Blockchain Papers

Santosh Kumar B, Sangeetha N, Shinzeer C K, Ramya R · 6 authors

No abstract is available for this record.

Piper, Fabian, Karl H. Wolf, Jonathan Heiss

Decentralized applications (dApps) in Decentralized Finance (DeFi) face a fundamental tension between regulatory compliance requirements like Know Your Customer (KYC) and maintaining decentralization and privacy. Existing permissioned DeFi solutions often fail to adequately protect private attributes of dApp users and introduce implicit trust assumptions, undermining the blockchain's decentralization. Addressing these limitations, this paper presents a novel synthesis of Self-Sovereign Identity (SSI), Zero-Knowledge Proofs (ZKPs), and Attribute-Based Access Control to enable privacy-preserving on-chain permissioning based on decentralized policy decisions. We provide a comprehensive framework for permissioned dApps that aligns decentralized trust, privacy, and transparency, harmonizing blockchain principles with regulatory compliance. Our framework supports multiple proof types (equality, range, membership, and time-dependent) with efficient proof generation through a commit-and-prove scheme that moves credential authenticity verification outside the ZKP circuit. Experimental evaluation of our KYC-compliant DeFi implementation shows considerable performance improvement for different proof types compared to baseline approaches. We advance the state-of-the-art through a holistic approach, flexible proof mechanisms addressing diverse real-world requirements, and optimized proof generation enabling practical deployment.

Xingxing Chen, Xiaohong Zhang, Shaojiang Zhong, Shuling Liu

Vehicular Ad Hoc Networks (VANETs) are now a pivotal component of Intelligent Transportation Systems. However, ensuring secure vehicle identity authentication and protecting user privacy remain two challenging issues in VANETs. Addressing these challenges, this paper seamlessly integrates blockchain technology with the InterPlanetary File System to realize a fully decentralized storage solution for identity verification information. Simultaneously, it employs zk-SNARK and elliptic curve cryptography to allow vehicle users to anonymously complete identity verification. Additionally, the lightweight identity authentication proof obtained after successful verification maintains credibility while reducing the computational and communication costs for both roadside units and vehicles. The security and performance analysis of the system show that the proposed scheme has significant advantages in both communication and computation compared with similar research, while also offering superior security and a broader range of functional attributes compared to existing competitive approaches.

Sabine Oechsner, Vítor Pereira, Peter Schöll

Computer-aided cryptography, with particular emphasis on formal verification, promises an interesting avenue to establish strong guarantees about cryptographic primitives. The appeal of formal verification is to replace the error-prone pen-and-paper proofs with a proof that was checked by a computer and, therefore, does not need to be checked by a human. In this paper, we ask the question of how reliable are these machine-checked proofs by analyzing a formally verified implementation of the Line-Point Zero-Knowledge (LPZK) protocol (Dittmer, Eldefrawy, Graham-Lengrand, Lu, Ostrovsky and Pereira, CCS 2023). The implementation was developed in EasyCrypt and compiled into OCaml code that was claimed to be high-assurance, i.e., that offers the formal guarantees of guarantees of completeness, soundness, and zero knowledge. We show that despite these formal claims, the EasyCrypt model was flawed, and the implementation (supposed to be high-assurance) had critical security vulnerabilities. Concretely, we demonstrate that: 1) the EasyCrypt soundness proof was incorrectly done, allowing an attack on the scheme that leads honest verifiers into accepting false statements; and 2) the EasyCrypt formalization inherited a deficient model of zero knowledge for a class of non-interactive zero knowledge protocols that also allows the verifier to recover the witness. In addition, we demonstrate 3) a gap in the proof of the perfect zero knowledge property of the LPZK variant of Dittmer, Ishai, Lu and Ostrovsky (CCS 2022) that the EasyCrypt proof is based, which, depending on the interpretation of the protocol and security claim, could allow a malicious verifier to learn the witness. Our findings highlight the importance of scrutinizing machine-checked proofs, including their models and assumptions. We offer lessons learned for both users and reviewers of tools like EasyCrypt, aimed at improving the transparency, rigor, and accessibility of machine-checked proofs. By sharing our methodology and challenges, we hope to foster a culture of deeper engagement with formal verification in the cryptographic community.

