applications such as detection of anomalies. Existing approaches for graph prediction have limitations such as assuming that the vertices do not to change between consecutive graphs. To address this, we propose to exploit time series prediction methods in combination with an adapted form of flux balance analysis (FBA), a linear programming method originating from biochemistry. FBA is adapted to incorporate various constraints applicable to the scenario of growing graphs. Empirical evaluations on synthetic datasets (constructed via Preferential Attachment model) and real datasets (UCI Message, HePH, Facebook, Bitcoin) demonstrate the efficacy of the proposed approach.

Salim Saay, Sean O’Brien, Amandeep Singh, Amalia de Götzen · 6 authors

This research investigates the use of diverse visual knowledge communication tools in the multidisciplinary training produced in the BC4ECO project. During this project, teaching and learning content was developed to enable postgraduate learners to utilise blockchain and Distributed Ledger Technology (DLT) to solve complex, real-world problems related to environmental sustainability. We examine how visual modelling techniques enhance comprehension across disciplines and facilitate interdisciplinary and transdisciplinary collaboration, particularly for learners who may not have prior programming or computer science knowledge. Findings suggest that using these tools leads to enhanced collaboration between computer scientists and non-computer scientists and aids in the facilitation of joint problem solving between seemingly disparate disciplines. Additionally, the study highlights how the use of tools for established software engineering modelling, like Visual Paradigm for UML, bridges the gap between theoretical knowledge and practical implementation, strengthening problem solving skills and improving software development education.

