The Internet of Things (IoT) is a disruptive technology that underpins Industry 5.0 by integrating various service technologies to enable intelligent connectivity among smart objects. These technologies enhance the convergence of Information Technology (IT), Operational Technology (OT), Core Technology (CT), and Data Technology (DT) networks, improving automation and decision-making capabilities. While cloud computing has become a mainstream technology across multiple domains, it struggles to efficiently manage the massive volume of OT data generated by IoT devices due to high latency, data transfer costs, limited resilience, and insufficient context awareness. Fog computing has emerged as a viable solution, extending cloud capabilities to the edge through a distributed peer-to-peer (P2P) network, enabling decentralized data processing and management. However, IoT networks still face critical challenges, including connectivity, heterogeneity, scalability, interoperability, security, and real-time decision-making constraints. Security is a key challenge in IoT implementations, including secure data communication, IoT edge and fog device identity, end-to-end authentication, and secure storage. This paper presents an efficient blockchain-based framework that creates a secure end-to-end communication cooperative flow IoT network. The framework utilizes a hybrid blockchain network that collaborates to offer a collaborative flow of end-to-end secure communication from end devices to cloud storage. The fog servers will maintain a private blockchain as a next-generation public key infrastructure to identify and authenticate the IoT's edge devices. The consortium blockchain will be maintained in the cloud and integrated with the permission blockchain system. This system ensures secure cloud storage, authorization, efficient key exchange, and remote protection (encryption) of all sensitive information. To improve the synchronization and block generation, reduce overhead, and ensure scalable IoT network operation, we proposed the threshold signature-based Proof of Stake and Validation (PoSV) consensus. Additionally, lightweight authentication protects resource-constrained IoT nodes using an aggregate signature, ensuring security and performance in real-time scenarios. The proposed system is implemented, and its performance is evaluated using key metrics such as cryptographic processing overhead, consensus efficiency, block acceptance time, and transaction delay. The findings show that threshold signature-based Proof of Stake and Validation (PoSV) consensus, reduces the computational burden of individual signature verification, which results in an optimized transaction latency of 80-150 ms, compared to the previous 100-200 ms without Non-PoSV. Additionally, aggregating multiple signatures from different authentication events reduces signing time by 1.98 ms compared to the individual signature time of 2.72 ms and the overhead of verifying multiple individual transactions is 2.87 ms is significantly reduced to1.46 ms along with authentication delay ranges between 95-180 ms. Hence, the proposed framework improves over existing approaches regarding linear computing complexity, increased cryptographic methods, and a more efficient consensus process.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
In this work, we address the evolutionary computation in programmable cryptography on blockchain technologies for the first time in the literature. For that, we propose a novel privacy-preserving and decentralized protocol ([email protected]) where the evolutionary computation model is public while the user inputs/outputs (i.e. the current and next populations) are private. The protocol relies on the transitions between the public-domain (i.e. contract-domain) and the private-domain (i.e. evolutionary-domain) to be secure. We perform an experimental study using two popular benchmark problems to measure the blockchain gas consumption, zero-knowledge proof generation/verification times and zero-knowledge proof size.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
With the growth of the Internet of Things (IoT), millions of users, devices, and applications compose a complex and heterogeneous network, which increases the complexity of digital identity management. Traditional centralized digital identity management systems (DIMS) confront single points of failure and privacy leakages. The emergence of blockchain technology presents an opportunity for DIMS to handle the single point of failure problem associated with centralized architectures. However, the transparency inherent in blockchain technology still exposes DIMS to privacy leakages. In this paper, we propose the privacy-protected IoT DIMS (PPID), a novel blockchain-based distributed identity system to protect the privacy of on-chain identity data. The PPID achieves the unlinkability of identity-credential-verification. Specifically, the PPID adopts the Zero Knowledge Proof (ZKP) algorithm and Shamir secret sharing (SSS) to safeguard privacy security, resist replay attacks, and ensure data integrity. Finally, we evaluate the performance of ZKP computation in PPID, as well as the transaction fees of smart contract on the Ethereum blockchain.
