Henry Ohiani Ohize, Adeiza James Onumanyi, Lukman Adewale Ajao, Buhari Ugbede Umar · 9 authors
Despite significant advances in electronic voting technologies, voter accreditation in many electoral systems remains vulnerable to identity fraud, database tampering, equipment failure, and centralized security breaches. Existing accreditation solutions often rely on single-modal biometric authentication and centralized architectures, limiting their robustness, transparency, and public trust. This paper proposes a Blockchain-based Bimodal Voter Accreditation System (Block-BVAS), together with a practical framework for its deployment in electronic voting systems. The proposed system integrates multimodal biometric authentication using facial and fingerprint recognition with a private Ethereum blockchain and conventional cryptographic mechanisms to provide secure, tamper-resistant, and auditable voter accreditation to provide secure, decentralized, and tamper-resistant voter accreditation. A Raspberry Pi 5 serves as the embedded processing platform, demonstrating the feasibility of implementing the framework on cost-effective hardware. By combining distributed-ledger technology with encrypted biometric verification, the proposed architecture enhances the integrity, confidentiality, and immutability of election-related records while addressing limitations associated with single-factor authentication and conventional centralized record management. Experimental evaluation of the biometric authentication module performed effectively, with fingerprint recognition achieving an average authentication accuracy (AA) of 97.8% and facial recognition averaging 95.1%. The blockchain storage overhead (BSO) displayed a near-linear growth pattern relative to the number of transactions, consistent with theoretical expectations for blockchain architectures. Reliability analysis indicated system uptime exceeding 95%, with only minimal operational failures recorded during the test period. This blockchain implementation further demonstrated reliable transaction processing and secure record management, indicating the effectiveness of the proposed Block-BVAS in enhancing the security, transparency, and trustworthiness of electronic voter accreditation.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Digital image steganography has evolved from traditional rule-based techniques to advanced data-driven frameworks enabled by deep learning. However, existing surveys remain fragmented, often focusing on limited aspects while overlooking emerging paradigms such as blockchain-integrated and quantum-based approaches. This paper presents a comprehensive and systematic review of digital image steganography following the PRISMA 2020 guidelines, covering studies published between January 2015 and April 2026 across six major scientific databases. From an initial pool of 26,539 records, 83 relevant studies were selected through a rigorous two-stage screening process. The review provides a unified analysis of steganographic techniques by examining five dimensions: structural evolution and taxonomy, algorithmic modifications and hybridisation, application domain mapping, integration of emerging technologies, and future research trends. Comparative evaluation indicates that deep learning-based methods achieve 18–23% higher steganalysis resistance than classical approaches, whereas classical methods retain a 5–8 dB PSNR advantage. The quantitative synthesis further confirms the inherent capacity–imperceptibility–security trilemma, wherein no reviewed technique simultaneously achieves $$\text {PSNR} > 42$$ dB, embedding capacity $$> 4$$ bpp, and detection error rate $$> 0.48$$ . Six open challenges and seven future research directions are identified and grounded in evidence from the included studies, with explainable steganography, quantum-resistant frameworks, and latent diffusion model integration emerging as the most critical priorities for advancing the field toward practical and secure deployment.
Open access
Advanced Steganography and Watermarking Techniques
With the rapid proliferation and interconnection of massive IoT devices, efficient and secure identity authentication has become a crucial prerequisite for ensuring communication security. Establishing trust among mutually untrusted devices remains a key research focus. Leveraging its tamper-resistance and traceability, blockchain technology has emerged as a foundational infrastructure for building trustworthy identity management systems. However, existing blockchain-based identity authentication schemes face critical challenges in large-scale IoT environments, including low authentication efficiency, complex certificate management, and risks of user privacy leakage. Achieving a balance among authentication efficiency, certificateless key management, and privacy protection remains a pressing challenge. In this paper, we propose a certificateless identity authentication scheme based on blockchain sharding. The scheme employs blockchain sharding to parallelize identity authentication across multiple shards, significantly enhancing overall efficiency. Within each shard, a certificateless public key cryptography (CL-PKC) scheme is adopted to eliminate certificate issuance and enable key generation via user interaction, thereby reducing key management overhead and improving security. For cross-shard authentication, a registration-based encryption (RBE) mechanism is utilized, allowing users to authenticate via their identity after registration. Any verifier can confirm the legitimacy of the authentication message solely based on the registration information and the user ID, ensuring transparency and public verifiability. Furthermore, a zero-knowledge proof-based verifiable credential (VC) selective disclosure mechanism is introduced, enabling users to reveal only the minimal necessary information required for authentication while protecting sensitive identity attributes. Experimental results demonstrate that the proposed scheme maintains high throughput under high-concurrency scenarios while effectively preserving user privacy.
