The state-of-the-art review comprehensively examines access control mechanisms for securing cloud computing environments, emphasizing their architectural evolution and performance efficiency. Conventional access control models such as Role Based Access Control (RBAC) and Attribute Based Encryption (ABE), though widely adopted, continue to face limitations including single points of failure, centralized policy management, and limited transparency in audit trails. Recent studies report average encryption and decryption times below one second in conventional schemes, yet these models struggle with scalability and dynamic revocation in distributed settings. The integration of blockchain technology addresses many of these challenges through its decentralized, immutable, and transparent infrastructure. Blockchain based access control frameworks implemented on platforms such as Hyperledger Fabric and Ethereum leverage smart contracts to automate policy enforcement and achieve throughput gains of up to 42 percent with transaction latencies near 39 milliseconds. By distributing trust and enabling verifiable audit trails, these models enhance data integrity, accountability, and compliance. This survey consolidates and analyzes current research in both conventional and blockchain based access control for cloud and IoT ecosystems, identifying performance tradeoffs, regulatory considerations, and future research directions toward secure, transparent, and scalable access management.
Marwa Ali Hamdan AL-Jabri, Nafisa Abul Ghafoor Othman AL-Ansari
Access control is an important part of cybersecurity in distributed systems since conventional centralized mechanisms are not always sufficient. Due to blockchain, individuals have begun to employ decentralized access control models as they are capable of enhancing transparency, auditing and defending against fraud. At the reason of this report, we survey various blockchain-based access control systems, paying special attention to their architectures, confirmation mechanisms, identity models and policy enforcement mechanisms. We categorize the current literature into various groups based on their platforms (e.g. Ethereum, Hyperledger, Fabric), control mechanisms (e.g. RBAC, ABAC and capability-based) and whether they introduce additional privacy-tools such as zero-knowledge proofs and decentralized identifiers. The paper analyzes and describes the key gaps in current frameworks in terms of scalability, interoperability and computing expenses. Then, the shortcomings of the current research are pointed out so that they could guide future efforts in the field of blockchain-based access control systems.
We present the Mazari Bidirectional Architecture, a cryptographic framework providing end-to-end privacy guarantees for computation systems employing homomorphic encryption (HE), differential privacy (DP), and zero-knowledge proofs (ZK). The architecture comprises two complementary orderings: Y.I.N. Mazari Ordering (DP→ZK→HE) for secure data submission and Y.A.N.G. Mazari Ordering (VERIFY→DISAGGREGATE→DECRYPT→DENOISE) for secure result retrieval. Through exhaustive permutation analysis, we prove that among all possible orderings for each direction, exactly one ordering in each direction is secure—and these orderings are mathematical duals. The Y.I.N. ordering prevents information leakage during data submission, while the Y.A.N.G. ordering prevents timing side-channel attacks during result retrieval. This paper provides comprehensive coverage of all implementation variations, security proofs, and robustness analysis to establish technical foundations for privacy-preserving computation research.
The fast digitalization of contemporary society has changed the data into a valuable resource, and it has been the key to the innovation in the financial sector, healthcare, politics, and industries, and it has also increased risks both in terms of misusing it, stealing it, and using it. Information security through maintaining confidentiality, integrity and availability of information has thus become a pre-requisite to trust in digital infrastructures. The present paper gives a detailed discussion of how cryptography, cybersecurity, and data privacy come into convergence and have a central role to play in protecting the digital ecosystems. Basic cryptographic primitives such as symmetric and asymmetric encryption, hash functions as well as digital signatures are discussed as the foundation of secure communication. With these, more complex privacy-sensitive technology like homomorphic encryption, zero-knowledge proofs, and differential privacy is discussed as technology that could offer the opportunity to perform safe computation and share data without jeopardizing the privacy of individuals.The paper also explores the disruptive potential of quantum computing, specifically how it can render the popular public-key systems insecure by figuring out ways to break them, e.g. the Shor algorithm, and assesses the new paradigm of post-quantum cryptography as a reaction to this existential risk. The examples are discussed within various fields such as secure communication schemes, data-at-rest security, cloud computing, and the Internet of things (IoT), e.g., in which cryptographic efficiency and versatility are most crucial. It is a synthesis of these factors that the paper highlights that cryptography is not only a technical protection but it is a cornerstone enabling resiliency, trust, and privacy-by-design in the digital era. This paper then ends with a discussion on the challenges that still need to be tackled, including scalability, usability and compliance with regulations, and how future research will be needed to define the future of secure and privacy-preserving technologies in the increasingly interconnected world.
