Scarlett Sieber, Ian Fong, Tina Lončarić, Dhanum Nursigadoo · 6 authors
Rules make fun better! Said no one ever, other than that one cousin who’s weirdly competitive but pretends they know how to relax (you know who you are). Look, we know regulations are painful, and everyone would rather pass them off to their legal team or compliance head to read this stuff. But it’s what we’ve all got to know when operating in financial services. And given the risks around the convergence of traditional finance (TradFi) and decentralized finance (DeFi), that’s doubly important. TradFi has long been constrained (sometimes for the better) by regulation; DeFi… not so much until recently. That’s the benefit DeFi gets from being a greenfield innovation space. But regulators are closely monitoring the activities of DeFi players and TradFi operators entering the space. If you want to take advantage of the technological benefits of tokenization, stablecoins, prediction markets, and more, you need to soak this stuff up.
Incentive (or point) systems are widely deployed across industries such as retail, tourism, and finance to enhance customer loyalty and create benefits for service providers. However, their operation typically requires the collection and processing of sensitive customer data, leading to significant privacy concerns. Existing privacy-preserving incentive systems predominantly rely on bilinear pairings and the discrete logarithm assumption, which, while efficient in classical settings, are vulnerable to quantum adversaries and thus lack long-term security guarantees. To address this limitation, we present LatInc, a practical lattice-based privacy-preserving incentive system. LatInc integrates state-of-the-art lattice-based signatures with efficient protocols, the ABDLOP commitment, and efficient lattice zero-knowledge proofs, achieving a robust balance between post-quantum security and efficiency. Relying on the hardness of the MLWE and MSIS problems, we formally prove that LatInc achieves unforgeability, anonymity, and framing-resistance in the random oracle model. We implement a demo of the system and evaluate its performance on a standard laptop platform. Experimental results show that the communication overheads for the Earning and Spending protocols are approximately 99 KB and 140 KB, respectively, with execution times of 610 ms and 900 ms, highlighting significant efficiency gains over previous lattice-based incentive constructions.
Blockchain-Enhanced AI: Securing Data Pipelines in Hybrid Cloud Environments: The data is vulnerable to tampering and breaches, which would completely undermine the accuracy of AI-driven insights, when running data pipelines in hybrid cloud setups.Blockchain Enhanced AI is a framework that combines the unchangeable records of blockchain technology with AI to check the accuracy of real-time data in multi-cloud systems. This can be done with the help of smart contracts that automatically flag anomalies, using sophisticated machine learning models such as LSTM networks. We can virtually eliminate the possibility of man-in-the-middle attacks by hashing the data blocks and validating them via consensus algorithms. In software engineering, the process streamlines the DevOps pipeline and reduces the risk of breaches by 30% on simulations in AWS and Azure. At the heart of the framework lies a robust core architecture and also includes privacy-preserving zero-knowledge proofs, and we’ve put this system to the test with empirical results in prototypes processing enormous petabyte-scale datasets. Attendees will be able to learn about the real-world implementation of this technology, challenges to scaling, and the ethical concerns around decentralized AI governance, and in doing so will help in developing more secure cloud-native applications.
Scarlett Sieber, Ian Fong, Tina Lončarić, Dhanum Nursigadoo · 6 authors
Before we get started properly, we thought it best to define the intersection for you. It’s a term we started using back in early 2025 to define the convergence of DeFi and TradFi we were seeing across the space. It was fully activated at Money20/20’s conferences across the world, but in reality, it’s so much more. The intersection is the space where two realities come together to create something better. For this book, it’s where traditional finance (TradFi) and decentralized finance (DeFi) come together to deliver truly digital financial services, changing what it means for money to do business.