Open access
2 source records
Cryptography and Data Security
Privacy-Preserving Technologies in Data
Advanced Steganography and Watermarking Techniques
Abstract A Non-Fungible Token (NFT) is a digital asset representing ownership or proof of authenticity of a unique digital item. NFTs are used for various purposes, including digital art, collectibles, virtual real estate, and tokenizing unique digital or physical items, and have introduced new dimensions to digital ownership and enabled individuals to tokenize unique digital assets using blockchain technology. Although NFTs offer exciting opportunities, they suffer from interoperability, high energy consumption, piracy, ownership control, and security issues. In this paper, an idea has been proposed in which any image, pdf file, or video file can be converted to an NFT and owned. We have used the ERC-721 standards, the PoS consensus protocol, and a smart contract to address the challenges. The proposed framework provides a step-by-step guide to create, list NFTs and maintain secure ownership where metadata are stored on IPFS, which generates a unique URL. This URL is then logged on the blockchain, saving time and costs. The created NFTs are interoperable among various applications and frameworks. Smart contract has been formally verified using Slither and tested against vulnerability using Smart Contract Weakness Classification (SWC) standards. Performance of the proposed system has been measured in terms of execution cost, latency, and throughput including statistical indicators like variance and confidence intervals. Minting cost has been compared with the similar network condition.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cheri Venkata Sai, Gurijela Pavan, Pittala Abhirameshwar, S. Suma
These come hand in hand with unprecedented levels of complexity in copyrighting and mon- etizing creations. In general, this protects the copyrights under the existing framework, which are cen- tralized, expensive, and beyond the reach of any independent creator. This paper presents an innovative blockchain-based framework for image copyrighting and social crypto monetization by using blockchain technologies such as Ethereum smart contracts and the InterPlanetary File System (IPFS). The proposed framework enables creators to publish digital images, calculate cryptographic proofs of image ownership with the SHA-256 hashing algorithm, store images in IPFS, and record metadata into the blockchain with unchanged timestamps. In addition, the platform supports “Like to Earn”, where public engagement for viewing is translated directly into rewarding creators with cryptocurrencies via smart contracts. The proposed framework adopts Web3 technologies to enable secure signing of all transactions with fraud prevention using the Elliptic Curve Digital Signature Algorithm (ECDSA) technique through MetaMask wallet authentication. Experimental evaluation of the proposed framework confirms that it can remove duplicate uploads, promptly verify image ownership, and enable social monetization of cryptocurrencies in a secured way.
Open access
2 source records
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Document authentication remains a pressing challenge in various domains, including financial services, academic credentialing, healthcare, and supply chain management. Existing centralized verification systems are vulnerable to manipulation, inefficiency, and limited transparency. Blockchain technology, with its immutability and tamper-resistant capabilities, offers a strong decentralized alternative; however, many current implementations lack structured, issuer-bound relationships for documents. This paper proposes a blockchain-based model that leverages a hierarchical token structure to authenticate and trace the provenance of high-value digital documents, with a focus on financial records. The model introduces the concept of an issuer-bound parent token and document-linked child tokens, enforcing a structured trust relationship between a legitimate institution and the documents it issues. By combining on-chain cryptographic hashing with off-chain file references, the approach is designed to balance verifiability with scalability. We implement a proof-of-concept using Ethereum-compatible smart contracts on a permissioned blockchain and evaluate it in a consortium-style financial setting. Our functional analyses demonstrate the model’s ability to ensure document integrity, provenance, and resistance to document fraud. This work offers a practical and extensible foundation for secure digital document authentication and verification in financial and other trust-sensitive settings.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Alinsha S, A Althaf, Chris P Reji, Fahad Mohammed A · 6 authors
Electronic voting techniques have gained popularity as a contemporary alternative to traditional paper-based elections because of their effectiveness and accessibility. The current electronic voting methods, however, have significant security flaws, such as multiple voting, identity theft, centralized control, and a lack of transparency. Despite the fact that blockchain technology is decentralized, immutable, and auditable, many blockchainbased voting systems merely employ cryptographic credentials and lack robust voter identification verification processes. The blockchain-based electronic voting system SecureVote, which incorporates multi-factor verification and facial biometric authentication, is proposed in this study. Ethereum smart contracts are used by the system to guarantee transparent result calculation and tamper-proof vote storage. SecureVote employs one-time password (OTP) validation as a secondary authentication method in conjunction with client-side facial recognition and deep learning-based feature extraction. The suggested design makes use of Web3.js and a decentralized application (DApp) concept for safe wallet-based transaction signing and blockchain interaction. High authentication reliability, avoidance of double voting, and effective transaction processing with low gas overhead are all demonstrated by the experimental results. SecureVote combines biometric multifactor authentication with blockchain immutability to enhance the reliability, transparency, and integrity of remote voting.