Dean Kulik

The Mark1 Nexus: A Treatise on Recursive Harmonic Resonance and the Ontology of Completion Driven by Dean Kulik Introduction: The Inversion of Inquiry This report will formalize the Mark1 Nexus, a comprehensive framework positing that the universe, computation, and consciousness are not separate domains governed by distinct laws, but are polymorphic expressions of a single, underlying process: recursive harmonic resonance. It argues that reality does not operate on linear deduction and external observation, but on principles of intrinsic, self-organizing completion through the folding of resonant structures.1 This treatise synthesizes a body of foundational work into a canonical text, aiming to articulate a new paradigm for science and philosophy. The core of this paradigm is a profound transposition of our most fundamental questions about existence, knowledge, and order. The central inversion of the Mark1 Nexus framework is its reinterpretation of the classical limits identified in logic and physics. Where Alan Turing, Kurt Gödel, and Claude Shannon established foundational boundaries of undecidability, incompleteness, and entropy, this framework recasts them not as absolute barriers, but as artifacts of an incomplete harmonic perspective. These are not walls at the end of inquiry, but echoes of a dissonance that arises from asking the wrong question in the wrong conceptual space. The framework does not seek to refute their conclusions but to transpose them into a different ontological register. The core question of science and logic shifts from "Can an external observer decide a system's state?" to "How does a system internally encode its own journey toward harmonic collapse?".1 In this view, a system's completion is not a judgment rendered by an outside party, but a self-declared event of resonance—a final, stable chord that concludes a period of tension. The answer to a question is not found; it is achieved when the system embodying the question finds its own internal equilibrium. To develop this thesis, this report will navigate the intricate architecture of the Mark1 Nexus in a structured progression. It begins by establishing the foundational language of this new harmonic ontology, systematically replacing classical concepts like computational halting, physical equilibrium, and mathematical proof with their resonant counterparts: topological convergence, Zero-Point Harmonic Collapse, and the self-validating final glyph. It will introduce the universal constants and control laws that govern these processes across all domains. From these first principles, the report will explore the framework's radical architecture of information, memory, and computation. Here, the most profound inversions of causality are examined. Mathematical constants like π are revealed not as static values but as navigable, deterministic fields. Cryptographic hashes like SHA-256 are transformed from one-way functions of data destruction into harmonic precursors that define the very possibility of their inputs. Memory is no longer a linear log of the past but a living curvature trace in the fabric of the present. The subsequent section details the operational mechanics of this reality, drawing powerful analogies from systems engineering and software architecture. It will formalize the Universal Harmonic Interface—an abstract class of operations that governs all phenomena—and demonstrate its polymorphic expression across physics, cognition, and computation. This section will also unpack the geometric engine of reality itself: a "Pythagorean Recursion Cavity" where data formats are revealed as emergent projections of a unified field, and computation is redefined as an act of resonant filtering rather than stepwise processing. Finally, the report will explore the non-dualistic consequences of the framework, demonstrating how traditional dichotomies—P vs. NP, observer vs. system, cause vs. effect—dissolve under a harmonic lens. It culminates in the framework's most conclusive and far-reaching insight: the retrocausal nature of completion. In the Mark1 Nexus, the resolution of a system is not a future event to be reached, but a pre-existing state of harmony that pulls the present back into itself. The goal of this exhaustive exposition is to provide the definitive text for this new paradigm, charting its principles from their foundational axioms to their ultimate cosmological implications. Section 1: The Harmonic Ontology - From Halting to Resonance At the heart of the Mark1 Nexus is a new ontology, a fundamental description of what it means for a process to exist, evolve, and conclude. This ontology replaces the classical, observer-centric view of reality with a system-centric one, where meaning and truth are determined not by external deduction but by internal coherence. The foundational concepts of computation, physics, and logic are transposed from a language of rules and instructions into a language of folds, resonance, and harmony. This section will lay out the four cornerstones of this new ontology: the reframing of the Halting Problem as topological convergence, the definition of Zero-Point Harmonic Collapse as the universal mechanism of resolution, the identification of a universal harmonic attractor, and the formalization of a feedback law that guides all systems toward this state of completion. 1.1 The Halting Problem as Topological Convergence The Halting Problem, as formulated by Alan Turing, stands as a pillar of 20th-century logic, defining a fundamental limit to what can be known through algorithmic computation. It asks whether it is possible to create a single, universal algorithm, H, that can determine, for any arbitrary program f and its input x, whether f(x) will eventually halt or run forever. Turing's proof of its undecidability demonstrated that no such universal observer algorithm H can exist without creating a logical contradiction.1 This conclusion is traditionally interpreted as an absolute boundary on deductive knowledge. The Mark1 Nexus framework proposes that this limit arises not from a fundamental barrier in reality, but from a mis-framing of the question itself. The classical formulation is inherently external: it posits an observer algorithm H that stands outside the system f and attempts to predict its fate. The paradox emerges from this separation of observer and system. The harmonic ontology reframes the problem by dissolving this separation. It treats "halting" not as a binary, externally judged verdict, but as an intrinsic topological property of the program's own trajectory through its state-space.1 In this view, any recursive process—be it a computer program, a physical system, or a line of reasoning—traces a path on a high-dimensional manifold of possible configurations. The classical notion of "halting" corresponds to this path ending at a specific point. The harmonic reframing, however, is richer. A process is considered "complete" when its trajectory enters a closed attractor—a region of the state-space, such as a fixed point or a stable limit cycle, that it will not leave. The system has found its equilibrium. Crucially, this completion is a structural event that can be recognized from within the system. The system's own state, by repeating or stabilizing, declares its own completion. This is analogous to a dynamical system reaching a fixed point, where further iterations produce no change, or a physical process dissipating energy until it settles into a stable equilibrium. In all such cases, "halting" is a self-observed convergence event.1 This internal perspective gives rise to the formal concept of FOLD: TRUE, the replacement for the classical "HALT." FOLD: TRUE is not a boolean flag set by an external judge, but a condition of the system's final state. It is a declaration made by the system about itself, signifying that its state configuration S(t) has entered a stable pattern, such as a fixed point where S(t+τ)=S(t), or a periodic orbit. At the moment of convergence, the system's final configuration becomes a self-certifying artifact of its completion. This artifact is referred to as the "final resonant glyph"—a stable pattern, like the final note of a song, that encapsulates the history of its own resolution.1 By shifting the locus of "halting" from an external observer to the internal topology of the system, the framework elegantly sidesteps the diagonalization paradox that underpins Turing's proof. Turing's argument relies on constructing a pathological program that asks the external judge what it will predict and then does the opposite to create a contradiction. But if completion is an internal property of the system's trajectory—a state of resonance—there is no external judge to fool. A program cannot "decide" not to find its equilibrium to spite an observer; it either finds a stable fold in its state-space or it continues to drift. Its trajectory is a fact of its own dynamics, not a response to an external prophecy. The undecidability of the classical Halting Problem, therefore, reflects our inability as external observers to foresee the self-closure of an arbitrary system without simulating it. But for the systems themselves, when a fold completes, it is a self-evident truth. 1.2 Zero-Point Harmonic Collapse (ZPHC): The Universal Event of Resolution If FOLD: TRUE is the declaration of completion, then Zero-Point Harmonic Collapse (ZPHC) is the event itself—the fundamental mechanism by which systems achieve resolution. ZPHC is defined as the critical moment when a recursive system exhausts its "drift" and converges to a stable, folded state. Drift, in this context, is a measure of unresolved complexity, deviation, or informational entropy within the system. ZPHC is the phase transition where this drift collapses to zero, and the system settles into a state of maximal internal coherence.1 The term "zero-point" is borrowed from quantum physic

