Juan Alamrio Berrios Moya, John Ayoade, Md. Ashraf Uddin
Academic credential fraud presents a significant challenge to the global academic and labor markets, undermining the credibility of legitimate qualifications. In this paper, we introduce ZKBAR-V, a Zero-Knowledge Proof-Enabled Blockchain-Based Academic Record Verification System. This system is designed to provide a privacy-preserving, immutable, and secure framework for managing academic credentials. The proposed system leverages zkEVM smart contracts on a blockchain-based infrastructure that enables credential verification without exposing underlying data. The approach integrates Decentralized Identifiers (DIDs) to standardize identity management while eliminating reliance on centralized authorities. We have used dual-blockchain, which separates public and private information, which can enhance both efficiency and privacy. In addition, this approach employs the Interplanetary File System (IPFS) for decentralized and secure document storage. ZKBAR-V is designed as an open-source, interoperable solution with a standardized Application Programming Interface (API) for seamless integration. We implemented the system and conducted comprehensive testing, which demonstrates its capability to manage transactions securely, maintain privacy, and reduce costs compared to traditional Ethereum mainnet-based solutions. By combining advanced blockchain technologies, decentralized storage, and globally unique identifiers, ZKBAR-V offers a scalable, adaptable, and robust solution for academic credential management. This strategy can significantly enhance credential integrity, promote global student mobility, and provide institutions worldwide with a trustworthy and efficient verification system.
Theorem proving serves as a major testbed for evaluating complex reasoning abilities in large language models (LLMs). However, traditional automated theorem proving (ATP) approaches rely heavily on formal proof systems that poorly align with LLMs' strength derived from informal, natural language knowledge acquired during pre-training. In this work, we propose DeepTheorem, a comprehensive informal theorem-proving framework exploiting natural language to enhance LLM mathematical reasoning. DeepTheorem includes a large-scale benchmark dataset consisting of 121K high-quality IMO-level informal theorems and proofs spanning diverse mathematical domains, rigorously annotated for correctness, difficulty, and topic categories, accompanied by systematically constructed verifiable theorem variants. We devise a novel reinforcement learning strategy (RL-Zero) explicitly tailored to informal theorem proving, leveraging the verified theorem variants to incentivize robust mathematical inference. Additionally, we propose comprehensive outcome and process evaluation metrics examining proof correctness and the quality of reasoning steps. Extensive experimental analyses demonstrate DeepTheorem significantly improves LLM theorem-proving performance compared to existing datasets and supervised fine-tuning protocols, achieving state-of-the-art accuracy and reasoning quality. Our findings highlight DeepTheorem's potential to fundamentally advance automated informal theorem proving and mathematical exploration.
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang · 6 authors
Cautious predictions -- where a machine learning model abstains when uncertain -- are crucial for limiting harmful errors in safety-critical applications. In this work, we identify a novel threat: a dishonest institution can exploit these mechanisms to discriminate or unjustly deny services under the guise of uncertainty. We demonstrate the practicality of this threat by introducing an uncertainty-inducing attack called Mirage, which deliberately reduces confidence in targeted input regions, thereby covertly disadvantaging specific individuals. At the same time, Mirage maintains high predictive performance across all data points. To counter this threat, we propose Confidential Guardian, a framework that analyzes calibration metrics on a reference dataset to detect artificially suppressed confidence. Additionally, it employs zero-knowledge proofs of verified inference to ensure that reported confidence scores genuinely originate from the deployed model. This prevents the provider from fabricating arbitrary model confidence values while protecting the model's proprietary details. Our results confirm that Confidential Guardian effectively prevents the misuse of cautious predictions, providing verifiable assurances that abstention reflects genuine model uncertainty rather than malicious intent.
We construct an empirically founded model of a repo trade intermediated by two broker-dealers and prove multiple equilibrium and the existence of equilibrium at the joint profit maximizing volume of trade. We then present a smart contract that resolves multiple equilibrium by requiring each broker-dealer to report its client schedule and its minimum hurdle spread, and implementing a selection rule that filters out hurdle-infeasible outcomes. Whenever there exists an equilibrium that exceeds both hurdle spreads, the protocol selects the joint profit maximizing feasible trade and thereby avoids a collapse to no trade. The smart contract is a machine executed algorithm which eliminates the need for trust. Hardware and cryptography are used to prevent leakage of broker-dealer client trade schedules, and to enable privacy-protected auditing with zero-knowledge proofs of the integrity of computations. The outcome can be implemented by a myopic strategy where a broker-dealer truthfully reports its own variables without anticipating its counterparty's reports. This minimizes cognitive and computational complexity, thereby making our smart contract suitable for real-world deployment.