Open access
2 source records
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Dr. A. Radhika, D. Avinash, D. Sowjanya, K. Karthik · 5 authors
The increasing use of digital communication has made it essential to maintain the confidentiality, integrity, and authenticity of sensitive information. Conventional image steganographic methods offer data hiding in digital images, but they fail to offer effective tamper proofing and secure ownership verification. To overcome these issues, this paper presents a Blockchain-Integrated Secure Image Steganography system using IPFS and Ethereum. In the proposed system, secret data is hidden within digital images using a Least Significant Bit (LSB) image steganographic method developed in Python. The stego images are then stored in the Inter Planetary File System (IPFS) for efficient and decentralized data storage. To ensure data integrity and secure access, the cryptographic hash values of the stego images and their corresponding IPFS Content Identifiers (CIDs) are securely stored on the Ethereum blockchain using smart contracts. The use of blockchain technology provides immutability, transparency, and tamper resistance, and IPFS provides decentralized storage without depending on centralized storage servers. The proposed system is validated to offer high image quality with negligible distortion and robust data security and traceability. This system is applicable for secure data sharing in confidential communication, digital forensics, and secure document transfer.
Open access
Advanced Steganography and Watermarking Techniques
Decentralized storage platforms and blockchain systems offer novel opportunities for data exchange; however, they also present significant challenges in safeguarding sensitive visual information. The Interplanetary File System (IPFS) offers efficient distributed storage, but it lacks built-in confidentiality mechanisms, making additional security layers necessary. This work proposes a security-oriented framework that integrates (k,n) threshold visual cryptography (shamir secret ), LSB-based image steganography, and blockchain-based ownership management using non-fungible tokens (NFTs). Sensitive images are divided into multiple visual shares using a threshold scheme so that no useful information can be obtained unless enough shares are available. Each share is then hidden inside a cover image using a simple LSB-based steganography method and stored on IPFS. Instead of storing the data itself on the blockchain, NFTs are used only to reference the stored content and record ownership in an immutable manner. Experimental results are evaluated using common image quality and statistical metrics, including PSNR, SSIM, correlation, and entropy. With PSNR = Inf dB for all images, Entropy analysis shows that the entropy values of the original cover images are approximately 7.0865, while the entropy values of the stego-images after embedding range between 7.0907 and 7.0954, indicating only a slight increase in randomness. This minimal change confirms that the LSB-based steganographic embedding does not significantly alter the statistical properties of the cover images. The findings show that the original images can be reconstructed with acceptable visual quality while preserving the statistical characteristics of the cover images. The proposed approach demonstrates that combining visual cryptography with decentralized storage and blockchain-based ownership can offer improved confidentiality compared to direct on-chain image storage, without introducing excessive system complexity.