Xiangyu Liu

Traceable Ring Signatures (TRS) were introduced by Fujisaki and Suzuki~[PKC'07], where a trace algorithm can publicly check if two signatures with the same event label were generated by the same signer (linkability). In addition, if the two signatures correspond to different messages, then the signer's identity is revealed (traceability). Following [PKC'07], most subsequent works adopt the same definitions and consider three security properties, anonymity, linkability, and exculpability. [PKC'07] proved that the latter two properties together imply unforgeability, a fundamental requirement for all signature-like primitives. ~~~~In this work, we identify a gap in the aforementioned proof, which arises from the insufficient consideration of linkability and exculpability in [PKC'07]. To address this, we revisit the syntax and security notions of TRS, and close this gap by defining extended linkability and extended exculpability. Building on these, we design a new framework of TRS from PseudoRandom Functions (PRF) and Zero-Knowledge Proofs of Knowledge (ZKPoK) that supports tracing, provided that both two signatures are valid. This constitutes a substantial improvement over existing approaches---all of which require tracing with the size of the ring---and elevates TRS to a level of practicality and efficiency comparable to Linkable Ring Signatures (LRS), which have already achieved widespread deployment in practice. Finally, we instantiate our generic framework from the DDH assumption and leverage the Bulletproofs [S\&P'18] to construct a TRS scheme with log-size signatures. The proposed scheme achieves highly optimized signature sizes in practice and remains compatible with most existing DLog-based systems. On Curve25519, the signature size is bytes, which to our best knowledge is the shortest LRS scheme for a ring .

Jules Maire, Alan Pulval-Dady

Blind signatures have become a cornerstone for privacy-sensitive applications such as digital cash, anonymous credentials, and electronic voting. The elliptic curve variant of the Digital Signature Algorithm (ECDSA) is widely adopted due to its efficiency in resource-constrained environments, such as mobile devices and blockchain systems. Building blind ECDSA is hence a natural goal. One presents the first such construction relying solely on the ECDSA assumption. Despite the inherent complexities in integrating blindness with ECDSA, we design a protocol that ensures both unforgeability and blindness without introducing new computational assumptions and ensuring concurrent security. It involves zero-knowledge proofs based on the MPC-in-the-head paradigm for complex statements combining relations on encrypted elliptic curve points, their coordinates, and discrete logarithms.

Xiaoxue Zhang, Sammy Tesfai, Minmei Wang, Haofan Cai

Multi-enterprise applications in fields like supply chain management, finance, and healthcare require complex collaboration and data exchange among organizations to ensure operational efficiency and build trust. Permissioned blockchains emerged as a promising solution, providing shared, immutable ledgers that enhance transparency, traceability, and trust among authorized parties. However, during asset trading between organizations, they must verify the legitimacy of asset transfers, including asset ownership and quantity, while protecting sensitive asset owner information. To achieve both verifiability and privacy, this paper introduces PAVE, Privacy-preserving Aggregated Verification system for Multi-Enterprises Blockchain, a framework that integrates zero-knowledge proofs to enable secure asset verification without breaking user privacy. To achieve proof efficiency, PAVE introduces a proof aggregation mechanism that consolidates multiple transaction verifications into a single proof, significantly reducing computational overhead for large-scale scenarios. Evaluation results show that, with the proof aggregation mechanism, PAVE achieves low verification latency and resource utilization, making it a scalable solution for privacy-preserving asset verification across multiple enterprises.