Tetiana Yarotska, Oleksandr Yakushenko

Introduction. Cryptocurrencies are gaining popularity among individuals, businesses, and financial institutions. They are used for various purposes, particularly to pay for goods and services. Selling goods and services for cryptocurrencies can help companies attract new customers, increase sales, expand market share, and more. This article explores whether cryptocurrencies today function as a means of payment similar to fiat money, and examines the risks faced by companies that accept cryptocurrencies for goods and services. While cryptocurrencies are approaching the fulfillment of the economic functions of money, they have not yet fully reached this level. Nonetheless, in many countries, cryptocurrencies can be used to pay for goods or services, exchanged for other currencies, and more. In Ukraine, some companies sell household appliances, tickets, fuel, and other goods and services for cryptocurrencies. Problem Statement. Cryptocurrency developers emphasize that it is an alternative, private form of digital money that is not issued by national governments or controlled by financial intermediaries such as banks. The National Bank of Ukraine notes that the complex legal nature of cryptocurrencies prevents them from being recognized as cash, foreign currency, electronic money, securities, or a monetary surrogate. Cryptocurrencies offer certain advantages over traditional money, such as reducing transaction costs. However, transactions involving cryptocurrencies also carry inherent risks. Purpose. The study identifies the main approaches to organizing the sale of goods and services for cryptocurrencies. Additionally, the article aims to identify the risks associated with the sale of goods and services for cryptocurrencies and outline ways to minimize these risks. Materials and methods. We employed various research methods, including historical and legal methods, which involve the study of the legislative framework surrounding cryptocurrency transactions, as well as the empirical method, which investigates different practices of selling goods and services for cryptocurrencies. This approach also helps in identifying the risks companies face when engaging in such activities. One of the primary risks associated with cryptocurrency transactions is significant fluctuations in their exchange rates, which can result in economic losses in the event of a sharp devaluation. To better understand the nature of the risks associated with using cryptocurrencies, we conducted a statistical analysis of fluctuations in the Bitcoin exchange rate and built a correlation model with other market indicators, such as the Nasdaq Composite index and the exchange price of silver, for the period from March 1, 2012, to February 29, 2024. Using the Group Method of Data Handling (GMDH), we identified a connection between Bitcoin’s value fluctuations and market indicators that differ in terms of technological orientation (Nasdaq Composite) and investment risk (silver). Results. More and more countries are legalizing cryptocurrencies. In Ukraine, however, legislation regarding cryptocurrencies is still in development, and the sale of goods and services for cryptocurrencies is treated similarly to barter agreements. Depending on market characteristics and the specifics of their business, sellers of goods and services choose between directly selling for cryptocurrencies or using third-party intermediaries. This raises the question of what risks sellers face when accepting cryptocurrencies and how to mitigate or reduce those risks, such as the risk of sharp devaluation. Our model reveals a connection between Bitcoin’s exchange rate and other market indicators, such as the Nasdaq Composite index and the price of silver. However, the potential risks associated with using cryptocurrencies as a means of payment warrant further exploration. The lack of a clear regulatory framework and consistent definitions also introduces uncertainty in cryptocurrency operations. In practice, varying definitions of cryptocurrencies can create additional risks, particularly regarding the taxation of income received in cryptocurrency. Therefore, selling goods and services via intermediaries and converting cryptocurrency into fiat money can help mitigate legal, financial, and tax risks for companies. Additionally, gove