The widespread deployment of neural networks has raised significant concerns regarding the integrity and privacy of model predictions, especially in malicious environments. Current approaches have explored zero-knowledge proofs for integrity verification. However, they suffer from inefficiency in proving runtime and a lack of rigorous integrity verification for non linear operations. To address these issues, we present a trustwor thy framework for Enhancing Integrity Verification of Convolutional Neural Network predictions (EIV-CNN) in a malicious model, whose key contributions are an efficient optimized sum check protocol and a robust enhanced verification mechanism. Specifically, we first propose an algorithm that enables efficient proving of both batch and collaborative CNN predictions by com bining sumcheck claims of multiple matrix multiplications into one. Moreover, we introduce a non-interactive sumcheck protocol with malicious security (NM-Sumcheck) to serve as a building block for publicly verifying matrix multiplication operations. Furthermore, we introduce a verifiable method for transforming nonlinear operations into matrix operations, enabling their sub sequent evaluation with the NM-Sumcheck protocol. Our EIV CNN provides malicious security, guarantees public verifiability, and preserves model privacy. Empirical results demonstrate that our sumcheck framework achieves constant prover time, verifier time, and proof size. Compared to the state-of-the-art, it achieves up to a 128.56× reduction in prover time, along with significant reductions in communication overhead and enhanced scalability.
The modular invariance and automorphism group rigidity of vertex operatoralgebras provide a profound mathematical foundation for constructing novel postquantum cryptographic systems. However, a significant theoretical and engineeringgap exists between mathematical theorems and deployable cryptosystems. Thispaper does not propose new cryptographic protocols but rather systematicallyexamines the core challenges encountered in engineering vertex operator algebracryptography: the discrete selection of parameter spaces and their quantitativerelationship with security strength, the computational resource requirements ofcandidate algebraic families (lattice vertex operator algebras, WZW models, andmoonshine vertex operator algebras), the assessment of security boundaries underquantum attack models, and the practical overhead of auxiliary mechanisms suchas zero-knowledge proofs. The objective is to provide a clear problem inventoryand a feasibility analysis framework for future research, rather than to claim anyimmediately usable security parameters. The article concludes by summarizing thecurrent technology readiness levels and identifying the key breakthroughs requiredto advance from a theoretical framework toward a practical system.
Digital signature schemes derived from non-interactive zero-knowledge (NIZK) proofs are rapidly gaining prominence within post-quantum cryptography. CROSS is a promising new code-based post-quantum digital signature scheme based on the NIZK framework. It is currently in the second round of the NIST’s additional call for standardization for post-quantum digital signatures. However, CROSS’s reference implementation has a substantially large memory footprint. This makes its deployment on resource-constrained platforms prohibitively difficult.In particular, we identified the most memory-intensive areas such as Merkle and GGM tree structures, and zero-knowledge proof commitment generation. We propose several novel algorithms and implementation strategies to reduce the memory requirement of these components. Apart from these, we also propose several memory optimization techniques, such as just-in-time hashing and execution flow analysis. As a result, our implementation reduces the memory footprint of Key Generation, Signature Generation, and Verification of the CROSS reference code by as much as 95%, 92%, and 85%, respectively. This results in a suite of implementations in which all variants are under 128kB (for all security levels of KeyGen/Sign/Verify) and six variants under 32kB. Our memory optimization techniques are not specific to CROSS, but can be applied to other NIZK-based signature schemes.Regarding efficiency, matrix multiplications are crucial to the performance of CROSS. We show how the Digital Signal Processing (DSP) instructions on ARM Cortex-M4, specifically packing and multiplying, can be utilized to efficiently implement matrix operations over finite fields. The DSP optimizations combined with the memory reductions improve the efficiency of CROSS by up to 32% and 33% in Signature Generation and Verification respectively.
Scarlett Sieber, Ian Fong, Tina Lončarić, Dhanum Nursigadoo · 6 authors
Fraud is the financial world’s biggest headache. It doesn’t matter if you’re in traditional finance (TradFi) or decentralized finance (DeFi); you’re faced with an unrelenting wave of criminal behavior.