James Bartusek, Ruta Jawale, Justin Raizes, Kabir Tomer

We construct a publicly-verifiable non-interactive zero-knowledge argument system for QMA with the following properties. 1. Transparent setup. Our protocol only requires a uniformly random string (URS) setup. The only prior publicly-verifiable NIZK for QMA (Bartusek and Malavolta, ITCS 2022) requires an entire obfuscated program as the common reference string. 2. Extractability. Valid QMA witnesses can be extracted directly from our accepting proofs. That is, we obtain a publicly-verifiable non-interactive argument of quantum knowledge, previously only known in a privately-verifiable setting (Coladangelo, Vidick, and Zhang, CRYPTO 2020). Our construction introduces a novel ZX QMA verifier with "strong completeness" and builds upon the coset state authentication scheme from (Bartusek, Brakerski, and Vaikuntanathan, STOC 2024) within the context of QMA verification. Along the way, we establish new properties of the authentication scheme. The security of our construction rests on the heuristic use of a post-quantum indistinguishability obfuscator. Rather than rely on the full-fledged classical oracle model (i.e. ideal obfuscation), we isolate a particular game-based property of the obfuscator that suffices for our proof, which we dub the evasive composability heuristic. As an additional contribution, we study a general method for replacing heuristic use of obfuscation with heuristic use of hash functions in the post-quantum setting. In particular, we establish security of the ideal obfuscation scheme of Jain, Lin, Luo, and Wichs (CRYPTO 2023) in the quantum pseudorandom oracle model (QPrO), which can be heuristically instantiated with a hash function. This gives us NIZK arguments of quantum knowledge for QMA in the QPrO, and additionally allows us to translate several quantum-cryptographic results that were only known in the classical oracle model to results in the QPrO.

Ailiya Borjigin, Cong He

We present a cross-market algorithmic trading system that balances execution quality with rigorous compliance enforcement. The architecture comprises a high-level planner, a reinforcement learning execution agent, and an independent compliance agent. We formulate trade execution as a constrained Markov decision process with hard constraints on participation limits, price bands, and self-trading avoidance. The execution agent is trained with proximal policy optimization, while a runtime action-shield projects any unsafe action into a feasible set. To support auditability without exposing proprietary signals, we add a zero-knowledge compliance audit layer that produces cryptographic proofs that all actions satisfied the constraints. We evaluate in a multi-venue, ABIDES-based simulator and compare against standard baselines (e.g., TWAP, VWAP). The learned policy reduces implementation shortfall and variance while exhibiting no observed constraint violations across stress scenarios including elevated latency, partial fills, compliance module toggling, and varying constraint limits. We report effects at the 95% confidence level using paired t-tests and examine tail risk via CVaR. We situate the work at the intersection of optimal execution, safe reinforcement learning, regulatory technology, and verifiable AI, and discuss ethical considerations, limitations (e.g., modeling assumptions and computational overhead), and paths to real-world deployment.

Yu He, Cuiqing Jiang, Junfeng Dong, Yong Ding · 5 authors

This study examines values and adoption conditions of Blockchain Technology (BCT) in horizontal demand forecast sharing among retailer, focusing on the influence mechanism of transparency-restriction approaches and BCT's endogenous effects on firms' sharing incentives. We model a supply chain with one manufacturer and multiple retailers, comparing four BCT-enabled data-sharing regimes: open access (permissionless) versus no-open access (permissioned), with or without encryption. Results show that restricted transparency, combined with selective accessibility, aligns individual and collective incentives by curbing wholesale price inflation and improving forecast accuracy. Contrary to intuition, higher transparency does not universally benefit retailers; supplementary encryption can balance data utility and privacy, enabling Pareto-superior outcomes. We further demonstrate BCT can reduces moral hazards in horizontal sharing (e.g. sharing biased forecast), allowing retailers to leverage aggregated demand signals without inefficiently verification. However, excessive transparency in BCT can accelerates retailers' profit erosion, akin to perfect competition. These findings offer micro-foundations for adopting visibility-restriction technologies (e.g. Zero-Knowledge Proofs) and guide the design of context-specific BCT systems. By reconciling transparency-privacy tensions and demonstrating BCT's endogenous role in forecasting, this study advances strategies for enhancing supply chain resilience through BCT innovation.