Caixiang Fan, Amirhossein Sohrabbeig, Petr Musı́lek
Blockchain-based peer-to-peer energy trading enables individuals to directly share renewable energy using Internet of Things technologies. However, it faces significant challenges related to privacy, scalability, and the integration of advanced artificial intelligence. To address these issues, this article proposes zkPET, a secure and intelligent peer-to-peer energy trading framework. zkPET integrates machine learning and blockchain with advanced cryptographic techniques of zero-knowledge machine learning to protect user data while enabling intelligent decision making. In the zkPET framework, the computationally intensive operations of various machine learning models are executed off-chain, and only succinct cryptographic proofs of these computations are uploaded to the blockchain for verification and recording. In addition, a time-series clustering approach is incorporated into federated learning to enhance both inference accuracy and the efficiency of proof generation. Experimental validation using the zero-knowledge proof tool EZKL and a real-world electricity dataset demonstrates the feasibility and effectiveness of zkPET. The results underscore its potential to significantly improve privacy, scalability, and computational efficiency in decentralized energy trading, contributing to the advancement of secure and intelligent energy markets.
Federated Learning (FL) has emerged as a critical paradigm for enabling privacy-preserving machine learning, particularly in regulated sectors such as finance and healthcare. However, standard FL strategies often encounter significant operational challenges related to fault tolerance, system resilience against concurrent client and server failures, and the provision of robust, verifiable privacy guarantees essential for handling sensitive data. These deficiencies can lead to training disruptions, data loss, compromised model integrity, and non-compliance with data protection regulations (e.g., GDPR, CCPA). This paper introduces Differentially Private Resilient Temporal Federated Learning (DP-RTFL), an advanced FL framework designed to ensure training continuity, precise state recovery, and strong data privacy. DP-RTFL integrates local Differential Privacy (LDP) at the client level with resilient temporal state management and integrity verification mechanisms, such as hash-based commitments (referred to as Zero-Knowledge Integrity Proofs or ZKIPs in this context). The framework is particularly suited for critical applications like credit risk assessment using sensitive financial data, aiming to be operationally robust, auditable, and scalable for enterprise AI deployments. The implementation of the DP-RTFL framework is available as open-source.
Decentralized and Connected Autonomous Vehicle (CAV) networks offer promising advances in safety, efficiency, and real-time decision-making. However, they face significant challenges in authentication, privacy, and scalability—especially in the face of quantum adversaries. This paper proposes a novel post-quantum secure framework that integrates lattice-based Zero-Knowledge Proofs (ZKPs), optimized Binius proofs, and Multi-Layer Compressed Counting Bloom Filters (ML-CCBF) to enable privacy-preserving authentication and model verification in decentralized CAV environments. Our lattice-based ZKP scheme achieves cryptographic commitments in under 5μs, while Binius proofs verify model integrity in less than 0.17 seconds per update. ML-CCBF ensures scalable membership filtering with 0% false positives across 1000 nodes. Experimental results confirm 100% ZKP soundness, strong resilience against simulated quantum and adaptive attacks, and stable latency under increasing network load. These findings demonstrate that our framework delivers quantum-resilient security, real-time efficiency, and robust scalability, offering a viable solution for trustworthy decentralized intelligence in next-generation vehicular systems.
India’s dynamic socio-economic landscape and vast geography necessitate efficient and equitable public service delivery mechanisms, especially in areas like inter-state travel for citizens eligible for complimentary or concessional passes. Traditional systems used for issuing such privilege passes suffer from inefficiencies, fraud vulnerabilities, and inconsistent verification standards across states. This paper proposes a novel smart contract- based authentication mechanism built on a permissioned blockchain architecture to automate and secure the issuance of privilege passes for inter-state travel within India. By integrating Aadhaar-based digital identity verification and leveraging the immutability and transparency of blockchain, this approach enables real-time, verifiable, and tamper-proof pass issuance, while minimizing administrative overhead. The proposed system operates through a consortium-led blockchain network composed of central and state transport authorities and public sector technology partners. Smart contracts deployed on this network enforce eligibility rules automatically by interacting with off-chain data sources—referred to as oracles—that provide income, age, or employment status of applicants. Once eligibility is validated, a digital privilege pass is issued, cryptographically linked to the citizen’s identity and stored on-chain. These digital passes can be presented through QR codes and verified instantly by transport officials using mobile applications. Key features of this system include tamper-resistant records, zero-knowledge proof support for privacy preservation, and revocation capabilities for dynamic eligibility management. Aadhaar e-KYC ensures that only legitimate individuals are granted benefits, while the use of hashed identifiers on-chain preserves personal privacy. Furthermore, the permissioned nature of the blockchain network ensures compliance with national data protection laws while allowing rapid consensus and controlled access. By introducing automation, auditability, and interoperability into the travel concession ecosystem, this framework significantly reduces the risk of misuse, streamlines citizen experience, and enhances governance efficiency. The solution supports pan-India applicability and is adaptable to the varied policy rules across different states. Its modular design also enables future expansion to other welfare services, such as subsidized healthcare or education benefits. This paper outlines the technical architecture, smart contract workflow, governance model, and potential challenges in implementing such a system. The integration of decentralized technologies in public service infrastructure marks a progressive step toward a transparent, efficient, and citizen-centric Digital India.