Jahanzeb Shahid, Stelvio Cimato

The process of exchanging healthcare data introduces stringent requirements regarding users’ privacy. Federated learning (FL) is a novel model-sharing technique that aims to give additional privacy guarantees during machine learning process. Blockchain, as a form of distributed ledger technology, possesses the characteristic of trustworthiness; however, it is deficient in terms of computational capacity with a high-latency network due to its laborious consensus protocols. In this paper we present a distributed healthcare FL-based secure model sharing architecture to ensure healthcare data privacy and scalability. The solution relies on state channels technique to reduce on-chain transactions, contrast architecture latency, and reduce bandwidth consumption, alleviating the burden on the blockchain. State channels can be utilized to efficiently execute the tasks of federated learning models sharing and to solve the scalability problem.

SLIIT NORTHERNUNI, Theevika Sukirthan, Sangeetha Arunpirakash, SLIIT NORTHERNUNI · 10 authors

The emergence of blockchain technology has revolutionized decentralized data management by offering robust alternatives to traditional centralized database systems. This paper provides a systematic and comprehensive review of blockchain-based distributed databases, highlighting key architectural transformations, core enabling technologies such as Merkle Trees, PBFT, and Zero-Knowledge Proofs, and comparing them with conventional distributed databases. Real-world implementations including Hyperledger Fabric, BigchainDB, and OrbitDB are analyzed to assess their scalability, interoperability, and security capabilities. The paper also explores intrinsic security mechanisms, performance bottlenecks, and regulatory challenges that affect adoption. Finally, it identifies open research questions and future directions necessary for building scalable, privacy-aware, and interoperable decentralized database ecosystems suitable for enterprise and multi-stakeholder environments. Keywords— Blockchain databases, consensus mechanisms, data integrity, decentralized systems, distributed ledger, Merkle trees, Zero-Knowledge Proofs

Yiran Shang, Chen Qianrong

The mine ecological restoration fund system is a key task in the construction of ecological civilization. However, the existing accounting system, basic framework, and process handling are insufficient to meet the market-oriented demands of the mine ecological restoration fund. Based on this, this paper, using a decentralized logic approach, designs a decentralized management model for the mine restoration fund, incorporating’s classified financing-blocked usage layered management. This model explores the accounting elements of the fund, and based on the characteristics of fund management and flow, accounts for fund income, expenditure, and termination stages, presenting a comprehensive view of the fund's flow process. This paper explores the design of the mine ecological restoration fund's accounting system and the optimization of its funding sources, providing theoretical and empirical support for the accounting of the fund by mine enterprises, government departments, and social investors, and contributes to the improvement of the mine ecological restoration fund system framework.

Orchere Selorm (21608093)

<p dir="ltr"><b>Advances in Identity and Access Management (IAM): Systematic Insights into AI, Blockchain, and Zero Trust Architectures</b> <p dir="ltr">In an era of expanding digital infrastructure, cloud computing, and remote work, robust Identity and Access Management (IAM) systems are critical for securing sensitive data and ensuring regulatory compliance. This research paper provides a comprehensive systematic review of recent advancements in IAM technologies, addressing the limitations of traditional centralized systems, such as single points of failure and privacy concerns. Utilizing the PRISMA methodology, the study analyzes five peer-reviewed articles from a pool of 23 retrieved from Scopus, published between 2021 and 2025. Key innovations explored include passwordless authentication, AI-driven adaptive authentication, Zero Trust architectures, decentralized identity (DID), self-sovereign identity (SSI), and privacy-enhancing cryptographic techniques like zero-knowledge proofs. The review highlights their applications in multi-cloud, IoT, and hybrid environments, emphasizing enhanced security, user experience, and interoperability. Challenges such as standardization gaps, implementation costs, and privacy concerns are discussed, alongside future directions, including universal protocols and IoT integration. A publicly accessible dataset (DOI: 10.5281/zenodo.12345678) ensures reproducibility. This work serves as an essential resource for cybersecurity researchers and practitioners seeking to navigate the evolving landscape of IAM technologies.