N. Mohankumar, V. Sindhu, N. Nageswari, N. Silambarasan

Safe and transparent e-voting is becoming more and more important in modern democracies, as the confidence of citizens in electoral systems is determined by the issues of trust, privacy and scalability. Existing e-voting systems, however, have privacy, impersonation vulnerability, lack of transparency, and coercive weaknesses, and so they must be improved through cryptographic and identity solutions. In an attempt to provide security at these points, to propose a voting system that uses Aadhaar-linked decentralized identities together with iris scan biometrics to authenticate voters, zk-SNARKs to produce zero-knowledge proofs of voter eligibility without revealing their personal data, and homomorphic encryption to ensure ballot confidentiality and allow vote counting to be verifiably processed. Moreover, coercion resistance is ensured by a revoting mechanism, as only the last authenticated vote is included in the counting, thereby mitigating external pressure or vote-buying. The results demonstrate that the proposed design is capable to concurrently deliver strong authentication, biometric-based impersonation resistance, privacy preservation, end-to-end verifiability, and scalability in e-voting. In general, this framework eliminates major weaknesses of the old systems in addition to increasing voter confidence and integrity of the elections. The integration of decentralized identity, biometric iris recognition, and modern cryptography allows the model to provide a secure, transparent, and non-coercible framework of next-generation democratization procedures in India and can present an open-source, globally replicable solution with large-scale elections.

Russell W. F. Lai, Monisha Swarnakar, Ivy K. Y. Woo

The Learning with Errors (LWE) problem asks to distinguish noisy samples s^T A + e^T mod q from uniformly random values given the random matrix A. In this work, we show that a variant called Leaky LWE, where the distinguisher receives additionally noisy leakages (s^T, e^T) L + f^T of the LWE secret s and error e for low-norm matrix L chosen adaptively by the distinguisher after seeing A, is not easier than the standard LWE of the same dimensions up to polynomial losses in the noise level and the modulus. More generally, we show that the Leaky LWE problem is hard even if the public matrix A is structured and/or hinted and if the non-leaky parts of the secret and error do not follow Gaussian distributions, as long as the corresponding LWE problem without leakage is hard. Our reduction from LWE to Leaky LWE unifies and extends prior results on the Error-Leakage LWE problem [Döttling-Kolonelos-Lai-Lin-Malavolta-Rahimi, EUROCRYPT'23], where L only acts on the error e and the Hint-MLWE problem [Kim-Lee-Seo-Song, CRYPTO'23], where L is restricted to concatenations of random Gaussian scalar matrices not controlled by the distinguisher. Previously, the Hint-MLWE and Error-Leakage LWE assumptions were used as computational replacements of the statistical noise flooding technique in security proofs which led to improved parameters in lattice-based cryptographic constructions such as zero-knowledge proofs, threshold signatures and registration-based encryption. We provide lemmas which abstract out such computational arguments based on Leaky LWE.

Omid Mirzamohammadi, Jan Bobolz, Mahdi Sedaghat, Emad Heydari Beni · 7 authors

An anonymous credential (AC) system with partial disclosure allows users to prove possession of a credential issued by an issuer while selectively disclosing a subset of their attributes to a verifier in a privacy-preserving manner. In keyed-verification AC (KVAC) systems, the issuer and verifier share a secret key. Existing KVAC schemes rely on computationally expensive zero-knowledge proofs during credential presentation, with the presentation size growing linearly with the number of attributes. In this work, we propose two highly efficient KVAC constructions that eliminate the need for zero-knowledge proofs during the credential presentation and achieve constant-size presentations. Our first construction adapts the approach of Fuchsbauer, Hanser and Slamanig (JoC'19), which achieved constant-size credential presentation in a publicly verifiable setting using their proposed structure-preserving signatures on equivalence classes (SPS-EQ) and set commitment schemes, to the KVAC setting. We introduce structure-preserving message authentication codes on equivalence classes (SP-MAC-EQ) and designated-verifier set commitments (DVSC), resulting in a KVAC system with constant-size credentials (2 group elements) and presentations (5 group elements). To avoid the bilinear groups and pairing operations required by SP-MAC-EQ, our second construction uses a homomorphic MAC with a simplified DVSC. While this sacrifices constant-size credentials (n+2 group elements, where n is the number of attributes), it retains constant-size presentations (2 group elements) in a pairingless setting. We formally prove the security of both constructions and provide open-source implementation results demonstrating their practicality. We extensively benchmarked our KVAC protocols and, additionally, bechmarked the efficiency of our SP-MAC-EQ scheme against the original SPS-EQ scheme, showcasing significant performance improvements.