Filippo Scaramuzza, Giovanni Quattrocchi, Damian A. Tamburri
As Artificial Intelligence (AI) systems, particularly those based on machine learning (ML), become integral to high-stakes applications, their probabilistic and opaque nature poses significant challenges to traditional verification and validation methods. These challenges are exacerbated in regulated sectors requiring tamper-proof, auditable evidence, as highlighted by apposite legal frameworks, e.g., the EU AI Act. Conversely, Zero-Knowledge Proofs (ZKPs) offer a cryptographic solution that enables provers to demonstrate, through verified computations, adherence to set requirements without revealing sensitive model details or data. Through a systematic survey of ZKP protocols, we identify five key properties (non-interactivity, transparent setup, standard representations, succinctness, and post-quantum security) critical for their application in AI validation and verification pipelines. Subsequently, we perform a follow-up systematic survey analyzing ZKP-enhanced ML applications across an adaptation of the Team Data Science Process (TDSP) model (Data & Preprocessing, Training & Offline Metrics, Inference, and Online Metrics), detailing verification objectives, ML models, and adopted protocols. Our findings indicate that current research on ZKP-Enhanced ML primarily focuses on inference verification, while the data preprocessing and training stages remain underexplored. Most notably, our analysis identifies a significant convergence within the research domain toward the development of a unified Zero-Knowledge Machine Learning Operations (ZKMLOps) framework. This emerging framework leverages ZKPs to provide robust cryptographic guarantees of correctness, integrity, and privacy, thereby promoting enhanced accountability, transparency, and compliance with Trustworthy AI principles.
Ken Huang, Vineeth Sai Narajala, John Yeoh, Jason Ross · 9 authors
Traditional Identity and Access Management (IAM) systems, primarily designed for human users or static machine identities via protocols such as OAuth, OpenID Connect (OIDC), and SAML, prove fundamentally inadequate for the dynamic, interdependent, and often ephemeral nature of AI agents operating at scale within Multi Agent Systems (MAS), a computational system composed of multiple interacting intelligent agents that work collectively. This paper posits the imperative for a novel Agentic AI IAM framework: We deconstruct the limitations of existing protocols when applied to MAS, illustrating with concrete examples why their coarse-grained controls, single-entity focus, and lack of context-awareness falter. We then propose a comprehensive framework built upon rich, verifiable Agent Identities (IDs), leveraging Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), that encapsulate an agents capabilities, provenance, behavioral scope, and security posture. Our framework includes an Agent Naming Service (ANS) for secure and capability-aware discovery, dynamic fine-grained access control mechanisms, and critically, a unified global session management and policy enforcement layer for real-time control and consistent revocation across heterogeneous agent communication protocols. We also explore how Zero-Knowledge Proofs (ZKPs) enable privacy-preserving attribute disclosure and verifiable policy compliance. We outline the architecture, operational lifecycle, innovative contributions, and security considerations of this new IAM paradigm, aiming to establish the foundational trust, accountability, and security necessary for the burgeoning field of agentic AI and the complex ecosystems they will inhabit.
Traditional voting systems face significant challenges, including susceptibility to fraud, lack of transparency, and privacy concerns. Centralized electronic voting systems, while improving accessibility, often suffer from vulnerabilities such as tampering, single points of failure, and insufficient auditability. This project proposes a blockchain-based distributed electronic voting system that leverages smart contracts to ensure voter privacy, ballot integrity, and decentralized verification. The system employs cryptographic techniques such as zero-knowledge proofs (ZKPs) to anonymize voter identities while maintaining a verifiable audit trail on an immutable blockchain ledger. Smart contracts automate vote tallying, enforce voting rules (e.g., eligibility checks, one-vote-per- voter), and ensure tamper-proof execution of electoral processes. A permissioned blockchain network enhances scalability and reduces energy consumption compared to public blockchains. The system also incorporates multi-factor voter authentication and end- to-end encryption to safeguard against unauthorized access. By decentralizing control and enabling real-time transparency, this solution addresses critical flaws in existing systems, reduces electoral fraud, and strengthens public trust in democratic processes. The proposed architecture is implemented using Hyperledger Fabric for blockchain operations and Ethereum-based smart contracts, ensuring high performance, security, and compliance with electoral regulations.