Industrial operational technology systems are becoming more intelligent and interconnected, requiring remote maintenance and multiparty collaboration. While traditional approaches improve efficiency, they introduce risks like data leakage and unauthorized operations. Existing access control schemes struggle with compliance verification and auditing while ensuring privacy. A novel access control scheme was proposed that combines zero-knowledge proof with the publicly verifiable covert security model. The scheme features a dual-layer verification mechanism: a basic layer using zero-knowledge proof to protect identities and permissions during remote maintenance and an enhanced layer for high-risk operations that uses oblivious transfer and digital signatures to detect malicious behavior and generate cheating certificates. Security analysis showed the scheme ensures privacy, access legitimacy, and non-repudiation. Experiments demonstrated the scheme had faster proof generation and verification compared to existing methods with effective malicious behavior detection and accountability.
A novel blockchain-based smart contract framework is proposed and designed to mitigate financial product fraud by enhancing transparency, auditability, and trust in advisory processes. The framework introduces a unique dual-contract architecture that combines product and authorization smart contracts, along with a challenge-response verification protocol that ensures both product authenticity and advisor legitimacy. The system is implemented and tested on the Ethereum blockchain, demonstrating operational feasibility through real-world transaction simulations and a corresponding gas cost analysis. By leveraging immutability, the framework preserves data integrity, while cryptographic signatures enable privacy protection without exposing sensitive data on-chain. It is designed to support multi-institutional environments, allowing various financial institutions to issue products and authorize advisors under a unified, fraud-resistant platform. Experimental results confirm the system’s effectiveness in preventing common fraud scenarios, while maintaining low transaction costs and high security.
The Blind Watchdog Protocol (BWP) constructs a directed oversight graph where each autonomous agent has exactly one hidden watchdog, but no agent knows who watches it. Compliance emerges through a Panopticon equilibrium — the mere possibility of observation makes defection irrational. A closed-form Nash equilibrium theorem (6-step proof, TLC model-checked: 2,071 states, zero violations) establishes that compliance is strictly dominant under configurable parameters. The protocol implements 10 composable plugins (reputation, staking, mixnet, rotation, correlation analysis, adaptive watcher allocation, conviction scoring, knowledge gating, hybrid oversight, and optimistic slashing) and maps 10 biological oversight mechanisms to executable code. Key results: 100% detection rate with 0% false positives across 1,000 deterministic simulation runs (p_d=1.0). Stress-tested with stochastic observation noise, collusion sweeps (10-40%), Dark DAO bribery economics, and latency profiling. Layered defense separates immediate containment (escalation levels 1-3) from delayed adjudication (optimistic slashing with challenge period). Three-tier Sybil resistance via admission staking, DID-based identity, and Proof-of-Personhood interface. Constant-rate dummy traffic for timing-analysis resistance. Standardized evidence protocol for dispute resolution. Dynamic VaR-coupled stakes for high-value environments. Three fundamental open problems are identified: out-of-band cryptographic bribery (Dark DAOs), the recursive final arbitrator problem, and the latency-anonymity-cost trilemma for LLM agents. The reference implementation (422 tests, 5,757+ LOC, Python) is licensed under PolyForm Noncommercial 1.0. This paper is a defensive publication of the protocol design, formal proofs, and empirical results.
Статья посвящена философскому анализу феномена технологической сингулярности, рассматриваемой не как технический рубеж, а как фундаментальный онтологический сдвиг в истории цивилизации. В работе критически сопоставляются модели «взрыва интеллекта» и S-образных кривых технологического роста. Особое внимание уделено трансформации человеческой субъектности (агентности) в условиях перехода к «пост-инструментальной эре». Предлагается стратегия навигации в неопределенности мира VUCA, опираясь на синтез аристотелевской этики добродетели (концепт «искусственного фронезиса»), стоицизма и логотерапии Виктора Франкла. В качестве практических механизмов сохранения демократического участия рассматриваются инновационные инструменты: децентрализованные автономные организации (DAO) и платформы делиберативной демократии. This article provides a philosophical analysis of the phenomenon of technological singularity, viewed not as a technical frontier, but as a fundamental ontological shift in the history of civilization. The paper critically compares the "intelligence explosion" and S-shaped curves of technological growth. Particular attention is paid to the transformation of human agency in the transition to a "post-instrumental era." A strategy for navigating the uncertainty of a VUCA world is proposed, drawing on a synthesis of Aristotelian virtue ethics (the concept of "artificial phronesis"), Stoicism, and Viktor Frankl's logotherapy. Innovative tools, such as decentralized autonomous organizations (DAOs) and deliberative democracy platforms, are considered as practical mechanisms for preserving democratic participation.