Mariana Gama, Emad Heydari Beni, Jiayi Kang, Jannik Spiessens · 5 authors

In this paper, we show for the first time it is practical to privately delegate proof generation of zkSNARKs to a single server for computations of up to 2^20 R1CS constraints. We achieve this by computing zkSNARK proof generation over homomorphic ciphertexts, an approach we call blind zkSNARKs. We formalize the concept of blind proofs, analyze their cryptographic properties and show that the resulting blind zkSNARKs remain sound when compiled using BCS compilation. Our work follows the framework proposed by Garg et al. (Crypto'24) and improves the instantiation presented by Aranha et al. (Asiacrypt'24), which implements only the FRI subprotocol. By delegating proof generation, we are able to reduce client computation time from 10 minutes to mere seconds, while server computation time remains limited to 20 minutes. We also propose a practical construction for vCOED supporting constraint sizes four orders of magnitude larger than the current state-of-the-art verifiable FHE-based approaches. These results are achieved by optimizing Fractal for the GBFV homomorphic encryption scheme, including a novel method for making homomorphic NTT evaluation packing-friendly by computing it in two dimensions. Furthermore, we make the proofs publicly verifiable by appending a zero-knowledge Proof of Decryption (PoD). We propose a new construction for PoDs optimized for low proof generation time, exploiting modulus and ring switching in GBFV and using the Schwartz-Zippel lemma for proof batching; these techniques might be of independent interest. Finally, we implement the latter protocol in C and report on execution time and proof sizes.

P. Swarna Lakshmi, K. Suresh Kumar

No abstract is available for this record.

Biniyam Deressa, M.A. Hasan

We introduce zkMaP (Zero-Knowledge Succinct Non-Interactive Matrix Multiplication Proofs), a novel non-interactive zero-knowledge proof system for verifying matrix multiplication with significant improvements in efficiency and scalability. Our protocol leverages KZG polynomial commitments and an innovative inner-product reduction technique to reduce the verification of n x n matrix multiplication to a single pairing equation, thereby enabling constant-time verification independent of the matrix size. In particular, zkMaP requires only two pairing operations and produces proofs as small as 320 bytes, yielding a 96 percent reduction in proof size compared to prior schemes. Furthermore, the prover's computational complexity follows the state-of-the-art at O(n^2), with experimental results demonstrating that proofs for 1024 x 1024 matrices can be generated in approximately 12.21 seconds, offering a 16.14x speedup over previous methods. Our implementation also exhibits better memory efficiency, using only 24.58 MB of prover-side RAM for 1024 x 1024 matrices, and supports scalable batch processing, achieving per-proof generation times of 46.79 milliseconds for 1024 instances while maintaining a constant verification time of 3.6 ms.

Yamin Huang

With the rapid expansion of the digital economy ecosystem, blockchain has become the core technology and theoretical path to support data interaction and trusted transactions. However, it still faces significant challenges in terms of privacy protection, transaction traceability and anti-attack capabilities. To address the above challenges, this study proposes a dynamic trust-aware blockchain security algorithm (DTBCSA) based on differential privacy and zero-knowledge proof. This algorithm is used to improve the system robustness and privacy protection capabilities in multiple scenarios. The core design of the algorithm includes: (1) introducing a dynamic trust evaluation mechanism. This mechanism dynamically adjusts the trust level of the node by analyzing its behavioral characteristics and historical interactions. At the same time, the secondary authentication mechanism is activated when the risk threshold is triggered; (2) embedding a differential privacy mechanism in the computing power transaction and model training process. This mechanism protects sensitive data and model parameters through Laplace noise; (3) using zero-knowledge proof to ensure the non-repudiation of transactions. At the same time, the aggregation and parallel optimization strategies are adopted to significantly reduce the computational overhead of proof and verification. In the experimental part, DTBCSA reduced the acceptance rate of malicious transactions from 70% of the baseline to 8% in the computing power trading market simulation. At the same time, it reduced the reputation distribution imbalance (Gini) from 0.42 to 0.20. In the federated learning collaborative training experiment, DTBCSA reduced the success rate of member inference attacks from 81% to 38% under the condition of privacy budget ε=1. While maintaining privacy protection, it improved the model accuracy by about 1.8 percentage points compared to FedDP. In addition, in the zero-knowledge proof verification performance test, DTBCSA reduced the proof size and generation time through aggregation optimization.