Electronic voting (e-voting) has emerged as a transformative technology in the modern digital era. Many countries across the world are using e-voting systems in different types of elections, from political to non-political. One of the primary goals of e-voting is ensuring both verifiability and privacy simultaneously, which we refer to as security. Verifiability is a security feature that guarantees voters can confirm their vote is reflected in the final election result, while privacy guarantees that no one is able to link a vote to the voter who cast it. Verifiability needs to hold only for the duration of the election, whereas privacy needs to extend beyond the election period, even decades after the election. This property, known as everlasting privacy in the literature, ensures that even computationally unbounded adversaries cannot compromise voter privacy, securing elections against future advances in computing, including quantum computing. Researchers have proposed a wide variety of protocols to achieve this ambitious goal in secure e-voting, however, these protocols differ significantly, making the analysis and state-of-the-art complicated. In this thesis, we first address this fragmentation by systematically analyzing all existing e-voting protocols designed to ensure everlasting privacy. We map out the relationships and dependencies among these protocols, evaluate their security and efficiency under realistic assumptions, and identify unresolved challenges in the field. Our work provides a foundational reference for researchers aiming to design secure e-voting systems with everlasting privacy, paving the way for privacypreserving elections in the post-quantum era. Building on these insights, we propose a novel e-voting system that integrates the best practices from prior research while addressing their limitations. Leveraging the Hyperion scheme as a foundation, we develop an enhanced protocol that not only guarantees everlasting privacy but also introduces everlasting receipt-freeness and coercion mitigation. Unlike existing systems like Selene and Hyperion, which rely on computational assumptions for privacy, our protocol offers privacy even against adversaries with unlimited computational power. In secure electronic voting systems with everlasting privacy, the focus is on futureproofing privacy, while sometimes election verifiability relies on the computational soundness of zero-knowledge proofs (ZKP), which are vulnerable to quantum adversaries. Therefore, a key technical challenge is designing e-voting systems with efficient post-quantum cryptographic primitives to secure both privacy and verifiability against quantum attacks. In this thesis, we advance the state of post-quantum ZKPs by focusing on the ZKPs proposed by Jain et al., which are based on the conservative Learning Parity with Noise (LPN) assumption. We optimize the efficiency of these ZKPs, achieve formal security verification using EasyCrypt, and uncover flaws in existing implementations, demonstrating their vulnerability to malicious provers. Additionally, we construct the first code-based ZKP of shuffle, enabling a verifiable and privacy-preserving e-voting protocol with mixing-based tallying. Our e-voting system ensures both verifiability and vote privacy through the computational difficulty of decoding random linear codes, marking it as the first verifiable code-based e-voting system.
Electronic voting systems have long been proposed as a means of modernizing democratic participation by improving accessibility, reducing administrative costs, and accelerating electoral processes. Nevertheless, existing electronic voting architectures frequently rely upon centralized infrastructures that introduce significant challenges concerning transparency, security, auditability, and public trust. Blockchain technology has emerged as a promising alternative capable of addressing many of these limitations through decentralization, immutability, and distributed consensus. Despite considerable research activity, many proposed blockchain voting solutions remain conceptual, while relatively few studies present fully implemented and experimentally evaluated frameworks integrating multiple complementary security mechanisms.This study presents the design, implementation, and evaluation of a secure blockchain-based electronic voting framework built upon Hyperledger Fabric 2.4. The proposed architecture integrates smart contracts, distributed consensus mechanisms, AES-256 cryptographic vote protection, a conceptual zero-knowledge proof layer, and Merkle-tree-based integrity verification within a permissioned blockchain environment. A functional prototype was implemented in Go chaincode and deployed within a simulated regional election scenario representing the four prefectures of Crete, Greece.The study adopts a Design Science Research methodology and evaluates the proposed framework through a series of functional, security, and scalability experiments. The evaluation examined voter eligibility enforcement, duplicate vote prevention, ballot confidentiality, ledger integrity, auditability, and resistance against five distinct attack scenarios, including unauthorized ballot modification, ballot injection, and timestamp manipulation.The findings demonstrate that the proposed framework successfully preserves voter anonymity, prevents duplicate voting, detects unauthorized modifications in all tested scenarios, and enables transparent and independently verifiable election outcomes. While the results confirm the suitability of permissioned blockchain architectures for secure digital elections, several challenges remain, particularly regarding scalability, endpoint security, legal compliance, and large-scale deployment.Overall, this study contributes both a practical implementation and an empirical evaluation of a blockchain-enabled electoral infrastructure, providing insights into the future development of secure digital democratic systems.