Digital Education and Society
Interdisciplinary Studies: Technology, Society, and Humanities
This paper investigates the resilience and dynamic behavior of energy-conserving cryptocurrencies (ECCs) during two major global crises: the COVID-19 pandemic and the Russia–Ukraine conflict. Unlike traditional proof-of-work (PoW) assets, ECCs—primarily proof-of-stake (PoS) and low-energy blockchain tokens—are increasingly promoted as sustainable digital alternatives. Using a balanced panel of major ECCs across 10 countries with cryptocurrency markets from January 2019 to December 2023, we apply a panel ARDL–PMG model combined with panel causality tests and structural break analysis to examine the long- and short-run effects of global uncertainty on ECC returns and volatility. Our findings show that ECCs exhibit stronger crisis resilience compared with high-energy cryptocurrencies, with limited long-run exposure to pandemic shocks but moderate sensitivity to geopolitical tensions following the Russia–Ukraine conflict. COVID-19 uncertainty has a short-run negative pressure on ECC markets, whereas geopolitical risk (GPR) driven by the conflict generates asymmetric responses. Cross-country results reveal that ECC markets in technologically advanced, energy-transition economies (EU, Singapore, UAE) exhibit greater stability than those in emerging markets. These findings highlight the potential role of ECCs in sustainable finance, offering policymakers, investors, and regulators insights into the feasibility of promoting energy-efficient digital assets amid extreme global uncertainty.
The rapid growth of cloud computing has significantly transformed the way digital data is stored, managed, and accessed, enabling efficient sharing of information across distributed environments; however, this advancement introduces serious concerns related to data security, privacy, and trust, particularly when sensitive information is involved. Many cloud-based systems rely on centralized architectures, which increase the risk of single points of failure, unauthorized access, data tampering, and limited transparency in tracking data activities. These systems often depend on basic encryption techniques without strong auditing or verification mechanisms, making them vulnerable to insider misuse and external cyber threats, while the absence of immutable records reduces accountability and weakens user confidence. Such limitations highlight the need for a secure and transparent data-sharing framework that ensures confidentiality, integrity, and traceability of data transactions. To address these challenges, the proposed system introduces a secure cloud data sharing model developed using the Django framework, integrating Elliptic Curve Cryptography (ECC), blockchain technology, and the InterPlanetary File System (IPFS) to enhance data protection and decentralization. In this approach, ECC is used to generate cryptographic keys and encrypt user files before storage, ensuring that only authorized users can decrypt the data using the corresponding private key. The encrypted files are stored using IPFS for distributed and content-addressable storage, while file metadata such as username, filename, and timestamp is recorded on the blockchain through smart contracts using Web3, providing a decentralized and tamper-resistant record of all transactions. The system also supports user registration, authentication, secure file upload, and controlled file download functionalities, ensuring secure access and traceability. During file access, encrypted data is retrieved from IPFS and decrypted using ECC to maintain end-to-end security. By combining cryptographic encryption, decentralized storage, and blockchain-based verification, the proposed system enhances data confidentiality, prevents unauthorized modifications, and establishes a reliable and transparent framework for secure cloud data sharing.