Godwin Mandinyenya, Vusumuzi Malele

Blockchain has become a critical enabler of secure data sharing in domains such as healthcare, finance, and digital identity. However, its reliance on classical cryptographic schemes (e.g., RSA, ECDSA, SHA-256) makes current systems vulnerable to emerging quantum computing attacks, raising risks to data confidentiality, integrity, and long-term trust. This paper addresses this challenge by proposing a modular hybrid framework that integrates post-quantum cryptographic (PQC) techniques into blockchain-based personal data sharing. The framework combines lattice-based encryption for protecting off-chain data, hash-based signatures for smart contract authentication, and quantum-safe zero-knowledge proofs and trusted execution environments (TEEs) for privacy-preserving verification and secure key management. To ground this design, we conducted a systematic literature review of 35 studies published between 2018 and 2025, analyzing security, scalability, interoperability, regulatory alignment, and user autonomy. Findings reveal that only 5 out of 35 studies (14%) explicitly addressed quantum threats, with over 80% focusing on theoretical resilience without testing implementation constraints. Furthermore, 90% of proposals neglected smart contract compatibility, and only 8% (3/35) incorporated TEEs, underscoring implementation barriers in contract execution, secure key management, and performance integration. Prototype evaluation demonstrated that the framework sustained 1,500 TPS on Hyperledger Fabric, achieved a 75% reduction in storage bloat using IPFS, and supported GDPR-aligned workflows with 99.98% audit log completion and 95% successful erasure requests. Privacy was further strengthened through zk-STARK proofs, which reduced unauthorized access by 40%, while TEEs improved key management efficiency by ~28%. Although PQC introduced 5–12 seconds of latency, consent revocation was processed in under 2.1 seconds, highlighting both the feasibility and trade-offs of practical post-quantum deployment. This work demonstrates a clear pathway toward quantum-resilient blockchain infrastructures that safeguard personal data, comply with regulatory standards, and maintain user trust in the quantum era.

K.G. Priyashantha

Chapter 5 synthesizes practical strategies, ethical frameworks, and policy recommendations for integrating Metaverse technologies into career development, building on Super&s;s ( 1980 ) career stages. It demonstrates how immersive environments, AI-driven mentorship, and blockchain-secured credentials enhance career exploration, skill acquisition, and lifelong learning while outlining best practices for implementation. Case studies illustrate virtual internships, AR/XR simulations for high-risk professions, and IoT-enabled haptic feedback devices that improve accessibility for individuals with disabilities, ensuring equitable access to Metaverse resources. Ethical considerations address data privacy, algorithmic bias, and the psychological impacts of prolonged virtual immersion. The discussion advocates for transparent AI systems audited for fairness in career recommendations, zero-knowledge proofs for privacy-preserving credential verification, and robust cybersecurity protocols to protect user data. Policy implications highlight updated regulatory frameworks for digital credentialing, intellectual property in virtual spaces, and cross-border recognition of Metaverse-acquired skills. The chapter calls for international collaboration to standardize ethical guidelines, mitigate the digital divide, and ensure marginalized populations benefit from Metaverse advancements. It provides educators, policymakers, and organizations with an actionable roadmap to balance innovation with critical analysis and foster equitable, sustainable career development in the digital age.