We present a secure and efficient string-matching platform leveraging zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) to address the challenge of detecting sensitive information leakage while preserving data privacy. Our solution enables organizations to verify whether private strings appear on public platforms without disclosing the strings themselves. To achieve computational efficiency, we integrate a sliding window technique with the Rabin-Karp algorithm and Rabin Fingerprint, enabling hash-based rolling comparisons to detect string matches. This approach significantly reduces time complexity compared to traditional character-by-character comparisons. We implement the proposed system using gnark, a high-performance zk-SNARK library, which generates succinct and verifiable proofs for privacy-preserving string matching. Experimental results demonstrate that our solution achieves strong privacy guarantees while maintaining computational efficiency and scalability. This work highlights the practical applications of zero-knowledge proofs in secure data verification and contributes a scalable method for privacy-preserving string matching.
Federated Learning (FL) enables collaborative model training across hospitals while keeping patient data local, thus aiming to satisfy strict healthcare privacy regulations (e.g. HIPAA, GDPR). However, FL still leaks information via shared model updates, exposing it to membership inference and gradient inversion attacks. In this work, we propose an end-to-end framework that integrates zero-knowledge proofs (ZKPs) with FL to ensure both data privacy and trust in the aggregation process. In our design, each hospital (client) sends encrypted model updates to a central aggregator, which then computes the global model and simultaneously generates a succinct ZKP (e.g. a zk-SNARK) attesting to the correctness of the aggregation. Clients (or a verifier network) can efficiently verify this proof without learning any additional information. We simulate a disease-prediction task on synthetic medical data and evaluate metrics including predictive accuracy, proof generation/verification time, and communication overhead. Our results (see Table 1 and Fig. 3) show that incorporating ZKP maintains almost identical model accuracy compared to standard FL while adding moderate computational and bandwidth overhead. ZKP verification costs scale favorably (often <50% of proof generation time) and can be offloaded to a blockchain network to avoid burdening resource-constrained hospitals. The key contribution is a structured ZK-FL framework combining FL and zk-SNARKs, along with a formal threat model. This approach closes FL’s trust gap in healthcare settings, and suggests future work on scalable proof systems (e.g. post-quantum ZKPs) and integration with blockchain-based verifiers.
The main motivation of this thesis is the uncertain panorama of cybersecurity risks and threats, accentuated by the arrival of the quantum computer. This type of computer is completely disruptive, since its operation is governed by quantum mechanical phenomena. The implementation of Shors algorithm in a quantum computer with relevant size and performance will allow breaking the security of the most currently used pre-quantum asymmetric algorithms. This panorama makes it necessary to research new cryptographic paradigms that are resistant to quantum threats. Thus, quantum and post-quantum cryptography emerge. Several national security agencies are recommending the immediate migration to quantum-resistant solutions of vulnerable critical cryptosystems, mainly by implementing post-quantum algorithms, some of them recently standardized. Quantum cryptography bases its security on the same physical foundations as quantum computers, being independent of the computational capacity of an adversary. The implementation of solutions based on quantum cryptography still requires greater technological maturity, development of standards and certification of devices. In addition, the infrastructures necessary for these networks are expensive and difficult to scale, in their current conception, due to the need to have trusted intermediate nodes. However, the rapid advances in this field allow to further research quantum communications networks to be a reality for daily operations where a high level of security is required. The main objective of this thesis is to investigate quantum cryptography-based solutions that go beyond quantum key distribution (QKD). The thesis has focused on proposing two novel cryptographic mechanisms ensuring that the new protocols are comparable in efficiency with pre-quantum and post-quantum algorithms. Furthermore, it has been taken into account that these protocols are implementable in current quantum communications infrastructures (QCI) to maximize the technical benefit of the investments carried out for these deployments. As a result, a quantum-assisted digital signature protocol (Q-DS) and a quantum zero-knowledge proof (QZKP) have been proposed, analyzed and implemented, which combine symmetric pre-quantum mechanisms with QKD. The proposed quantum-assisted digital signature protocol avoids the use of vulnerable pre- quantum public-key cryptosystems, using symmetric keys generated by QKD and using them with widely known NIST-approved hash functions, giving rise to a composite cryptosystem whose security against various attacks is demonstrated. For its part, the proposed quantum zero-knowledge proof allows the authentication of users in a QCI without revealing personal information during the process. The proposal of a quantum version of ZKP has been done in this thesis for the very first time, without precedent in the literature. A theoretical study as well as experimental tests have been carried out, resulting in a secure and efficient authentication mechanism. Finally, given the industrial nature of this thesis, the evolution of the political panorama regarding quantum technologies and PQC have been closely followed, including the positions of relevant security-oriented organizations and economic investments for project funding. These issues, although not technical, have influenced the design of the cryptographic protocols proposed in this thesis. RESUMEN La principal motivación de esta tesis es el panorama incierto de los riesgos y amenazas de ciberseguridad, acentuado por la llegada del ordenador cuántico. Este tipo de ordenadores son completamente disruptivos, ya que su funcionamiento se rige por fenómenos mecánico-cuánticos. La implementación del algoritmo de Shor en un ordenador cuántico con tamaño y rendimiento relevantes permitirá romper la seguridad de los algoritmos asimétricos pre-cuánticos más utilizados actualmente. Este panorama hace necesario investigar nuevos paradigmas criptográficos que sean resistentes a las amenazas cuánticas. Así, surgen la criptografía cuántica y post-cuántica. Varias agencias de seguridad nacional han recomendado la migración inmediata de los criptosistemas críticos vulnerables a soluciones "quantum-resistant", principalmente mediante la implementación de algoritmos post-cuánticos, algunos de ellos recientemente estandarizados. La criptografía cuántica basa su seguridad en los mismos fundamentos físicos que los ordenadores cuánticos, siendo independiente de la capacidad computacional de un adversario. La implementación de soluciones basadas en criptografía cuántica aún requiere de mayor madurez tecnológica, desarrollo de estándares y certificación de dispositivos. Además, las infraestructuras necesarias para estas redes son costosas y difíciles de escalar, en su concepción actual, debido a la necesidad de contar con nodos intermedios de confianza. Sin embargo, los rápidos avances en este campo permiten que la investigación de las redes de comunicaciones cuánticas se vaya convirtiendo en una realidad para las operaciones diarias donde se requiere un alto nivel de seguridad. El objetivo principal de esta tesis es investigar soluciones basadas en criptografía cuántica que vayan más allá de la distribución de claves cuánticas (QKD). La tesis se ha centrado en proponer dos mecanismos criptográficos novedosos asegurando que los nuevos protocolos sean comparables en eficiencia con algoritmos pre-cuánticos y post-cuánticos. Además, se ha tenido en cuenta que estos protocolos sean implementables en las actuales infraestructuras de comunicaciones cuánticas (QCI) para maximizar el beneficio técnico de las inversiones realizadas para estos despliegues. Como resultado, se han propuesto, analizado e implementado un protocolo de firma digital asistido por claves cuánticas (Q-DS) y una prueba de conocimiento cero cuántica (QZKP), que combinan mecanismos pre-cuánticos simétricos con QKD. El protocolo de firma digital cuántica propuesto evita el uso de criptosistemas de clave pública pre-cuánticos vulnerables, utilizando claves simétricas generadas por QKD y utilizándolas con funciones hash ampliamente conocidas aprobadas por el NIST, dando lugar a un criptosistema compuesto cuya seguridad frente a diversos ataques se demuestra. Por su parte, la QZKP propuesta permite la autenticación de usuarios en una QCI sin revelar información personal durante el proceso. La propuesta de una versión cuántica de ZKP se ha realizado en esta tesis por primera vez, sin precedentes en la literatura. Se ha realizado un estudio teórico así como pruebas experimentales, dando como resultado un mecanismo de autenticación seguro y eficiente. Finalmente, dada la naturaleza industrial de esta tesis, se ha seguido de cerca la evolución del panorama político en relación con las tecnologías cuánticas y PQC, incluyendo las posiciones de las organizaciones relevantes en materia de seguridad y las inversiones económicas para la financiación de proyectos. Estas cuestiones, aunque no técnicas, han influido en el diseño de los protocolos criptográficos propuestos en esta tesis.