Florian Krieger, Christian Dobrouschek, Florian Hirner, Sujoy Sinha Roy
We present the first high-performance SIMD software implementation of Spielman codes for their use in polynomial commitment schemes and zero-knowledge proofs. Spielman codes, as used in the Brakedown framework, are attractive alternatives to Reed-Solomon codes and benefit from linear-time complexity and field agnosticism. However, the practical deployment of Spielman codes has been hindered by a lack of research on efficient implementations. The involved costly finite-field arithmetic and random memory accesses operate on large volumes of data, typically exceeding gigabytes; these pose significant challenges for performance gains. To address these challenges, we propose several computational and memory-related optimizations that together reach an order-of-magnitude performance improvement in software. On the computation side, we propose SIMD optimizations using the AVX-512-IFMA instruction set and introduce a lazy reduction method to minimize the modular arithmetic cost. On the memory side, we implement a cache-friendly memory layout and a slicing technique, which exploit the CPU memory hierarchy. Finally, we present our multithreading approach to improve throughput without saturating memory bandwidth. Compared to prior Spielman software, our optimizations achieve speedups of up to 21.9x and 20.6x for single- and multi-threaded execution, respectively. In addition, instantiating our software with 64 threads on a high-end CPU even outperforms a recent FPGA accelerator by up to 4.3x for small and mid-sized polynomials. Our improvements make Spielman codes competitive with well-optimized Reed-Solomon codes on software platforms.
E. Sravanthi, Pabbathi Laxmiprasanna, Mulukutla Jahnavi, Kancharla Kritika Reddy
The increasing reliance on digital systems in law enforcement has emphasized the need for secure, transparent, and reliable mechanisms to manage crime evidence. In existing systems, evidence management is typically handled through centralized databases and manual record-keeping, where crime reports, officer details, and evidentiary materials are stored in a single controlled environment. This approach introduces critical challenges such as data tampering, unauthorized access, loss of sensitive information, and lack of transparency, which can weaken trust and complicate legal proceedings. Furthermore, storing evidence in physical formats or unsecured digital systems makes it difficult to ensure authenticity and maintain a proper Chain of Custody (CoC). These limitations highlight the necessity for a system that ensures data integrity, traceability, and secure verification. To overcome these issues, the proposed framework adopts a decentralized architecture using Blockchain technology and Smart Contracts to provide immutability, transparency, and enhanced security of evidence records. The system leverages Ethereum for decentralized data storage, Web3 for enabling interaction between the application and the blockchain network, and Django as the web framework for managing the user interface, file handling, and administrative functionalities. Authorized officers can securely upload, access, and manage evidence, while administrators can monitor and verify transactions in real time. Each evidence record is assigned a unique identifier and permanently stored on the blockchain, preventing unauthorized modification and ensuring a verifiable audit trail. Although the system does not utilize Machine Learning (ML) or Deep Learning (DL), it effectively employs smart contracts-based automation for secure evidence tracking, thereby improving accountability, legal reliability, and operational efficiency.
Drug repurposing has emerged as an effective strategy in modern healthcare, enabling researchers to discover new therapeutic uses for existing drugs while significantly reducing development time and cost. Traditional drug discovery methods rely heavily on manual laboratory experiments, expert analysis, and prolonged clinical trials, making the process slow, expensive, and limited in scalability. These approaches struggle to handle complex and high-dimensional biomedical data, leading to delayed insights and reduced efficiency. With the rapid growth of healthcare data, there is an increasing need for intelligent and automated systems that can efficiently analyze drug characteristics and predict alternative therapeutic applications. Additionally, conventional systems often lack transparency and strong security mechanisms, making clinical data vulnerable to tampering and reducing trust in research outcomes. To address these challenges, the proposed framework integrates Machine Learning (ML), Deep Learning (DL), and Blockchain technologies to develop a secure and intelligent drug repurposing system. The framework employs Random Forest (RF) as a baseline model and a Two-Dimensional Convolutional Neural Network (CNN2D) as an advanced model to improve prediction accuracy. The CNN2D effectively captures complex feature patterns in structured drug data, enabling precise identification of potential new disease treatments. Furthermore, Web3-based Blockchain technology ensures secure storage of user data, clinical interactions, and experimental records by providing immutability, transparency, and data integrity. By combining Artificial Intelligence (AI)-driven analytics with Blockchain-based security, the system enhances prediction performance, automates decision-making, and ensures reliable data management, offering a scalable and efficient solution for accelerating drug discovery and supporting healthcare innovation.
