ZKVault is a privacy-preserving decentralized KYC system aimed at eliminating redundant identity verification and reducing the risks associated with centralized data storage. The project leverages zero-knowledge proofs and blockchain technology to enable users to prove specific identity attributes without exposing sensitive personal information. It ensures secure, tamper-proof, and reusable verification across multiple platforms while maintaining user privacy and regulatory compliance. Experimental results demonstrate efficient performance, with proof generation taking approximately 1.8 seconds and verification under 50 milliseconds, making ZKVault a scalable and practical alternative to traditional KYC systems.
In the modern digital landscape, traditional cen- tralized storage models are increasingly vulnerable to security breaches, suffer from single points of failure, incur high main- tenance costs, and present scalability limitations. The Decen- tralized Storage System (DSS) is proposed as an alternative solution, utilizing distributed ledger technologies, peer-to-peer (P2P) networks, and advanced cryptographic mechanisms to establish a fault-tolerant, secure, and highly available data storage infrastructure. This paper presents the design and imple- mentation of a decentralized storage framework that integrates key blockchain concepts—such as immutability, transparency, and consensus validation—to enhance data integrity and security. The system enables users to store, retrieve, and share data in a fully decentralized manner while ensuring confidentiality through encryption. The work includes a comprehensive architectural and functional analysis of a full-stack, decentralized file storage platform built specifically on the Filecoin Protocol, leveraging the InterPlanetary File System (IPFS) for distributed content addressing and efficient data retrieval. The platform employs a hybrid architecture combining Web2 technologies—Next.js for the frontend, Node.js/Express for the backend, and MongoDB for centralized metadata management—with core Web3 protocols. The analysis confirms the project's success in creating a practical, non-custodial storage solution that abstracts the complexities of the decentralized web. However, a key architectural trade-off is identified: the system's reliance on provider-centric tooling (Boost CLI) and third-party Remote Procedure Call (RPC) endpoints (Glif API) simplifies development but introduces dependencies that compromise the ideal of full, end-to-end decentralization.
Nuha Omran Abokhdair, Ali Alissawi Ahmed AlQudairi
Decentralized storage networks increasingly rely on blockchain-based verification to ensure data integrity without centralized control; however, proof-intensive workloads introduce significant latency and on-chain cost overhead. This paper presents a lifecycle-based comparative analysis of major zero-knowledge proof (ZKP) models used in decentralized storage, focusing on zk-SNARK frameworks and transparent zk-STARK constructions. A multi-layer evaluation framework is introduced, aligning performance analysis with the core stages of the proof lifecycle: generation, aggregation, and on-chain verification. Building on this analysis, the paper proposes a hybrid architecture that combines parallel STARK-based proof generation with recursive SNARK-based compression, reducing on-chain verification complexity to near-constant. A Filecoin-inspired case study, supported by a quasi-empirical performance model, demonstrates that the proposed hybrid approach significantly reduces verification latency and data overhead while mitigating the linear growth of verification costs. The results indicate that hybrid ZKP architectures offer a scalable and economically viable solution for decentralized storage systems and large-scale blockchain networks. Keywords: Zero-knowledge proofs, zk-SNARKs, zk-STARKs, recursive aggregation, decentralized storage, verifiable cryptography, scalability, gas cost.
This article examines the integration of blockchain, distributed file system, and virtualization technologies (including Virtual SAN, VSAN) to improve data storage privacy and efficiency. The limitations of traditional centralized storage models are presented, such as vulnerability to tampering, limited flexibility in access control, difficulty in auditing, and low resource efficiency. A concept for an integrated data storage system based on blockchain smart contracts is proposed. This system incorporates data encryption, implementation of an access control strategy based on blockchain attributes, the use of virtualization optimized through VSAN, distributed key management, and privacy-enhancing technologies (zero-knowledge proof, trusted computing environment). The proposed architecture provides flexible access control, efficient data processing, and a high level of security in a public or private blockchain environment.