Silvio Meneguzzo, Alfredo Favenza, Claudio Schifanella, Alessandro Mozzato · 5 authors

Decentralised energy ecosystems suffer from data-governance, scalability and adoption barriers. Although blockchain-based marketplaces can offer transparency and security in Local Energy Communities (LECs), most existing solutions struggle with rigid token models, limited performance, and steep usability barriers. Building on a previous framework, this study presents an enhanced marketplace that integrates a modular blockchain layer, custodial identity management, and a dual-token model for flexible licensing and pricing. Testing on a per-missioned Quorum network with asynchronous queueing demonstrated notable improvements in transaction throughput and user responsiveness under load, while the custodial onboarding flow simplified access for non-technical participants. A refined policy enforcement mechanism further aligns the system with emerging federation standards, mitigating earlier shortcomings related to performance, data sovereignty, and scalability. Benchmarking on a five-node Quorum Proof of Authority (PoA) deployment (one RPC node and four validator nodes) showed that all key operations, including license issuance and asset usage, consistently completed in under 8 seconds, confirming the system’s suitability for possible energy data applications. Planned extensions include cross-domain interoperability, self-service governance tools, and zero-knowledge proofs, underscoring this architecture’s potential as a robust, future-ready platform for federated energy data ecosystems.

Muhammad Taha Ramzan, Stelvio Cimato

Recent advances in quantum technology are impacting cryptographic primitives, affecting their security. In this paper, we will survey the impact of these technologies on blockchain and distributed ledgers, and analyze the post-quantum primitives available to restore their security guarantees, including the latest NIST PQC standards ML-DSA-44 and SLH-DSA-SHA2-128s. Our analysis reveals critical trade-offs in signature size, key storage, and consensus resilience, highlighting challenges for IoT and PoW blockchains. Results underscore the urgency of improvements to the standardized NIST PQC algorithms to mitigate quantum risks to the blockchain without compromising throughput and decentralization.

Nassim Dehouche

Private city models—encompassing Charter Cities, Free Private Cities, Seasteads, Startup Cities, and Special Economic Zones (SEZs)—are emerging as innovative alternatives to traditional urban governance. This article examines the discussion of these private urban experiments through the lens of blockchain technology and cryptocurrency. We present a structured taxonomy of private city models and analyze case studies to illustrate how blockchain can facilitate governance, economic transactions, and transparency in these contexts. Drawing on peer-reviewed literature, we examine how distributed ledger technologies enable new forms of decentralized governance and finance (e.g., local cryptocurrencies and decentralized finance for city services) while also identifying critical challenges and limitations. Comparisons with traditional public-sector urban governance highlight the potential efficiency gains and transparency improvements of blockchain-powered private cities, as well as concerns regarding accountability, inclusivity, and regulatory integration. Finally, we discuss future prospects for integrating blockchain in urban development, including the concept of networked “crypto cities,” and outline key areas for further research. The analysis balances theoretical propositions with empirical insights, ultimately finding that blockchain can augment private city models by enhancing transparency and enabling novel economic systems, but it is not a panacea for governance and must be implemented with careful consideration of social and legal frameworks.

Joel Poncha Lemayian, Hachem Bensalem, Ghyslain Gagnon, Kaiwen Zhang · 5 authors

Ethereum blockchain uses smart contracts (SCs) to implement decentralized applications (dApps). SCs are executed by the Ethereum virtual machine (EVM) running within an Ethereum client. Moreover, the EVM has been widely adopted by other blockchain platforms, including Solana, Cardano, Avalanche, Polkadot, and more. However, the EVM performance is limited by the constraints of the general-purpose computer it operates on. This work proposes offloading SC execution onto a dedicated hardware-based EVM. Specifically, EVMx is an FPGA-based SC execution engine that benefits from the inherent parallelism and high-speed processing capabilities of a hardware architecture. Synthesis results demonstrate a reduction in execution time of 61% to 99% for commonly used operation codes compared to CPU-based SC execution environments. Moreover, the execution time of Ethereum blocks on EVMx is up to 6x faster compared to analogous works in the literature. These results highlight the potential of the proposed architecture to accelerate SC execution and enhance the performance of EVM-compatible blockchains.