Open access
Advanced Steganography and Watermarking Techniques
The digital art industry faces critical challenges in copyright protection and privacy preservation that existing solutions fail to adequately address. Traditional digital watermarking techniques are vulnerable to removal attacks and cannot prevent unauthorized content access, while current Non-Fungible Token (NFT) platforms expose transaction details and artwork content due to blockchain transparency, creating privacy risks for creators and collectors. Conventional encryption methods require decryption before any data processing, making copyright verification and feature extraction impossible in encrypted states, thus creating a fundamental security-usability trade-off. To overcome these limitations, this research proposes a network security protection system integrating homomorphic encryption with NFT copyright protection. Homomorphic encryption was selected because it uniquely enables computational operations on encrypted data without decryption, allowing copyright verification while maintaining complete data confidentiality – a capability unmatched by alternative privacy-preserving technologies. The system employs the Cheon-Kim-Kim-Song (CKKS) homomorphic encryption algorithm to construct a three-tier protection architecture consisting of an encryption layer, verification layer, and storage layer. This architecture achieves copyright verification and feature extraction of digital artworks in ciphertext state by integrating zero-knowledge proof for identity authentication and Shamir’s secret sharing for secure key management. The NFT copyright protection mechanism introduces homomorphic watermark embedding and smart contract verification, combined with proxy re-encryption to implement secure copyright transfer. A prototype system was developed and evaluated through comprehensive testing. Security performance was assessed using six metrics: privacy protection strength, copyright verification accuracy, anti-tampering capability, key security, transaction anonymity, and system resilience. Each metric was scored on a 0–100 scale based on standardized penetration testing and cryptographic attack simulations, with the comprehensive security score calculated as the weighted average of all metrics. Performance testing on 100 digital artworks across five resolutions (256×256 to 4096×4096 pixels) demonstrates that encryption time for 512×512 resolution images is kept within 15 seconds, while security testing reveals the system achieves a comprehensive security score of 94.7, representing a 60.5% improvement over traditional NFT platforms. This solution provides a practical copyright protection framework balancing security and usability for the digital art industry, with significant theoretical value and broad application prospects.
Open access
Advanced Steganography and Watermarking Techniques
In the digital era, protecting visual content from misuse and forgery is essential. This study proposes a robust image watermarking method by integrating Discrete Wavelet Transform (DWT), Hessenberg Decomposition (HD), and Singular Value Decomposition (SVD), aiming to enhance watermark imperceptibility and resilience against common image attacks. Additionally, the system incorporates RSA digital signatures within the watermark metadata to ensure verifiable authenticity in NFT (Non-Fungible Token) applications. The method was implemented using Python and tested on multiple grayscale images across various attack scenarios, including noise addition and compression. Experimental results demonstrate high SSIM and PSNR values, confirming the method's effectiveness in maintaining both visual fidelity and embedded watermark integrity. These findings support the potential of this approach for secure and scalable NFT copyright protection.
Open access
Advanced Steganography and Watermarking Techniques
Prof. Abhijeet More, Tejashree B. Patil, Deep Kharate, M P Akhil · 5 authors
As the multi-chain digital assets, decentralized finance (DeFi) and non-fungible tokens (NFTs) seeing rapid development, cryptocurrency portfolio management is causing strong pain among users.With the growing number of blockchain networks like Ethereum and a variety of chains, users commonly have assets across multiple wallets, protocols and dApps.Classic portfolio tracking services often require the constant relationship between client and server, with centralized servers, offering heavy privacy issues and security implications.Manual and account based access Many of these systems require data to be manually entered or employees to sign in with their accounts, which opens up the possibility for data leaks, inaccurate reporting, and divulgence of sensitive financial information.More centralized trackers unfortunately have a very poor understanding of more advanced DeFi functions such as staking, joining liquidity pools, and yield farming positions, total or just plain token approval permissions leading to either incomplete or worse yet misleading asset summaries.To solve the above issues, this system suggests a completely decentralized cryptocurrency portfolio tracker on client-side.The code utilizes APIs like Alchemy, Zapper and CoinGecko to read real-time token balances, NFTs creatures or positions (for DeFi), and allowances from the current network directly offchain.Being exclusively client side, the tracker does not rely on centralized databases and it is designed to minimize privacy compromises.The built-in on-chain security module is its most noticeable feature, as it detects any potentially malicious or extremely large token approvals given to smart contracts.Suspicious approvals can be detected, and then revoked in a timely manner through signed wallet transactions without needing to reveal any private keys.The results show that this decentralized tracker would provide significantly better user privacy, data accuracy and overall security.As a serverless applications service, that bypasses central authentication, as well as database storage, it offers a transparency, user-centric and scalable way to manage digital assets securely.