H. P. Yu, Yinglong Gao, Shen Su, Zhen Yang · 6 authors
Decentralized storage auditing approaches are designed to ensure data security in dishonest decentralized storage providers. However, the need for data updates introduces new challenges to the design of decentralized storage auditing approaches. Existing approaches can support dynamic auditing for updated files. Unfortunately, they can only deal with block-level updating, which is counter-intuitive and requires conversion from semantic changes to binary changes. Furthermore, existing dynamic auditing approaches require the recalculation of auxiliary auditing information (e.g., auditing authenticators) in data owners, which imposes unnecessary additional burdens on data owners, particularly those with constrained resources in decentralized storage environments. In this paper, we focus on image files and propose iAudit, an efficient pixel-level dynamic image auditing approach in decentralized storage. We first design a novel image authenticator with image pixels for efficient dynamic auditing, which combines convolution operations and polynomial commitment in authenticator construction. Additionally, we build an owner-free dynamic mechanism in dynamic decentralized storage auditing approach by utilizing zero-knowledge proof techniques. In this way, the dynamic operation overheads incurred by auditing can be completely eliminated from the data owners. A prototype of iAudit is implemented, and extensive experimental results demonstrate that iAudit outperforms state-of-the-art works, achieving over a 210× speedup for data owner in dynamic update phase.
Advanced Data Storage Technologies
Cloud Data Security Solutions
Advanced Steganography and Watermarking Techniques
Niccolò Scatena, Pericle Perazzo, Giovanni Nardini
This paper proposes iblock, a comprehensive C++ library for Bitcoin simulation, designed for OMNeT++. iblock offers superior efficiency and scalability with respect to state-of-the-art simulators, which are typically written in high-level languages. Moreover, the possible integration with other OMNeT++ libraries allows highly detailed simulations. We measure iblock's performance against a state-of-the-art blockchain simulator, proving that it is more efficient at the same level of simulation detail. We also validate iblock by using it to simulate different scenarios such as the normal Bitcoin operation and the selfish mine attack, showing that simulation results are coherent with theoretical expectations.
International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Open access
Advanced Data Storage Technologies
Security and Verification in Computing
Physical Unclonable Functions (PUFs) and Hardware Security
Decentralized file systems (DFS) offer secure and transparent and resilient data storage through the integration of peer-to-peer storage protocols and blockchain technologies. Such systems are, nevertheless, vulnerable to a range of threats to security at an application, smart-contract, or network level. We present a profound discussion of the weaknesses of a DFS developed based on IPFS as a file-storing engine, Ethereum as metadata storage, and MetaMask as authentication in this paper. With a combination of tools of superior quality in security-related analyses, like Slither, MythX, and Metasploit, we model attack-related situations in the form of reentrancy, content poisoning, and Sybil, as well as phishing. The evidence highlights the main threats, with chief ones being contract-logic defects, file-integrity breaks and session socialists. We suggest the relevant countermeasures, including the best practices in smart-contract writing, cryptographic assurance of content identifiers (CIDs), strong session management, and defences against nodes. The findings provide a security benchmark to system developers and researchers keen on enhancing the robustness of decentralized systems of storage.
The proliferation of Non-Fungible Tokens (NFTs) has revolutionized digital asset ownership and trading, creating unprecedented opportunities for creators and collectors. However, existing NFT marketplaces face significant challenges, including limited user discovery mechanisms, inadequate recommendation systems, security vulnerabilities, and poor user experience design. This paper presents a new way to run an NFT marketplace using Blockchain and Artificial Intelligence. The system keeps everything secure by storing asset information on a distributed online ledger. With built-in AI, it helps users find content they'll like by giving personalized suggestions. It also uses multiple authentication steps to make sure the marketplace stays safe for everyone. The design uses decentralized storage through the InterPlanetary File System (IPFS). It employs smart contract automation for transaction processing and incorporates machine learning algorithms for fraud detection and user behavior analysis. We demonstrate the effectiveness of our approach with implementation results that show improved user engagement, reduced transaction costs, and better security compared to traditional NFT platforms. The system achieves a 47% improvement in user retention and a 63% increase in successful transactions through personalized recommendations. This research contributes to the growing field of blockchain-based digital asset management and provides a scalable framework for next-generation NFT marketplaces.