The developing Sixth-Generation (6G) network aims to establish seamless global connectivity for billions of humans, machines, and devices. However, the rich digital service and explosive heterogeneous connection between various entities in 6G networks can not only induce increasing complications of digital identity management but also raise material concerns about the security and privacy of user identity. In this paper, we design a user-centric identity management that returns the sole control to the user self and achieves identity sovereignty towards 6G networks. Specifically, we propose a blockchain-based Identity Management (IDM) architecture for 6G networks, which provides a practical method to secure digital identity management. Subsequently, we develop a fully privacy-preserving identity attribute management scheme by using zero-knowledge proof to protect the privacy-sensitive identity attribute. In particular, the scheme achieves an identity attribute hiding and verification protocol to support users in obtaining and applying their identity attributes without revealing concrete data. Finally, we analyze the security of the proposed architecture and implement a prototype system to evaluate its performance. The result shows that our proposed architecture can ensure that users effectively manage their digital identity in 6G networks.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
S. M. Dilip Kumar, Namrta Tanwar, Namrta Tanwar, Aakarsh Chandna · 5 authors
The blockchain technology has disrupted the earlyage digital banking through concepts like bitcoin and ether [1,3].In this study, some major elements of the blockchain technology are examined-decentralized networks, smart contracts, cryptographic techniques, and consensus mechanisms of Proof of Work and Proof of Stake usage-and understanding how they contribute to safe, peer-to-peer transactions without intermediaries [2,5].Bitcoin can do no more than about seven transactions a second (TPS) is a very paltry competition of an impressive 30 to 40 TPS of Ethereum.This depicts the ongoing scalability challenges that need to be tackled by initiatives linked with Ethereum 2.0 and the Lightning Network [4,9].While most industries, apart from banking, have effectively made their blockchain applications and transparency useful-Supply Chain Management, Healthcare, and DeFi-currently poses challenges of transaction speed limitations, the vagueness of regulations, and energy consumption by mining [8].Emerging trends include Non-Fungible Tokens (NFTs), Central Bank Digital Currencies (CBDCs), and privacy enhanced through zero-knowledge proofs.There is hope for excellent feedback on the future of the blockchain from these and other initiatives yet to come into reality.
Web Assembly (Wasm) and blockchain technology offer a viable solution for reliable and high-performance front-end systems. Wasm provides high execution speeds by incorporating code from high-level languages to improvise on performance limitations. Its sand-boxed execution model enhances security by extenuating memory-related weaknesses. Similarly, blockchain reinforces security with decentralized, tamper-resistant data structures and smart contracts. Conventional blockchain frameworks often suffer from computational overhead, but Wasm-based execution platforms like Polkadot and EOS optimize resource utilization and improve interoperability. This integration facilitates high-speed, reliable interactions in decentralized applications (dApps). Potential benefits include fast and secure off-chain computations, hence reducing blockchain congestion in front-end frameworks. However, challenges remain in securing Wasm execution in decentralized environments and optimizing blockchain and Wasm interoperability. A promising direction is to exploit Just-In-Time (JIT), Ahead-of-Time (AOT) compilation schemes along with zero-knowledge proofs to further enhance performance and security characteristics. By coupling Wasm’s efficiency with blockchain’s security, scalable and decentralized front-end systems are evolving to meet challenging web demand scenarios.
In the current digital landscape, the demand for robust and layered security frameworks has intensified due to the increasing frequency and complexity of cyber threats. Cryptography and cybersecurity, though different in focus, are closely aligned and collectively form the core of modern digital defense strategies. Cryptography provides essential tools—such as encryption, hashing, and digital signatures—that safeguard the confidentiality, integrity, and authenticity of information. Cybersecurity builds on these techniques to implement policies and systems that protect against unauthorized access, data breaches, and malicious attacks. This paper examines the evolving connection between cryptography and cybersecurity, focusing on the development of cryptographic methods and their application in securing digital protocols like SSL/TLS, blockchain technologies, and public key infrastructures. Real-world use cases from healthcare, finance, and government are explored, highlighting the role of cryptographic integration in meeting regulatory standards like GDPR, HIPAA, and FISMA. The study also explores current challenges such as key management, scalability, and the threat posed by quantum computing. It further reviews emerging technologies including post-quantum cryptography, zero-knowledge proofs, and the integration of AI and machine learning for proactive, intelligent cybersecurity solutions.