Open access
Internet Traffic Analysis and Secure E-voting
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
Biometric authentication provides high convenience with the drawback of privacy leakage, replay attacks, and centralized control over biometric templates. This paper introduces an Ethereum-based decentralized biometric authentication framework that uses Elliptic Curve Digital Signature Algorithm (ECDSA), InterPlanetary File System (IPFS) storage, and an on-chain challenge–response protocol. In the proposed model, encrypted biometric templates are stored of-chain in IPFS, whereas their content identifiers (CIDs) are registered in Ethereum smart contracts. Every authentication attempt necessitates a new on-chain nonce and an ECDSA signature of the concatenation of the CID and the nonce, authenticated through Ethereum’s built-in method, ecrecover. The design supports explicit replay protection, revocation, and public auditability. Deployment of the prototype on Ganache and MetaMask reveals that the scheme provides secure, transparent, and tamper-proof authentication with minimal gas consumption on FVC2004 datasets and reasonable storage usage on Ethereum.
Open access
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
The thriving Non-Fungible Token(NFT) market, despite its innovative redefinition of digital ownership, faces malicious attacks and challenges, notably from widespread wash trading. In this paper, we examine the underexplored relationship between NFT rarity and wash trading.We present a novel approach to NFT market dynamics, by establishing the first comprehensive formal framework for NFT trait systems, including essential definitions, a robust taxonomy, precise rarity calculation, and verifiable properties. Building upon this, we conduct an empirical analysis of NFT rarity and wash trading across 30 collections including 336,133 NFTs, 764,679 transactions, total volume of 14,394,949 in Ethereum. Our findings reveal the strong inverse correlation between a collection’s price-rarity coefficient and its wash trading volume, showing that the top 5 collections with the lowest price-rarity coefficients are overwhelmingly dominated by wash trading, averaging 89.29% of their total volume, in contrast to the vast majority of other collections which exhibited negligible volumes, consistently below 2%. Case studies further highlight the power of this price-rarity analysis as a novel anomaly detection tool: it exposed wash trading-induced distortions in CryptoPunks by detecting an outlier previously undetectable by existing graph-based approaches. We also demonstrate Rektguy’s remarkable resilience—absorbing 20.04% wash volume possibly due to strong rarity-price correlation. Our findings establish rarity as an intrinsic resilience factor against manipulation, fundamentally reshaping approaches to NFT market analysis and robust anomaly detection.
Open access
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Advanced Steganography and Watermarking Techniques
L. B. WANG, Liming Zhang, Ruitao Qu, Tao Tan · 6 authors
Existing vector geographic data transaction schemes are typically merchant-controlled, hindering fair ownership tracing and impartial arbitration. To address this, we propose an asymmetric digital fingerprinting scheme based on smart contracts. In our approach, the user encrypts a proof fingerprint with a public key and sends it to the merchant; the merchant leverages the additive homomorphic property of the Paillier cryptosystem to embed the encrypted user fingerprint into an encrypted portion of the vector data while embedding a tracking fingerprint into the plaintext portion. The combined data is delivered to the user, who uses their private key to decrypt the encrypted part and obtain the plaintext data containing both fingerprints. This design enables tracing of unauthorized distribution without exposing the user’s fingerprint in plaintext, preventing malicious accusations. By leveraging blockchain immutability and smart contract automation, the scheme supports secure, transparent transactions and decentralized arbitration without third-party involvement, thereby reducing collusion risk and protecting both parties’ rights.
Open access
Advanced Steganography and Watermarking Techniques
With the rapid proliferation of smart home cameras, wearable vision devices, and user-generated Consumer Internet of Things (CIoT) content, ensuring visual media authenticity, rightful ownership, and tamper detection has become increasingly challenging. We propose Chain-Visage, a blockchain-assisted framework for secure content authentication and tamper tracing in decentralized CIoT multimedia ecosystems. The termChainreflects the consortium blockchain backbone that guarantees immutable provenance, decentralized ownership management, and copyright revocation, whileVisagesymbolizes the unique visual identity of multimedia content achieved through dual-stage visual hash embedding. The proposed framework integrates Zero-Knowledge Proofs (ZKPs) for privacy-preserving ownership verification and employs optimized smart contracts to manage visual rights, provenance records, and ownership transfers efficiently. Evaluations on a large-scale dataset of over 10,000 real-world images and 3,850 video clips from diverse CIoT devices demonstrate Chain-Visage’s superior performance, achieving 97.5% traceability accuracy, 93% tamper detection sensitivity, and low verification latency even under resource-constrained environments. This work addresses a critical research gap in secure, privacy-preserving, and energy-efficient multimedia ownership control and tamper-resilient content authentication for next-generation CIoT ecosystems.