Cloud storage uses proofs of ownership to avoid redundant uploads while keeping file contents secret. Many existing schemes need extra round trips, or rely on predictable sampling. These choices reduce security when an adversary knows part of the file. We present MiS-PoW, a zero knowledge and non-interactive proof of ownership. The protocol derives a synchronized challenge seed from the existing HTTPS/TLS session. The seed binds a discretized time window and the file identifier. Both parties compute the same challenges locally, and the protocol adds no new messages. MiS-PoW samples blocks with a stratified policy without duplicates. The policy enforces coverage across partitions and reduces the advantage of contiguous knowledge and near duplicate files. The proof layer uses STARKs with simple AIR constraints. The constraints check that indices come from the seed, lie in range, are unique, and meet per partition counts. We analyze security and show seed unpredictability, resistance to replay, and bounds under partial knowledge with limited grinding. A prototype shows that verification time does not grow with file size, and proof and bandwidth costs remain modest. MiS-PoW is deployable, privacy preserving, and scalable for cloud storage.
S K Sharif, C H Saritha, P. Senthil, Madhavi Pingili · 6 authors
Every business operation worldwide adopts cloud storage solutions since cybersecurity now demands mandatory protection for data security together with integrity management while also ensuring data confidentiality. Cloud storage systems that run from one central platform remain exposed to cyberattacks that lead to two risks: system malfunctions and unapproved system access. This research delivers an unalterable data management system through the application of blockchain-based methods to distributed cloud architectures. Through the combination of smart contracts with distributed ledger technology (DLT) and cryptographic hashing capabilities in blockchain technology data protection and data integrity get enhanced in cloud systems. Research teams develop hybrid blockchain systems by combining several systems using external storage methods to solve scalability issues. Through shading technology integration with hybrid blockchain systems and off-chain storage systems fast transaction execution becomes possible. The setup of distributed control centers employing blockchain technology secures data better because it extends traditional systems by creating comprehensive visibility that detects unauthorized access attempts. Researchers have investigated how blockchain-enabled cloud storage applications protect digital data in this study.
This paper presents a decentralized authorization framework that employs non-transferable Non-Fungible Tokens (NFTs), also known as soul-bound tokens (SBTs), to deliver tamper-resistant, identity-bound access control. Access rights are permanently linked to a user's blockchain wallet and can be upgraded via metadata updates without reminting, enabling dynamic tier management while preventing resale or delegation. The architecture combines an ERC-721 smart contract backend with a decentralized front-end interface for wallet-based authentication and administrator-controlled content distribution. Implementation on the Binance Smart Chain test network demonstrates secure and cost-effective access management with tiered content control. An experimental evaluation quantifies the gas costs associated with NFT minting, tier upgrades, and InterPlanetary File System (IPFS) metadata storage. Results show that using the native Base32 encoding of IPFS content identifiers reduces storage gas costs by approximately 6% compared to the previously standard Bitcoin-style Base58 encoding. Furthermore, shorter uniform resource identifiers (URIs) avoid costly expansions of the storage slots of the Ethereum Virtual Machine (EVM), which can increase transaction costs by 20,000 gas per slot. These findings provide practical guidelines for designing scalable and cost-effective NFT-based authorization systems. Source code and implementation details are available on GitHub.
To address the limitations of blockchain data storage capacity and uneven dis-tribution, this paper proposes a Chord dual-ring distributed storage method based on virtual nodes. Building upon the original Chord protocol, this approach introduces virtual rings to construct a “storage ring-virtual ring” dual-ring structure. Target virtual nodes are located through routing table lookups, and data is distributed across the storage ring via a name mapping mechanism. Sim-ulation experiments validate the proposed scheme's effectiveness by evalu-ating load balancing and query success rate across varying sharding granulari-ties. Results demonstrate that this approach not only efficiently achieves shard-ed storage for blockchain data but also ensures balanced distribution of block data.
Rini Hardiyanti, Amil Ahmad Ilham, Ady Wahyudi Paundu
This research proposes the use of AES-256-CBC encryption, decentralized storage using Interplanetary File System (IPFS), and CID hash logging into the Ethereum. The system was tested using files of 5, 10, 15 and 100 MB, and shows that the encryption-decryption process has no significant impact on system performance. The security evaluation resulted 6 out of 7 test scenarios successfully prevented data theft, manipulation, and duplication after using attack simulations such as reply attacks, bit-flipping, Man-in-the-Middle (MITM), and Brute Force attacks. The total cost for logging CID hashes to Ethereum was $0.00913-0.01080$ ETH. Although throughput performance and execution time are volatile in both proposed and comparison system, the proposed system is superior in terms of system security and cost efficiency, making it feasible to use for e-learning content protection.