Fully Homomorphic Encryption (FHE) enables computation on encrypted data with end-to-end confidentiality; however, its practical adoption remains limited by substantial computational costs...
To address centralized trust risks, inadequate privacy protection, and quantum vulnerability of traditional crossdomain authentication systems, this paper proposes a quantumresistant self-sovereign identity (SSI) scheme based on lattice cryptography. Centered on Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), it constructs a decentralized ecosystem with two key innovations: a “single trapdoor - multi-attribute public key” structure (reducing storage and simplifying key management) and a lattice-based linkable ring signature (balancing anonymity and traceability). Implemented via TrapGen, SamplePre, and rejection sampling, the scheme's security relies on the Short Integer Solution (SIS) problem, with unconditional anonymity and unforgeability proven in the random oracle model. Efficiency comparisons confirm advantages in signature/verification time and storage overhead. This work provides a secure, privacy-preserving post-quantum solution for crossdomain collaboration in smart cities and supply chains. Future work will focus on lattice optimization and zero-knowledge proof integration.
Elif Nur Kucur, Tolga Büyüktanır, Muharrem Ugurelli, Kazım Yıldız
Privacy-preserving machine learning (PPML) constitutes a core element of responsible AI by supporting model training and inference without exposing sensitive information. This survey presents a comprehensive examination of the major cryptographic PPML techniques and introduces a unified taxonomy covering technical models, verification criteria, and evaluation dimensions. The study consolidates findings from both survey and experimental works using structured comparison tables and emphasizes that recent research increasingly adopts hybrid and verifiable PPML designs. In addition, we map PPML applications across domains such as healthcare, finance, Internet of Things (IoT), and edge systems, indicating that cryptographic approaches are progressively transitioning from theoretical constructs to deployable solutions. Finally, the survey outlines emerging trends—including the growth of zero-knowledge proofs (ZKPs)-based verification and domain-specific hybrid architectures—and identifies practical considerations that shape PPML adoption in real systems.
Aso Mohammad Darwesh, Atefeh Nekouie, Mohammad Hossein Moattar, Parisa Khoshvaght · 7 authors
Abstract Electronic Health Record (EHR) management is one of the challenging problems in digital healthcare and is related to several issues such as data security, privacy, scalability, interoperability, and ownership which are very crucial for reliable exchange of information. This review discusses the recent trend and technological solutions for the mentioned challenges. These solutions mainly focus on cloud-based infrastructures, attribute-based encryption (ABE), blockchain frameworks, and Non-Fungible Token (NFT)-based data ownership. This study highlights the strengths and limitations of each approach using comparative analysis and evaluations. Also, this review introduces a conceptual integration framework that combines graph neural networks (GNNs), multi-reference attribute-based encryption (MA-ABE), blockchain, and NFTs. The proposed model integrates predictive artificial intelligence, decentralized mechanism, immutable auditing, and verifiable ownership in a multi-layered architecture to address the issues and challenges of HER systems. Quantitative analysis of the reviewed literature reveals a clear upward trend in research activity, with more than 80 peer-reviewed studies published between 2017 and 2024, representing an approximate 250% growth in blockchain-, ABE-, and NFT-based EHR solutions. Among these, 41% focus on security and privacy, 27% on scalability, and 19% on interoperability, underscoring the field’s growing emphasis on decentralized and intelligent healthcare systems. This article not only contributes to a comprehensive review of the previous researches, but also provides a perspective on how the future of healthcare systems will be reshaped by intelligent and decentralized technologies.