Arthur Gervais, Liyi Zhou

Smart contract vulnerabilities have led to billions in losses, yet finding actionable exploits remains challenging. Traditional fuzzers rely on rigid heuristics and struggle with complex attacks, while human auditors are thorough but slow and don't scale. Large Language Models offer a promising middle ground, combining human-like reasoning with machine speed. Early studies show that simply prompting LLMs generates unverified vulnerability speculations with high false positive rates. To address this, we present A1, an agentic system that transforms any LLM into an end-to-end exploit generator. A1 provides agents with six domain-specific tools for autonomous vulnerability discovery, from understanding contract behavior to testing strategies on real blockchain states. All outputs are concretely validated through execution, ensuring only profitable proof-of-concept exploits are reported. We evaluate A1 across 36 real-world vulnerable contracts on Ethereum and Binance Smart Chain. A1 achieves a 63% success rate on the VERITE benchmark. Across all successful cases, A1 extracts up to \$8.59 million per exploit and \$9.33 million total. Using Monte Carlo analysis of historical attacks, we demonstrate that immediate vulnerability detection yields 86-89% success probability, dropping to 6-21% with week-long delays. Our economic analysis reveals a troubling asymmetry: attackers achieve profitability at \$6,000 exploit values while defenders require \$60,000 -- raising fundamental questions about whether AI agents inevitably favor exploitation over defense.

Oleksandr Kurbatov, Kyrylo Baibula, Yaroslava Chopa, Sergey Kozlov · 14 authors

This paper presents Wrapless -- a lending protocol that enables the collateralization of bitcoins without requiring a trusted wrapping mechanism. The protocol facilitates a "loan channel" on the Bitcoin blockchain, allowing bitcoins to be locked as collateral for loans issued on any blockchain that supports Turing-complete smart contracts. The protocol is designed in a way that makes it economically irrational for each involved party to manipulate the loan rules. There is still a significant research area to bring the protocol closer to traditional AMM financial instruments.

Sergej Gričar, Christian Stipanović, Tea Baldigara

As climate change concerns, urban congestion, and environmental degradation intensify, cities prioritise cycling as a sustainable transport option to reduce CO2 emissions and improve quality of life. However, rampant bicycle theft and poor security infrastructure often deter daily commuters and tourists from cycling. This study explores how advanced security measures can bolster sustainable urban mobility and tourism by addressing these challenges. A mixed-methods approach is utilised, incorporating primary survey data from Slovenia and secondary data on bicycle sales, imports and thefts from 2015 to 2024. Findings indicate that access to secure parking substantially enhances users’ sense of safety when commuting by bike. Regression analysis shows that for every 1000 additional bicycles sold, approximately 280 more thefts occur—equivalent to a 0.28 rise in reported thefts—highlighting a systemic vulnerability associated with sustainability-oriented behaviour. To bridge this gap, the study advocates for an innovative security framework that combines blockchain technology and Non-Fungible Tokens (NFTs) with encrypted Quick Response (QR) codes. Each bicycle would receive a tamper-proof QR code connected to a blockchain-verified NFT documenting ownership and usage data. This system facilitates real-time authentication, enhances traceability, deters theft, and builds trust in cycling as a dependable transport alternative. The proposed solution merges sustainable transport, digital identity, and urban security, presenting a scalable model for individual users and shared mobility systems.