Yanjing Ren, Jia Zhao, Jingwei Li, Patrick P. C. Lee
Blockchains have revolutionized trust and transparency in distributed systems, yet their heavy reliance on key-value (KV) storage for managing immutable, rapidly growing data leads to performance bottlenecks due to I/O inefficiencies. In this paper, we analyze Ethereum’s storage workload traces, with billions of KV operations, across four dimensions: storage overhead, KV operation distributions, read correlations, and update correlations. Our study reveals 11 key findings and provides suggestions on the design and optimization of blockchain storage.
The InterPlanetary File System (IPFS) has been successfully established as the de facto standard for decentralized data storage in the emerging Web3. Despite its decentralized nature, IPFS nodes, as well as IPFS content providers, have converged to centralization in large public clouds. Centralization introduces BGP routing-based attacks, such as passive interception and BGP hijacking, as potential threats. Although this attack vector has been investigated for many other Web3 protocols, such as Bitcoin and Ethereum, to the best of our knowledge, it has not been analyzed for the IPFS network. In our work, we bridge this gap and demonstrate that BGP routing attacks can be effectively leveraged to censor content in IPFS. For the analysis, we collected 3,000 content blocks called CIDs and conducted a simulation of BGP hijacking and passive interception against them. We find that a single malicious AS can censor 75% of the IPFS content for more than 57% of all requester nodes. Furthermore, we show that even with a small set of only 62 hijacked prefixes, 70% of the full attack effectiveness can already be reached. We further propose and validate countermeasures based on global collaborative content replication among all nodes in the IPFS network, together with additional robust backup content provider nodes that are well-hardened against BGP hijacking. We hope this work raises awareness about the threat BGP routing-based attacks pose to IPFS and triggers further efforts to harden the live IPFS network against them.
Hao Cheng, Georgios Fotiadis, Johann Großschädl, Daniel Page
Non-degenerate bilinear maps on elliptic curves, commonly referred to as pairings, have many applications including short signature schemes, zero-knowledge proofs and remote attestation protocols. Computing a state-of-the-art pairing at the 128-bit security level, such as the optimal ate pairing over the curve BLS12-381, is very costly due to the high complexity of some of its sub-operations: most notable are the Miller loop and final exponentiation. In the past ten years, a few optimized pairing implementations have been introduced in the literature, but none of those took advantage of the vector (SIMD) extensions of state-of-the-art Intel and AMD CPUs, especially AVX-512; this is surprising, because doing so offers the potential to reach significant speed-ups. Consequently, the questions of 1) how computation of the optimal ate pairing can be effectively vectorized, and 2) what execution time such a vectorized implementation can achieve are still open. This paper addresses said questions by introducing a carefully-optimized AVX-512 implementation of the optimal ate pairing on BLS12-381. A central feature of the implementation is the use of 8-way Integer Fused Multiply-Add (IFMA) instructions, which are capable to execute eight 52 x 52-bit multiplications in a SIMD-parallel fashion. We introduce new vectorization strategies and describe optimizations of existing ones to speed up arithmetic operations in the extension fields Fp4 , Fp6 , and Fp12 as well as certain higher-level functions. Furthermore, we discuss some parallelization bottlenecks and how they impact execution time. We benchmarked our pairing software, which we call avxbls, on an Intel Core i3-1005G1 (“Ice Lake”) CPU and found that it needs 1, 265, 314 clock cycles (resp. 1, 195, 236 clock cycles) for the full pairing, with the Granger-Scott cyclotomic squaring (resp. compressed cyclotomic squaring) being used in the final exponentiation. For comparison, the non-vectorized (i.e., scalar) x64 assembly implementation from the widely-used blst library has an execution time of 2, 351, 615 cycles, which is 1.86 times (resp. 1.97 times) slower. avxbls also outperforms Longa’s implementation (CHES 2023) by almost the same factor. The practical importance of these results is amplified by Intel’s recent announcement to support AVX10, which includes IFMA instructions, in all future CPUs.