Conventional educational accreditation systems face significant challenges, including issues of data integrity, procedural inefficiencies, and insufficient privacy protection. This study introduces a lifelong learning accreditation framework based on a Decentralized Autonomous Organization (DAO). Our approach leverages blockchain technology and smart contracts to create a decentralized and immutable credentialing infrastructure. Our work addresses critical vulnerabilities such as single-point-of-failure trust risks, inefficiencies in manual verification, and data privacy breaches. To counter these issues, we propose three key innovations: A hybrid IPFS-blockchain architecture for efficient and permanent data storage. A threshold signature scheme to enable multi-party governance and prevent centralized control. An NFT-based protocol for the automated issuance of credentials. The proposed framework provides a practical solution for enhancing transparency and security in lifelong learning. Future work will focus on improving the efficiency of the cryptographic mechanisms and enabling cross-chain interoperability.
Khang Wen Goh, Burhan Ul Islam Khan, Abdul Raouf Khan, Dwi Sudarno Putra · 6 authors
Blockchain systems built on classical cryptography face immediate risks from large-scale quantum computers, while purely quantum-based blockchains often rely on a single Private Key Generator (PKG) and incur heavy resource overheads. To overcome these issues, this paper proposes a hybrid quantum and post-quantum blockchain approach that removes single points of trust by using Distributed Key Generation and a dual-layer signature mechanism. This method integrates quantum digital signatures, rooted in the Fully Flipped Permutation problem, with classical post-quantum (lattice-based) cryptography, enabling users to switch between quantum and classical signatures according to security requirements and channel conditions. Delegated Proof-of-Stake with node behavior and Borda count has been incorporated to manage consensus, ensuring that witness nodes are regularly re-elected and malicious actors are penalized by distributing secret shares among multiple rotating witnesses. We eliminate the central vulnerability of a sole PKG while maintaining rigorous resistance to collusions. Our analytical model indicates that a fraction of transactions can use quantum signatures without system-wide bottlenecks, while the remaining transactions follow classical PQC paths with throughput approaching classical baselines under our modeling assumptions. Consequently, this hybrid method offers higher scalability, robust collusion resistance, and long-term security even under quantum-capable adversaries. This paper presents extensive theoretical analyses, probability models, and algorithmic complexities, demonstrating that our design provides resilient infrastructure that meets the key performance and security requirements of next-generation blockchain systems.
Abstract In the realm of blockchains, synchronization challenges are two-folded. First, smart contracts from different blockchains cannot communicate with each other, making it hard to establish a trustworthy communication channel to share and maintain a universal state between each other. Second, transactions on different blockchains can hardly be ordered. Hence interference is expected. We need a novel way to handle interference. Traditional solutions involving third parties have safety and liveness issues and thus compromise between safety, permissionless, and liveness. ZK Multi-Blockchain Aggregatoris a multi-blockchain execution layer that leverages the power of zero-knowledge proof to minimize the trust base of multi-blockchain communication, which does not compromise safety, liveness, permissionless, and atomicity. In contrast to traditional blockchain bridges performing transactions on different blockchains separately and using a relay system to enforce the order of transactions and prevent interference, our method uses an entirely new approach, such that for each multi-blockchain transaction, it simulates the multi-blockchain transaction in its aggregator chain. Our aggregator uses zero-knowledge proofs of the simulation to convince involved blockchains to update their local state accordingly. On top of this layer, rich applications over multi-blockchains can run safely and efficiently.
The article systematizes modern methods of zero-knowledge proof (ZKP). Classification features are considered: protocol interactivity, algebraic or stochastic basis, need for trusted setup, type of zero-knowledge, and proof model. Classical schemes (Fiat–Shamir, Schnorr, Blum), modern zk-SNARK and zk-STARK, as well as novel approaches – PLONK, Halo 2, Bulletproofs, lattice-based ZKPs, and machine learning proofs are described. A comparative analysis is conducted according to efficiency, proof size, generation and verification complexity. It is shown that SNARKs provide compactness but require a trusted setup, while STARKs are transparent and post-quantum secure but large. Open problems are highlighted: recursive proofs, standardization, metadata protection, and applications in machine learning. It is concluded that further research in this field is aimed at creating scalable, secure, and quantum-resistant protocols for digital technologies.