Open access
Blockchain Technology Applications and Security
Digital Media Forensic Detection
Advanced Steganography and Watermarking Techniques
The rapid expansion of the Non-Fungible Token (NFT) market has underscored significant challenges in copyright protection and ownership authentication. While blockchain technology ensures the immutability and transparency of token transactions, the off-chain storage of metadata and original content remains a critical vulnerability, exposing NFTs to risks such as data loss, manipulation, and copyright disputes. In response to these challenges, this study proposes a blockchain-integrated watermarking framework that embeds resilient copyright information into digital assets via a general frequency-domain approach. The watermark is stored off-chain within the InterPlanetary File System (IPFS), while its associated Content Identifier (CID) is anchored in a smart contract, ensuring traceability of provenance and verification of authenticity. Comparative experiments with the Least Significant Bit (LSB) method demonstrate the superior robustness of the proposed frequency-domain technique against various attacks, including compression, noise, and image manipulation. The proposed framework significantly enhances copyright protection, facilitates transparent NFT provenance, and provides a scalable foundation for secure digital asset management within blockchain-based ecosystems.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
In 2008, the idea of Bitcoin, a peer-to-peer electronic cash system, was proposed by Satoshi Nakamoto. It describes a distributed system for managing digital transactions. Based on this idea, the blockchain concept has evolved. Blockchain is a distributed ledger. The ledger is immutable and shareable among all the user nodes. The ledger/blockchain contains several blocks chained by hash values. If we try to modify a block, its hash value will change; the hash value is already stored in the neighbor node, so the neighbor node will not allow it to change. Thus, immutability is achieved. The blockchain is worthy because of its good characteristics, such as data decentralization and a high level of trust. This chapter represents a detailed study on blockchain architecture, consensus mechanisms, and their application in digital image watermarking. Digital image watermarking is used for copyright protection, ownership claim, and image tamper detection. If we use blockchain with watermarking, the technique becomes more secure and robust. Though the applications of blockchain technology in image watermarking are in a nascent stage at present, the disruptive and revolutionary nature of the blockchain will make it a significant force shortly.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The article presents an analysis of the robustness of an authentication scheme based on zero watermarking. The study examines a two-factor authentication scheme that uses "knowledge of something" (a password) and "possession of something" (a digital RGB image) as its factors. The zero watermarking algorithm chosen is based on DWT and K-means transformations, with additional use of the Swish function. The analysis is conducted by considering the theoretical complexity of the algorithm assuming the adversary knows its parameters, such as the password, the hash of the password, the image, the reference watermark, the transformation result, and other parameters. Previous studies have shown a high theoretical robustness of the scheme, which relies on the complexity of the password and the dimensionality of the image. For large image sizes (512×512 pixels and above), a relatively high level of cryptographic resistance is achieved. However, this robustness is not formally proven, and the actual strength may be significantly lower due to the specifics of the images and transformations, which can introduce additional vulnerabilities. The algorithm is subject to a relatively high rate of collision, associated with digital image transformations and matrix multiplications, which weakens its resistance. Authentication schemes and zero watermarking algorithms require further research, formal proof of cryptographic properties, and methods for integration into access control systems, as they can provide a high level of authentication robustness in systems with high noise levels. Additionally, the convenience and low cost of such schemes give them an advantage over other authentication methods. The study provides recommendations for improving the potential characteristics of the algorithm.