В статье рассматриваются основы технологии нулевых доказательств знания (Zero-Knowledge Proofs, ZK), её значение для развития криптовалютных систем и децентрализованных финансов. Особое внимание уделено механизмам zk-SNARK и zk-STARK, а также их практическому применению в проектах Zcash, Ethereum, Polygon и zkSync. Проведен анализ проблем масштабируемости, вычислительной сложности и регуляторных рисков, связанных с использованием ZK-технологий. Отмечаются перспективы интеграции в архитектуру цифровых валют центральных банков и развитие инфраструктуры Web3 на базе ZK-решений
Ethereum enables the creation and execution of decentralized applications through smart contracts, that are compiled to Ethereum Virtual Machine (EVM) bytecode. Once deployed in the blockchain, the bytecode is immutable; hence, ensuring that smart contracts are bug-free before their deployment is of utmost importance. A crucial preliminary step for any effective static analysis of EVM bytecode is the extraction of the control-flow graph (CFG): this presents significant challenges due to potentially statically unknown jump destinations. In this paper we present a novel approach, based on Abstract Interpretation, aiming to build a sound CFG from EVM bytecode smart contracts. Our analysis, which is implemented in our static analyzer EVMLiSA, is based on a parametric abstract domain that approximates concrete execution stacks at each program point as an l -sized set of abstract stacks of maximal height h ; the results of the analysis are then used to resolve the jump destinations at jump nodes. Furthermore, EVMLiSA includes a checker for reentrancy detection, working on the constructed CFG. Our experiments show that, by fine-tuning the analysis parameters, EVMLiSA is able to build sound CFGs for all real-world smart contracts in the considered benchmark suite. Moreover, EVMLiSA successfully detects all reentrancy vulnerabilities in EVM bytecode smart contracts, while producing a small number of false positives.
Finetuning Large Language Models (LLMs) is a highly effective way to improve their performance on the specific domains that need expertise knowledge. However, fine-tuning very large models is prohibitively expensive. A trending solution is to train a much smaller adapter, dubbed LoRA, serving as a “plugin” to the model. However, in an untrusted distributed edge computing environment, when a user of an open-source base model wishes to utilize LoRA weights provided by external contributors, it is crucial to ensure that the LoRA weights are correctly matched with the intended base model and that the LoRA computation process is executed correctly. In this paper, we present ZK-EDGELORA, an efficient zero-knowledge (ZK) protocol that allows the LLM adapter (LoRA, the prover) to convince the base LLM model (the verifier) of its computing pro- cess, without revealing any information apart from the fact that the LoRA computing process is true. In particular, by leveraging VOLE-based “commit-and-prove” style ZK protocol, our solution enables efficient batch verification of matrix operations while preserving privacy. The proposed ZK-EDGELORA can safely and efficiently validate the correctness of each LoRA module within 0.1 to 2.8 seconds, depending on the weight size of the LoRA layer, when applied to real-world medical adapters from HuggingFace. The protocol establishes a scalable trust framework for distributed LLM deployments, bridging the gap between performance and security in modular AI ecosystems.
In blockchain systems, Merkle trees represent a fundamental cryptographic structure for verifying the validity of public keys in digital signatures. However, the verification process presents significant computational challenges, particularly when dealing with large-scale public key participation in signing operations. This paper focuses on addressing the efficiency bottlenecks in public key validity verification within Merkle tree commitments, with particular emphasis on their application in trustless cross-chain bridge protocols. While existing cross-chain solutions predominantly rely on zero-knowledge proofs for blockchain state validation, the inherent computational cost of proof generation remains prohibitive.We present a novel batch opening scheme for Merkle tree commitments that synergistically integrates Merkle tree construction from permutation arguments to verify the membership of extensive leaf sets. Our approach demonstrates remarkable proof generation efficiency advantages, particularly maintaining consistent performance regardless of the number of opened leaves, given a fixed tree depth. Our methods significantly reduce the computational overhead associated with public key validity verification. Meanwhile, it is fully applicable to the existing classical Merkle tree structure without any modifications and has universality.To demonstrate the practicality and efficiency of our scheme, We implemented the Merkle tree opening circuit for three hash functions (Poseidon, Rescue and Keccak) based on our scheme. Our evaluation shows that the batch opening scheme achieves better performance: proof generation time begins to shorten from an opening ratio of 0.25, achieving a 3.5 to 7.1× improvement at a ratio of 0.75 (with tree depth = 9). Similar improvements are also reflected in the proof size and verification time. Moreover, as tree depth increases, our method’s performance advantages become more pronounced.