Blockchain technology is a game-changing invention that guarantees digital transactions on decentralized networks. The vital role that cryptography plays in guaranteeing the authenticity, confidentiality, and integrity of blockchains is examined in this paper. To secure the data on the blockchain and validate transactions, we are examining fundamental cryptographic techniques like hashing, symmetric and asymmetric encryption, and digital signatures. Furthermore, advanced cryptographic solutions that have the potential to improve privacy and scalability—such as homomorphic encryption, zero-knowledge proofs, and zk-SNARKs—are being discussed. Along with reviewing consensus techniques like proof of work and proof of stake, the paper contrasts the main blockchains, including those that are still in development, like Ethereum, Solana, and Hyperledger Fabric. Through an analysis of the advantages and disadvantages of existing cryptographic implementations, the study emphasizes the necessity for additional innovation.
The article systematizes modern methods of zero-knowledge proof (ZKP). Classification features are considered: protocol interactivity, algebraic or stochastic basis, need for trusted setup, type of zero-knowledge, and proof model. Classical schemes (Fiat–Shamir, Schnorr, Blum), modern zk-SNARK and zk-STARK, as well as novel approaches – PLONK, Halo 2, Bulletproofs, lattice-based ZKPs, and machine learning proofs are described. A comparative analysis is conducted according to efficiency, proof size, generation and verification complexity. It is shown that SNARKs provide compactness but require a trusted setup, while STARKs are transparent and post-quantum secure but large. Open problems are highlighted: recursive proofs, standardization, metadata protection, and applications in machine learning. It is concluded that further research in this field is aimed at creating scalable, secure, and quantum-resistant protocols for digital technologies.
Qaisar Manzoor, Ch Anwar Ul Hassan, Ali Daud, Azhar Imran
In order to effectively follow up with a patient, it is essential to have a health record. The opinions, prescriptions, research, and any other data connected to the patient that are provided by medical professionals are included in this document. An individual or individuals, such as the patient, the physician, and the chemist, are taking part in the process of exchanging and managing this file. Those individuals who are authorized to do so are able to view the electronic health record (EHR) from any location, and the information contained inside the EHR is distributed across various health care providers. Under some conditions, such as those pertaining to privacy and security, the electronic health record (EHR) must be shared. On the other hand, the existing health care systems may be susceptible to system failures and hacking, which makes it difficult to deliver services that can be relied upon. Additionally, the characteristics of such systems make it difficult to exercise centralized control over admission requirements. The findings of this study propose a strategy that Ethereum may implement to promote the trading of EHR models. Ethereum allows for the addition of EHR partners to the route, which makes it simpler for individuals to communicate data with one another. Users are given the ability to decide how data can be accessed using attribute-based access control (ABAC), which may result in the system becoming more secure. It is possible to view any record that has been preserved on the blockchain by utilizing the Ethereum Fabric feature; however, the record cannot be altered or removed. This ensures that the data can be traced back to the specific source from which it originated. By utilizing proxy re encryption, which guarantees that data will not be disclosed while it is being shared, it is possible to guarantee the safety of the data.
Zero-knowledge proof (ZKP) is a cryptographic protocol that allows a prover to convince verifiers that a computation is correctly executed without disclosing the prover’s secret. ZKP has been deployed in various privacy-preserving applications. However, the proof generation is notably inefficient on general-purpose processors. Multi-scalar multiplication (MSM) and polynomial computation (POLY), including number theoretic transform (NTT), are two of the most computation-intensive parts in proof generation. Recently, separate accelerators for MSM and POLY (mostly NTT) have been proposed. Unfortunately, separate accelerators may have poor resource utilization since MSM and POLY cannot be performed concurrently. To address this challenge, we propose Exa, a unified hardware architecture for MSM and POLY. It enables MSM and POLY to share computational resources and memory resources through decoupling dataflow control, computation, and memory. We design a novel unified functional unit (FU) array that can support both POLY operation and point addition (PADD) for MSM. In addition, we propose a 3-D NTT implementation and an adaptive MSM implementation on the FU array using a domain-specific instruction set architecture (ISA). Exa is scalable and can be efficiently orchestrated by our proposed runtime system. Compared with the separate accelerators for MSM and NTT, Exa occupies 47% less chip area. Compared to state-of-the-art accelerator PipeZK, Exa achieves up to$20.68 \times $and$4.58 \times $improvement for NTT and MSM, respectively, while occupying a chip area that is$2.6 \times $smaller. For end-to-end applications, Exa can achieve a speedup of$6.5 \times $on average than software implementation.