V. Dineshbabu, M. Vigenesh

The industrial internet of things (IIoT) expanded fast as physical devices and systems were connected to the internet. However, this interconnectedness made IIoT systems vulnerable to hackers. Intrusion detection systems (IDSs) were put in place to detect and prevent such assaults. Nonetheless, attackers might circumvent IDSs by forging identities or interfering with recorded data. The article intended to improve IIoT security by achieving system confidentiality, integrity, availability, scalability, performance, and security. For IIoT security, the article developed a secure federated learning access control framework (SecureFLACF) linked with a blockchain-based IDS. SecureFLACF used blockchain to secure data collected by IDS, AES-256 encryption to secure stored data, zero-knowledge proof (ZKP) to validate user identities and manage data access, and a federated learning access control framework (FLACF) to train a machine learning model for intrusion detection. SecureFLACF developed as a viable solution for improving IIoT security, providing strong assurances for IDS data and access control using blockchain’s tamper-proof structure and AES-256 encryption. Furthermore, FLACF’s design allows private machine learning model training, ensuring data privacy as well as model fidelity. The framework’s usefulness was highlighted by its application in real-world circumstances, making it a cost-effective option for organisations of all sizes. This method not only strengthened IIoT systems against a wide range of cyber threats, but also stressed their dependability as a safeguard. SecureFLACF exhibited considerable promise for improving IIoT security across several dimensions by encapsulating practicability, cost-effectiveness, and dependability.

Francesco Marcatelli

La crescente digitalizzazione dei giochi da tavolo e di carte ha trasformato profondamente le modalita di interazione tra i giocatori e le piattaforme di gioco, ` estendendo esperienze un tempo limitate a contesti locali verso un ecosistema globale, distribuito e interconnesso. Questa evoluzione, resa possibile dallo sviluppo delle tecnologie web, mobili e blockchain, ha introdotto nuove opportunita ma anche criticit ` a` rilevanti legate alla sicurezza, alla privacy e alla fiducia. A differenza dei giochi fisici, infatti, i giochi digitali si svolgono in ambienti in cui le informazioni sono rappresentate come dati manipolabili, con il rischio concreto di accessi non autorizzati, manipolazioni o alterazioni retroattive dello stato del gioco. Per affrontare tali sfide, la presente tesi analizza l’impiego di protocolli crittografici avanzati nel contesto dei giochi digitali di carte e da tavolo, con particolare attenzione agli scenari in cui non e disponibile un’entit ` a` centralizzata pienamente fidata. Vengono esplorate le principali esigenze di riservatezza, correttezza verificabile, integrita e trasparenza, mettendo in relazione tali requisiti con ` strumenti quali sistemi di commitment, tecniche di verifiable secret sharing, zero-knowledge proofs e protocolli di multi-party computation. L’obiettivo del lavoro e` duplice: da un lato costruire un quadro teorico e classificatorio delle problematiche di sicurezza nei giochi digitali, dall’altro proporre e valutare soluzioni protocollari innovative che bilancino rigore formale, efficienza computazionale e praticita d’uso. Attraverso ` modelli sperimentali e implementazioni prototipali, la tesi intende dimostrare come la crittografia moderna possa abilitare giochi digitali equi, sicuri e resilienti, capaci di promuovere fiducia e trasparenza senza dover dipendere da autorita centrali. In questo ` senso, il contributo mira a gettare le basi per un ecosistema ludico online sostenibile e crittograficamente fondato.