Kunal Kumar, Mohammad Malik, Gujju Koushik, Nujetti Abinandhan
The evolution of blockchain technology has introduced innovative approaches for managing digital assets and transforming fundraising models through Non-Fungible Tokens (NFTs). However, many existing charity platforms continue to operate on centralized systems that restrict transparency, limit accountability, and fail to provide donors with verifiable proof of their contributions. In such systems, donors often have minimal visibility into fund utilization, and there is no direct linkage between their contributions and any traceable digital asset. Moreover, traditional charity and auction mechanisms rely heavily on intermediaries for transaction validation, data management, and operational control, making them susceptible to data manipulation, reduced auditability, and diminished user trust, while also lacking mechanisms to encourage active participation. To address these limitations, this research proposes a decentralized charity auction framework that integrates Blockchain technology with NFTs to ensure secure, transparent, and verifiable transactions. The system is developed using the Django Web Framework and leverages Web3 Technology along with Smart Contracts to automate and manage auction processes. Each auction item is uniquely tokenized as an NFT, guaranteeing authenticity and non-replicability. Users can register as donors or auction organizers, create NFTbased auctions, and participate through bidding or direct contributions. All transactions are permanently recorded on the blockchain, and NFT ownership is automatically transferred to the highest bidder or contributor, serving as a verifiable digital proof of participation. By removing intermediaries and ensuring immutable record-keeping, the system enhances trust, strengthens security, and introduces an incentive-driven participation model, thereby improving transparency, accountability, and efficiency in modern charity and fundraising ecosystems.
Blockchain is a decentralised and distributed ledger technology that enables multiple participants to collectively maintain a secure and tamper-resistant record of transactions without relying on trusted central authorities. It has several potential features, including decentralisation, immutability, transparency and security. Beyond its original use in cryptocurrencies, blockchain has facilitated a diverse range of applications, including decentralised finance, supply chain tracking, digital identity management, secure voting systems and decentralised autonomous organisations, where transparency, trustlessness and data integrity are critical. Structurally speaking, a blockchain consists of an ordered sequence of blocks, each containing a set of validated transactions. Every block incorporates a cryptographic hash of its previous block, linking them into an immutable chain that maintains chronological ordering and prevents tampering. At its foundation, a blockchain relies on the consensus mechanism that ensures all untrusted participants agree on a consistent ledger state, despite network latency or malicious behaviour. Up to now, widely adopted consensus algorithms include proof-of-work (PoW), which relies on computationally intensive puzzles, and proof-of-stake (PoS), which utilises economic incentives based on stake ownership. Unlike PoW, PoS consumes less energy, achieves faster block finalisation with lower latency and lowers participation barriers, enhancing efficiency, scalability and decentralisation without compromising security.Digital signatures are fundamental cryptographic primitives essential for establishing trust and ensuring security in digital communications. By using a secret key to generate signatures on given messages, anyone who knows the corresponding public key can check the validity of signature candidates. This cryptographic process provides critical guarantees such as authentication, data integrity and non-repudiation, making them integral to secure communication and a wide range of cryptographic protocols. In PoS blockchain protocols, digital signatures play a crucial role not only in authenticating transactions but also in validating the participation of stakeholders in consensus processes, such as block proposals and block attestations. Advanced signature schemes, including forwardsecure signatures or puncturable signatures, are often employed to prevent long-range attacks caused by secret key leakage, preserving the immutability of PoS blockchain protocols. Furthermore, threshold or weighted threshold signatures are frequently deployed in PoS-based protocols to aggregate multiple block attestations into a single compact one efficiently, enhancing scalability while maintaining robust security guarantees.This thesis focuses on advanced digital signature schemes deployed in proof-of-stake blockchain protocols, with particular emphasis on puncturable signatures and weighted threshold signatures. To be more specific, the main contributions of this thesis are outlined as follows.First, we focus on puncturable signatures and propose the first generic construction derived from identity-based signatures by treating identities as to-be-punctured prefixes. Based on this framework, we give concrete puncturable signature instantiations