In this paper we present BlockMedLedger, a decentralized patient health record management system based on blockchain and IPFS. BlockMedLedger provides solutions to the challenges of healthcare data silos, security vulnerabilities and patient ownership of their own data. The patient centric model supports patients, medical data owners, to have complete control over their own medical data, while providing an efficient process to facilitate secure sharing of the medical data with care providers initiated through smart contracts and cryptographic access controls. The system uses an Ethereum compatible blockchain to support access control decision and IPFS for decentralized encrypted storage of encrypted medical records. The implementation demonstrates good security, efficient access, retrieval and sharing of encrypted health information for health care providers and patients while meeting requirements specified in HIPAA utilizing zero-knowledge proofs and patient consent control features.
Online harassment, incitement to violence, racist behavior, and other harmful content on social media can damage social harmony and even break the law. Traditional blocklisting technologies can block malicious users, but this comes at the expense of identity privacy. The anonymous blocklisting has emerged as an effective mechanism to restrict the abuse of freedom of speech while protecting user identity privacy. However, the state-of-the-art anonymous blocklisting schemes suffer from either poor dynamism or low efficiency. In this paper, we propose $\mathsf{ShadowBlock}$, an efficient dynamic anonymous blocklisting scheme. Specifically, we utilize the pseudorandom function and cryptographic accumulator to construct the public blocklisting, enabling users to prove they are not on the blocklisting in an anonymous manner. To improve verification efficiency, we design an aggregation zero-knowledge proof mechanism that converts multiple verification operations into a single one. In addition, we leverage the accumulator's property to achieve efficient updates of the blocklisting, i.e., the original proof can be reused with minimal updates rather than regenerating the entire proof. Experiments show that $\mathsf{ShadowBlock}$ has better dynamics and efficiency than the existing schemes. Finally, the discussion on applications indicates that $\mathsf{ShadowBlock}$ also holds significant value and has broad prospects in emerging fields such as cross-chain identity management.
Nadia van Niekerk, Brink van der Merwe, Louwrens Labuschagne
In the rapidly evolving realm of blockchain technology, the pursuit of enhanced privacy, security, and scalability has propelled the exploration of cryptographic innovations. Zero-Knowledge Proofs (ZKPs) have emerged as a pivotal solution, addressing diverse challenges across decentralized applications and cryptographic systems. However, the intricate mathematical foundations of ZKPs can pose a barrier to widespread adoption. To bridge this gap, a spectrum of ZKP tools has been developed, abstracting mathematical complexities and enabling developers with varying levels of expertise to incorporate ZKPs into their projects. The exploration of the 5 W’s – Who, What, When, Where, and Why – guides developers in selecting ZKP tools aligned with their specific needs and understanding. This paper serves as a vital resource for developers entering the dynamic landscape of ZKP development. By answering crucial questions and providing nuanced insights into ZKP tools, it empowers developers to navigate this intricate domain effectively. As ZKP technology continues to evolve, our findings contribute to the ongoing dialogue surrounding its implementation, utilization and the ever-adapting toolkit shaping the future of cryptographic innovation. This paper employs a Mining Software Repositories (MSR) approach to unravel insights from the expansive landscape of ZKP development. By delving into GitHub repositories, we categorize author archetypes, discuss ZKP proof constructions, identify phases of tool development, explore the level of understanding required and examine the correlation between tool types and application purposes. Through a metrics-driven analysis, we unveil patterns in tool popularity, development trends, and historical perspectives, offering a comprehensive understanding of the ZKP tooling ecosystem.