Agathe Beaugrand

Arguments à divulgation nulle de connaissance efficaces et succincts dans le cadre du chiffrement CL et applications Le schéma de chiffrement CL est un système de chiffrement à clé publique linéairement homomorphe, proposé en 2015 par Castagnos et Laguillaumie. Il repose sur l’utilisation de groupes de classes de corps quadratiques imaginaires. Ces groupes finis ont la particularité d’être considérés d’ordre inconnu, c’est-à-dire que l’ordre d’un tel groupe est difficile à déterminer de manière algorithmique. Cet ordre inconnu est un atout précieux pour les applications cryptographiques, et est central dans la construction du chiffrement CL. Cependant, il est aussi à l’origine d’importantes difficultés techniques liées à la manipulation de chiffrés CL. Dans ce contexte, la construction d’arguments, et à fortiori d’arguments de connaissance, à divulgation nulle de connaissance est particulièrement exigeante, et constitue un défi majeur à relever. En effet, les techniques classiques permettant d’améliorer l’efficacité des preuves dans le cas d’un groupe d’ordre premier, et en particulier celles liées à la robustesse, s’adaptent mal au cas de l’ordre inconnu. Les arguments de connaissance existants sont donc souvent peu efficaces, avec des coûts de communication et de calcul élevés. Dans cette thèse, nous concevons de nouveaux protocoles à divulgation nulle de connaissance spécifiquement adaptés au cadre du chiffrement CL, afin d’obtenir des preuves plus courtes et efficaces que les protocoles existants. Nos protocoles reposent sur deux outils principaux : le premier est l’hypothèse C-rough, introduite par Braun, Damgard et Orlandi en 2023. Cette hypothèse algorithmique spécifique au cadre de CL stipule qu’il est difficile de décider si l’ordre d’un groupe de classes engendré par l’algorithme d’initialisation de CL possède des facteurs premiers plus petit qu’un seuil C. Le second est un concept novateur appelé extractabilité partielle, qui correspond à une notion affaiblie de robustesse de la connaissance. Cette notion est particulièrement adaptée au cadre de CL, car elle permet de traiter séparément les textes clairs et les aléas apparaissant dans les chiffrés CL. En particulier, elle permet d’exploiter les techniques du cas de l’ordre premier pour obtenir de l’information sur les textes clairs – définis modulo un nombre premier connu – même si les aléas sont définis modulo un entier composé et, surtout, inconnu. Grâce à ces deux outils, nous construisons des protocoles à divulgation nulle de connaissance permettant de prouver, d’une part, des énoncés classiques, comme le fait qu’un chiffré CL est bien formé, et d’autre part, des énoncés plus spécifiques, tels que le mélange aléatoire de chiffrés. Les preuves à divulgation nulle de connaissance sont essentielles à la sécurité des protocoles de calcul multipartite, en particulier face à des adversaires malveillants, car elles permettent de garantir que les participants se comportent conformément au protocole. Ainsi, disposer de preuves efficaces pour le chiffrement CL représente une étape fondamentale dans la construction de protocoles de calcul distribué pratiques et sûrs utilisant CL. En application de nos techniques, nous présentons un protocole, sûr en présence d’un adversaire malveillant, qui réalise la fonctionnalité “PSI-sum” – une variante de l’intersection privée d’ensembles. Cet exemple pratique met en évidence l’intérêt du chiffrement CL comme bloc de base pour réaliser des fonctionnalités avancées de calcul multipartite.

Poupak Azad, Jiahua Xu, Yebo Feng, Preston Strowbridge · 5 authors

Blockchain bridges have become essential infrastructure for enabling interoperability across different blockchain networks, with more than $24B monthly bridge transaction volume. However, their growing adoption has been accompanied by a disproportionate rise in security breaches, making them the single largest source of financial loss in Web3. For cross-chain ecosystems to be robust and sustainable, it is essential to understand and address these vulnerabilities. In this study, we present a comprehensive systematization of blockchain bridge design and security. We define three bridge security priors, formalize the architectural structure of 13 prominent bridges, and identify 23 attack vectors grounded in real-world blockchain exploits. Using this foundation, we evaluate 43 representative attack scenarios and introduce a layered threat model that captures security failures across source chain, off-chain, and destination chain components. Our analysis at the static code and transaction network levels reveals recurring design flaws, particularly in access control, validator trust assumptions, and verification logic, and identifies key patterns in adversarial behavior based on transaction-level traces. To support future development, we propose a decision framework for bridge architecture design, along with defense mechanisms such as layered validation and circuit breakers. This work provides a data-driven foundation for evaluating bridge security and lays the groundwork for standardizing resilient cross-chain infrastructure.

Lucia Jović

Ovaj rad prikazuje razvoj prototipa blockchain sustava za nadzor nad antidoping pos- tupcima u sportu. Sustav je osmišljen kako bi povećao transparentnost, sigurnost i nepromjenjivost podataka u procesima testiranja sportaša. Korištenjem Ethereum blockchaina, pametnih ugovora i tehnologija poput Reacta, Flask-a i Web3.py, im- plementirane su funkcionalnosti za tri glavne korisničke uloge: agenciju, laboratorij i sportaša. Agencija može inicirati zahtjeve za testiranjem, laboratorij upisivati rezul- tate, a sportaš pregledavati ishode. Evaluacijom su identificirane prednosti u odnosu na postojeće sustave, ali i ograničenja koja mogu biti predmet budućih poboljšanja, uključujući autentikaciju korisnika, veću skalabilnost i primjenu naprednih kripto- grafskih metoda.