Open access
Advanced Steganography and Watermarking Techniques
The increasing need for trustworthy digital document verification presents challenges in ensuring authenticity, transparency, and tamper resistance without relying on centralized authorities. This study aims to develop and evaluate a decentralized document notarization system using Ethereum and IPFS that offers secure, transparent, and cost-efficient verification. The system employs modular smart contracts deployed through a factory pattern to create user-specific verifier instances, enabling document submission, revocation, and verification using keccak-256 hashes, ECDSA signatures, and IPFS content identifiers. Methods include contract development, deployment on a local Hardhat network, performance benchmarking, and front-end integration for user interaction. Results show that verifier deployment consumes approximately 1.19 million gas (≈$85 at 20 gwei), document submission around 85 thousand gas (≈$6), and revocation about 50 thousand gas (≈$3.50). Client-side operations such as hashing and IPFS pinning occur in under 50 milliseconds, while real-world blockchain confirmations take 10–30 seconds. The findings demonstrate that decentralized notarization using Ethereum and IPFS is both technically feasible and economically viable. Future enhancements, including Layer 2 rollups, batch notarization, and privacy-preserving features such as encrypted IPFS pinning or zero-knowledge proofs, are proposed to further improve scalability, cost-efficiency, and data confidentiality
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Audio piracy detection is increasingly complex in decentralised distribution settings, where mainstream approaches fail to ensure robustness, verifiability, or computational efficiency. Conventional Digital Rights Management (DRM) systems mainly enforce licensed access, but once content is copied or redistributed outside their control they offer little protection. Classical fingerprinting approaches such as MFCC based hashes can detect near-exact duplicates, yet they often fail under signal edits like pitch shifting, time stretching or equalisation. Deep learning embeddings improve robustness but demand heavy computation and centralised resources, making them less suitable for edge or decentralised deployments. These limitations call for a solution that is both edit resilient and verifiable. We propose HashWave, a blockchain-integrated perceptual hashing framework that combines robust audio fingerprinting with tamper-proof verification. The system fuses MFCC, chroma and chroma CENS, CQT, spectral contrast, and lightweight tempo/energy cues, applying operation-aware weighting via [Formula: see text] and constrained DTW for time-scale edits. Evaluated across GTZAN, FMA-A Dataset for Music Analysis, and MUSAN (SLR17) with over twenty signal-processing transformations, HashWave achieves AUC 0.957 and TPR@1%FPR 0.952, outperforming MFCC-only baselines and approaching deep embeddings at lower CPU cost. The blockchain layer, built on Ethereum and IPFS, ensures decentralised hash storage, duplication control, and verifiable authorship with average upload and contract execution times of 0.017 s and 0.044 s. Together, these results establish HashWave as a practical, scalable, and secure framework for piracy detection across streaming, podcasting, and Web3 ecosystems.
Open access
Advanced Steganography and Watermarking Techniques
The integrity, coupled with the transparency of electoral systems, is vital for the existence of a democratic society if that society is to function well. Often, conventional electronic voting mechanisms are criticized for their security vulnerabilities, with a lack of transparency, together with limited public trust. Blockchain technology has come about to be a possible enabler for trustless and immutable systems. However, such a standard, privacy-preserving, verifiable voting model remains elusive. This work seeks to fill this void with the use of a blockchain e-voting system that uses QR codes to validate voters, cryptographically ensures integrity with the EFFT-SWIFFT hash, and also handles ballots through smart contracts. A feature matrix together with a visual chart was used in a systematic literature review of 28 peer-reviewed papers to analyze and compare authentication methods, transparency techniques, consensus mechanisms, and scalability solutions. Though the analysis reveals that entities greatly underutilize advanced cryptographic primitives such as zero-knowledge proofs and post-quantum hashing, these primitives potentially improve privacy and also verifiability. Present in the proposed model is a multi-layered architecture. Also, the model can offer a secure as well as transparent solution for addressing these gaps. Blockchain-based e-voting can increase trust, reduce fraud, and broaden democratic participation, but it requires real-world validation through pilot projects and usability testing.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
The integration of blockchain technology into healthcare presents a paradigm shift for secure data management, enabling decentralized and tamper-proof storage and sharing of sensitive Electronic Health Records (EHRs). However, existing blockchain-based healthcare systems, while providing robust access control, commonly overlook the high latency in user-side re-computation of hashes for integrity verification of large multimedia data, impairing their practicality, especially in time-sensitive clinical scenarios. In this paper, we propose FAITH, an innovative scheme for \underline{F}ast \underline{A}uthenticated and \underline{I}nteroperable mul\underline{T}imedia \underline{H}ealthcare data storage and sharing over hybrid-storage blockchains. Rather than user-side hash re-computations, FAITH lets an off-chain storage provider generate verifiable proofs using recursive Zero-Knowledge Proofs (ZKPs), while the user only needs to perform lightweight verification. For flexible access authorization, we leverage Proxy Re-Encryption (PRE) and enable the provider to conduct ciphertext re-encryption, in which the re-encryption correctness can be verified via ZKPs against the malicious provider. All metadata and proofs are recorded on-chain for public verification. We provide a comprehensive analysis of FAITH's security regarding data privacy and integrity. We implemented a prototype of FAITH, and extensive experiments demonstrated its practicality for time-critical healthcare applications, dramatically reducing user-side verification latency by up to $98\%$, bringing it from $4$ s down to around $70$ ms for a $5$ GB encrypted file.