over bilinear maps, lattices and multivariate polynomials, respectively. More specifically, the pairing-based instantiation is proven secure based on the computational Diffie-Hellman (CDH) assumption in the standard model. The lattice-based instantiation achieves provable security under the short integer solution (SIS) assumption in the random oracle model. The multivariate-based instantiation is analysed against some best-known attacks in multivariate public key cryptography. All of the proposed schemes support efficient puncture operations, while the lattice-based and multivariate-based ones additionally enjoy post-quantum security.Second, we adopt a different approach to constructing puncturable signatures supporting compact secret keys that serve as an effective mitigation against long-range attacks caused by secret key leakage in PoS blockchains. Specifically, we propose a new generic construction of puncturable signatures from delegated (key-policy) constrained signatures. Such a framework is inspired by an observation that matching between messages and constraints can be converted to equality tests between prefixes of to-be-signed messages and punctured prefixes. The key delegation property of (key-policy) constrained signatures enables repeated key puncture operations. Building on our framework, we give a concrete lattice-based instantiation that is proven secure based on the SIS assumption in the standard model. Our proposed scheme features small secret key sizes, particularly for the initial secret key, which is beneficial for users to join PoS blockchains without requiring a significant commitment in the initial phase.Third, we revisit the notion of puncturable signatures and find their vulnerability in mitigating long-range attacks caused by secret key leakage in PoS blockchains. Despite their key evolving property, compromising previous secret keys enable adversaries to forge branches in PoS blockchains, bypassing the security guarantees provided by puncturable signatures. It is essential to invalidate previous secret keys, regardless of whether they have been securely deleted. Therefore, we integrate key puncture and signing operations into a unified Sign-and-Pun algorithm. By publishing punctured prefixes and providing additional proofs, our strengthened puncturable signatures ensure that no malicious signers can generate valid signatures using previous secret keys. Furthermore, we propose a concrete lattice-based construction that is provably secure under the SIS assumption in the standard model.Finally, we focus on weighted threshold signatures for block attestations in PoS blockchain protocols, where validators are assigned different weights to reflect their varying impacts on consensus decisions. Specifically, we present the first weighted threshold signature scheme over lattices, which is a combination of multi-signature and non-interactive inner product arguments. In our proposed scheme, the weights of signers are public and work as a separate checking condition in threshold signature verification. We show that our scheme is provably secure under the module short integer solution (MSIS) assumption in the random oracle model. Furthermore, we demonstrate how to integrate our scheme into PoS blockchains for block attestation. Moreover, we implement our scheme in the C programming language and present an experimental evaluation of its practical efficiency.
Abstract Web3 infrastructure has demonstrated that decentralized coordination is technically feasible. Yet the dominant governance model — token-weighted voting — produces structural concentration of decision-making authority over time, and has not proved well-suited to real-world economic coordination. This paper argues that the missing element is constitutional ownership geometry: a structural arrangement of bounded roles and non-dilutable stakeholder balance that persists as participation evolves. We introduce the Vessel Compartment System (VCS), developed within the Mycelia Inclusive Networks (MIN) framework, as one such approach. VCS distributes governance authority across fixed ownership compartments representing distinct stakeholder roles — community participants, operators, capital providers, and ecosystem partners — each non-dilutable relative to the others. Participants within compartments may change; the balance among compartments does not. Web3 infrastructure provides the enforcement and portability layer this model requires: smart contracts encode compartment boundaries, tokenized roles enable exit without requiring dissolution of institutional structure, and composable systems support cross-vessel coordination. Together, these features allow governance to remain internally stable while evolving externally through participant migration across structurally stable governance units. The paper situates VCS within established governance theory, contrasts it with token-weighted and procedural governance models, and examines its implications for real-world economic coordination and Web3 system design. Keywords: Web3 governance, token-weighted voting, decentralized autonomous organizations, ownership geometry, Vessel Compartment System, constitutional governance, exit-driven evolution, real-world economic coordination, multi-stakeholder governance