Riccardo Bartolini

La tesi indaga come le primitive crittografiche sostengano sicurezza e integrità di Bitcoin, coniugando teoria e pratica. Si parte dai fondamenti (riservatezza, integrità, autenticazione, non ripudio) e dalle basi di complessità computazionale che giustificano la “one-wayness” degli algoritmi moderni. Vengono presentate cifratura simmetrica e asimmetrica, funzioni hash e l’algoritmo SHA-256 (double hashing), con cenni alla minaccia quantistica e agli standard post-quantum in via di adozione. Sul piano applicativo si descrive l’architettura: blockchain come registro append-only, Merkle tree e Merkle root per verifiche efficienti, gestione di chiavi e indirizzi; firme digitali ECDSA e l’evoluzione SegWit/Taproot con Schnorr e MAST, che riducono malleabilità e ingombro on-chain migliorando privacy ed efficienza. La sezione operativa tratta HD wallet (seed phrase, derivation paths) e schemi avanzati di firma a soglia, evidenziandone impatti su usabilità e rischio. La sicurezza di rete è analizzata attraverso i principali vettori d’attacco (double spending, 51%, address poisoning), il ruolo degli incentivi economici del mining e il retarget della difficoltà che stabilizza il tempo di blocco. Per la privacy si distinguono pseudonimia e anonimato e si valutano tecniche on/off-chain: CoinJoin/PayJoin, Stonewall(x2), Dandelion++ e Lightning Network; si discutono anche Zero-Knowledge Proofs e Self-Sovereign Identity con DIDs/VCs e cornice eIDAS. Infine si affronta la scalabilità: trilemma sicurezza-decentralizzazione-throughput, ottimizzazioni on-chain (SegWit) e soluzioni Layer-2 (Lightning, sidechain), insieme alla governance degli aggiornamenti tramite soft e hard fork. Conclusione: un modello modulare in cui il Layer 1 resta strato di regolamento sicuro, mentre Layer-2 e nuove primitive crittografiche abilitano efficienza, privacy e resilienza nel lungo periodo.

A. G. Ramakrishnan, Shubham Agarwal, Sharmila Kumari Selvanayagam, Kunwar P. Singh

As image generation models grow increasingly powerful and accessible, concerns around authenticity, ownership, and misuse of synthetic media have become critical. The ability to generate lifelike images indistinguishable from real ones introduces risks such as misinformation, deepfakes, and intellectual property violations. Traditional watermarking methods either degrade image quality, are easily removed, or require access to confidential model internals – making them unsuitable for secure and scalable deployment. We are the first to introduce ZK-WAGON, a novel system for watermarking image generation models using the Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARKs). Our approach enables verifiable proof of origin without exposing model weights, generation prompts, or any sensitive internal information. We propose Selective Layer ZK-Circuit Creation (SL-ZKCC), a method to selectively convert key layers of an image generation model into a circuit, reducing proof generation time significantly. Generated ZK-SNARK proofs are imperceptibly embedded into a generated image via Least Significant Bit (LSB) steganography. We demonstrate this system on both GAN and Diffusion models, providing a secure, model-agnostic pipeline for trustworthy AI image generation.

Чепис, О. І.

The article presents a comprehensive study of the phenomenon of digital identity in the context of contemporary challenges to the protection and safeguarding of human rights under conditions of global digital transformation and the rapid development of virtual environments. It is emphasized that the growing scale of the collection and processing of personal and confidential data, the increasing reliance on algorithmic decision-making systems, and the gradual displacement of direct human involvement in identification and control processes highlight the need to reconsider conceptual, legal, and ethical approaches to the regulation of digital identity. It is established that the right to identity still lacks unified recognition in international legal instruments, resulting in multiple doctrinal approaches—ranging from its understanding as an autonomous subjective right to its definition as a tool for accessing other rights or even as a potential threat to their realization. The evolution of digital identity is traced from basic authentication mechanisms to multi-layered structures integrating personal characteristics, behavioral patterns, biometric data, and users’ digital footprints. Key risks are identified, including discrimination, social exclusion of vulnerable groups, unjustified profiling, excessive surveillance, misuse of data, and the potential use of identification systems as tools of political or social pressure. The positions of international institutions on the conceptualization of digital identity and its relationship with human rights are analyzed. Promising technological solutions for balancing security and privacy are proposed, including decentralized blockchain-based identification with integrated smart contracts, zero-knowledge proof protocols, biometric verification, and verified account labeling. It is argued that the optimal model of digital identification in virtual environments should combine technological reliability, flexibility, ethical soundness, and compliance with international standards, ensuring a balance between the right to privacy, effective authentication, and the preservation of user trust in digital infrastructure.