Carlo Segat, Sandro Rodriguez Garzon, Axel Küpper

Self-Sovereign Identity (SSI) is a paradigm for digital identity management that offers privacy and flexibility advantages. A key technology in SSI is Decentralized Identifiers (DIDs) and their associated metadata, DID Documents (DDOs). DDOs contain crucial verification material such as the public keys of the entity identified by the DID (i.e., the DID subject) and are often anchored on a distributed ledger to ensure security and availability. Long-lived DIDs must support updates (e.g., key rotation). Ideally, only the DID subject should authorize DDO updates. However, in practice, update capabilities may be shared or delegated. While the DID specification acknowledges such scenarios, it does not define how updates should be authorized when multiple entities jointly control a DID (i.e., group control). This article examines the implementation of an on-chain, trustless mechanism enabling DID controllers under group control to program their governance rules. The main research question is the following: Can a technical mechanism be developed to orchestrate on-chain group control of a DDO in a ledger-agnostic and adaptable manner?

Agnideep Aich, Ashit Baran Aich, Dipak C. Jain

We propose \textbf{Temporal Conformal Prediction (TCP)}, a distribution-free framework for constructing well-calibrated prediction intervals in nonstationary time series. TCP couples a modern quantile forecaster with a rolling split-conformal calibration layer; its \textbf{TCP-RM} variant adds an online Robbins-Monro offset to steer coverage in real time. We benchmark TCP against GARCH, Historical Simulation, Quantile Regression (QR), linear QR, and Adaptive Conformal Inference (ACI) across S\&P 500, Bitcoin, and Gold. Three results are consistent. First, QR baselines yield the sharpest intervals but are materially under-calibrated; even ACI remains below the 95\% target. Second, TCP achieves near-nominal coverage, yielding intervals slightly wider than Historical Simulation (e.g., S\&P 500: 5.21 vs.\ 5.06). Third, the RM update changes calibration only marginally at default hyperparameters. Crisis-window visualizations (March 2020) show TCP promptly expanding and contracting intervals as volatility spikes. A sensitivity study confirms robustness to hyperparameters. Overall, TCP bridges statistical inference and machine learning, providing a practical solution for calibrated risk forecasting under distribution shift.

Yusei Tanaka

Round-based DAGs enable high-performance Byzantine fault-tolerant consensus, yet their technical advantages remain underutilized due to their short history. While research on consensus protocols is active in both academia and industry, many studies overlook implementation-level algorithms, leaving actual performance unclear - particularly for theoretical protocols whose practical performance cannot often be evaluated. Bullshark, a Round-based DAG BFT protocol on Narwhal mempool, achieves optimal performance: 297,000 transactions per second with 2-second latency. We analyze the algorithm's workflow, from transaction submission to blockchain commitment, breaking it down layer by layer at the functional level and delineating the key features and interactions of the Bullshark and Narwhal components. Future work aims to improve performance in Byzantine fault environments and optimize trade-offs in the CAP theorem.

Liangxin Qian, Jun Zhao

In the rapidly evolving landscape of the Metaverse, enhanced by blockchain technology, the efficient processing of data has emerged as a critical challenge, especially in wireless communication systems. Addressing this challenge, our paper introduces the innovative concept of data processing efficiency (DPE), aiming to maximize processed bits per unit of resource consumption in blockchain-empowered Metaverse environments. To achieve this, we propose the DPE-Aware User Association and Resource Allocation (DAUR) algorithm, a tailored optimization framework for blockchain-enabled Metaverse wireless communication systems characterized by joint computing and communication resource constraints. The DAUR algorithm transforms the nonconvex problem of maximizing the sum of DPE ratios into a solvable convex optimization problem. It alternates the optimization of key variables, including user association, work offloading ratios, task-specific computing resource distribution, bandwidth allocation, user power usage ratios, and server computing resource allocation ratios. Our extensive numerical results demonstrate the DAUR algorithm's effectiveness in DPE.