This article examines the evolving landscape of blockchain technology as a security framework across diverse domains. Blockchain's fundamental architecture—based on decentralization, immutability, transparency, and cryptographic security—offers distinctive advantages in addressing contemporary cybersecurity challenges. The article explores established implementations and cutting-edge innovations in blockchain security, including decentralized identity management, supply chain integrity verification, quantum-resistant cryptography, cross-chain interoperability protocols, and integration with artificial intelligence. Zero-knowledge proofs and other privacy-enhancing techniques are evaluated for their contribution to confidential yet verifiable transactions. Throughout these applications, blockchain demonstrates its capacity to create resilient systems that establish trust without centralized authorities, maintain data integrity in adversarial environments, and adapt to emerging threats. By shifting security paradigms from centralized to distributed models, blockchain technology presents transformative solutions to persistent vulnerabilities in digital infrastructure.
The inevitable advance of quantum computing presents significant challenges to current API security frameworks that predominantly rely on classical cryptographic algorithms. This article examines how emerging post-quantum cryptographic technologies are reshaping API security landscapes in preparation for a quantum-capable future. From lattice-based algorithms like CRYSTALS-Kyber and Dilithium to Quantum Key Distribution networks achieving secure communications across intercontinental distances, a new generation of security mechanisms is being developed to safeguard API infrastructures against quantum threats. Beyond defensive applications, quantum computing offers transformative capabilities for API operations, including enhanced traffic prediction through variational quantum circuits, intelligent resource allocation with unprecedented accuracy, and anomaly detection systems capable of identifying sophisticated attack patterns that evade conventional monitoring. The integration of quantum-resistant Zero-Knowledge Proofs is simultaneously enhancing authentication processes while minimizing credential exposure. Together, these innovations are creating a comprehensive framework for API security that not only protects against future quantum threats but delivers immediate benefits in performance, privacy, and operational efficiency for organizations dependent on API communications.
Abstract: In modern democracies, secure and transparent voting mechanisms are critical for ensuring public trust and electoral integrity. Traditional voting systems often face challenges such as tampering, identity fraud, and lack of transparency. This paper proposes a Blockchain-Based Voting System designed to address these issues by integrating advanced technologies including Zero-Knowledge Proofs (ZKP), InterPlanetary File System (IPFS), and the Polygon Proof-of-Stake (PoS) blockchain. The system incorporates Aadhaar-based identity verification with OTP authentication to ensure that only eligible citizens can vote, while preserving voter anonymity through the implementation of ZKP. All sensitive data, including votes and candidate information, are recorded on the decentralized Polygon network, ensuring immutability and transparency. IPFS is employed for storing large files such as candidate profiles and voting records in a secure and distributed manner. Smart contracts automate the core election functions such as vote casting, validation, and result declaration, thereby minimizing the risk of human error and manipulation. A modular user interface is provided for both voters and election administrators, facilitating real-time monitoring, seamless authentication, and secure participation. By leveraging blockchain’s trustless architecture and privacypreserving cryptographic protocols, the proposed system aims to modernize the electoral process, enhance voter confidence, and strengthen democratic institutions in the digital age.The architecture ensures end-to-end verifiability, making each vote independently auditable without compromising confidentiality. This integration of privacy, security, and scalability offers a robust foundation for next-generation electoral systems.
Team lead at Upland.me Poland, Warsaw, Poltavskyi Dmytro
This article examines the role cryptographic methods play in protecting digital assets through blockchain systems, with a particular focus on their adjustment to contemporary challenges and technological trends. An endeavor is undertaken to systematize major cryptographic algorithms, their effective appraisal in data protection, and development prospects under quantum computing threats. The study is relevant because centralized systems increasingly depend on cryptography due to greater regulatory pressures and, above all, a need for security through secrecy. The scientific novelty lies in the detailed comparative analysis of the said methodology (hashing, digital signatures, zero-knowledge proofs) for cases relating to major blockchain platforms (Bitcoin, Ethereum, Zcash), which hence demonstrate varied approaches towards security provision. The study's methodological foundation consists of analyzing 13 sources, merging a qualitative examination of algorithms and ECDSA with zk-SNARKs with a quantitative assessment of their effectiveness. Hash functions and Merkle trees ensure data integrity while reducing the computational costs of verification; asymmetric cryptography and Zero-Knowledge Proofs guarantee authenticity and confidentiality for the function of the transaction. Main findings support that cryptography is the cornerstone technology for blockchain security, but it has to be tailored to meet new challenges. Development in post-quantum algorithms and the infusion of homomorphic encryption will soon become imperative for quantum threats. This paper strongly advocates hybrid solutions that would bring traditional ways merged with novelties, which will provide sustainability over time for digital assets. Thus, this article will be useful for Developers of Blockchain Systems, Cryptographers, Cybersecurity Experts, & Regulators willing to know how protection methods for digital assets evolve.