Blockchain deployments continue to face challenges related to scalability, energy consumption, and susceptibility of classical cryptographic primitives to emerging quantum attacks. Conventional systems employing RSA or DSA signatures and consensus mechanisms such as Proof of Work (PoW) or Proof of Stake (PoS) incur substantial computational overhead and are not well suited for cloud-scale execution. This study presents PQ-PoETChain, a post-quantum-secure blockchain model integrating NTRU-based signatures, an adaptive Proof of Elapsed Time (PoET) protocol executed within Trusted Execution Environments (TEEs), and a Lightweight Hash Validation (LHV) mechanism. The framework was implemented in Python and evaluated in a controlled simulation environment using 50-1000 nodes, with repeated trials to measure variability across throughput, latency, and energy metrics. NTRU demonstrated sub-2 ms signature operations, while the adaptive PoET configuration reduced consensus delay under load-dependent conditions. Across multiple experimental runs, the system achieved an average throughput of ~ 195 TPS with a latency of 189 ± 4 ms at 500 nodes. Energy consumption reduced by up to 91.8% (± 1.6%) when compared with PoW under identical conditions. LHV further lowered verification cost by replacing Merkle-tree traversal with constant-time hash-pointer validation. Results indicate that PQ-PoETChain offers a balanced combination of quantum-resilient security and improved performance characteristics suitable for cloud-native and large-scale deployments.
As the healthcare systems become more digital, a problem of data security, patient information safety, and the methods of guaranteeing that the information is available to everyone has come to the fore. Role-Based Access Control (RBAC) and other crude mechanisms of determining who is allowed to access what data are limited in preventing breaches and unlawful manipulation of data. To address these issues, this paper will propose the use of blockchain-based technology to develop a smart contract architecture that would enhance the process of managing healthcare data in a more transparent and secure way. The solution offered is based on the programmable smart contracts and the blockchain technology that cannot be altered and is decentralized to ensure that audits can be performed, data integrity is ensured, and access control is configured. According to simulated deployment studies, the proposed plan is much better than the current designs in the deterrence of unauthorized access, reduction of data modification and reducing the cost of operation.
In decentralized finance (DeFi), accidental cryptocurrency transfers to incorrect wallet addresses are a large usability and security issue, frequently causing permanent loss of funds. We present CryptoSafeSend, a smart contract-based safety protocol for transactions featuring a cryptographically secure passcode verification scheme supporting conditional transfers. This work addresses higher-level security issues by introducing a PBKDF2-based key derivation function, which generates strong encryption keys based on Firebase’s Firebase UID. Secret passcodes are encrypted in AES-GCM functions deployed underneath the Web Crypto API, and Initialization Vector and ciphertext are Base64 encoded for off-chain reliable storage and Firebase Firestore-based messaging. The protocol prevents unauthorized exploitation by safely binding off-chain passcode transmission to a matching on-chain verification, reinforcing user trust without undermining decentralization. Testing on an Ethereum testnet confirms negligible gas overhead, immunity against double claims, and strong security guarantees, qualifying CryptoSafeSend as a valuable constituent in next-generation secure digital asset protocols.
As the world transitions toward digital-first governance and civic participation, ensuring the security and integrity of voting systems has become a critical concern. Traditional evoting mechanisms, although convenient, suffer from a range of vulnerabilities - including voter impersonation, double voting, identity leaks, and tampering by insiders or external adversaries. ECC-EXONUM-eVOTING was previously proposed to mitigate many of these issues through elliptic curve cryptography (ECC), Zero-Knowledge Proofs (ZKP), and Exonum private blockchain. In this paper, we extend the capabilities of ECC-EXONUMeVOTING by integrating two novel modules aimed at enhancing both system intelligence and accessibility. First, we implement an AI-based fraud detection system using unsupervised anomaly detection techniques that proactively identify and block fraudulent voting behaviors in real time. Second, we introduce a secure offline voting architecture designed for voters in remote or lowconnectivity regions, using QR-based tokenization and Merkle-root-based integrity proofs for delayed blockchain synchronization. Through simulations, algorithmic validation, and comparative analysis, we demonstrate how these enhancements significantly increase the robustness, scalability, and real-world applicability of blockchain-based voting systems.