Open access
Blockchain Technology Applications and Security
Network Security and Intrusion Detection
Advanced Steganography and Watermarking Techniques
The rapid proliferation of mobile IoT devices with inadequate security measures has elevated security to a critical concern. Researchers have proposed various systems for vulnerability detection based on conventional frameworks. However, these approaches often face challenges such as high computational costs, limited storage capacity, and slow response times. To ensure robust protection against cyberattacks, modern security solutions must continuously monitor and analyze historical data across the entire IoT network. This paper introduces a distributed security framework for IoT networks, leveraging software-defined networking (SDN), blockchain, and edge computing to efficiently detect and mitigate IoT-based attacks. In the proposed framework, SDN facilitates network-wide data monitoring and analysis, enabling effective attack detection. Blockchain technology ensures decentralized and tamper-resistant attack identification, addressing potential vulnerabilities. Meanwhile, the edge computing paradigm enables real-time attack detection at the network edge, ensuring timely alerts. An experimental evaluation of the proposed framework demonstrates its superiority over traditional approaches in terms of detection accuracy (98.7%), false positive rate (1.2%) and response time (101.1 ms), highlighting its effectiveness in securing IoT networks.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Kode Lakshmi Durga Sindhujasri, Kaduputla Manogna, Sutrayeth Hari Yuktha Nanda, Baligiri Thandava Krishna · 5 authors
Abstract: Elections play a fundamental role in any democratic system, and ensuring their integrity is of utmost importance. Traditional voting methods, such as paper ballots and Electronic Voting Machines (EVMs), suffer from various limitations, including security vulnerabilities, vote tampering, low voter turnout, delays in result processing, and a lack of transparency. Digital voting solutions offer convenience but raise concerns regarding data security and susceptibility to cyber threats. Blockchain technology presents a promising solution to these challenges by providing a decentralized, transparent, and tamperproof framework for conducting elections. As a distributed ledger system, blockchain records transactions in an immutable and verifiable manner, ensuring the integrity of votes. Key features such as decentralization, cryptographic security, transparency, and anonymity make blockchain a robust choice for secure e-voting. In this paper, we propose and implement a blockchainbased e-voting system using Ethereum smart contracts and Web3.js. Our system enforces single-use voting credentials, preventing duplicate votes, and leverages gas fees to mitigate fraudulent voting attempts. Additionally, we develop a web-based application that demonstrates the practical implementation of blockchain voting, discussing its advantages, challenges, and limitations in real-world scenarios
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Atsuki Koyama, Kentaroh Toyoda, Manato Fujimoto, Thi Hong Tran
The rapid advancement of deepfake technology poses serious risks, including financial fraud and political misinformation, demanding robust methods for verifying image content authenticity. While the C2PA standard and zero-knowledgeproof-based methods provide an image content authenticity proving mechanism, the existing solutions struggle to efficiently support privacy-preserving edits and iterative modifications. To address these challenges, we propose zk-REAL (Zero-Knowledge-Based Protocol for Repeated Image Edit Authenticity Proof with Lattice Hashing), a framework that leverages a lightweight lattice-based hashing scheme within a zero-knowledge proof system. Our approach significantly reduces computational overhead, enabling faster proof generation and smaller proof size even for high-resolution images. Additionally, the updatability of our hashing method supports iterative edits, such as mosaicking or partial modifications, by minimizing redundant computations. Finally, to ensure compatibility with the C2PA ecosystem and conventional signature verifications, we integrate SHA-256 outside of the zero-knowledge circuit. Our evaluation shows up to a 29% reduction in computational costs for proof generation, showcasing the potential of zk-REAL in practical content authenticity verification scenarios.
Open access
2 source records
Advanced Steganography and Watermarking Techniques
Stefan Dziembowski, Shahriar Ebrahimi, Parisa Hassanizadeh
Ensuring the authenticity and credibility of daily media on internet is an ongoing problem. Meanwhile, genuinely captured images often require refinements before publication. Zero-knowledge proofs (ZKPs) offer a solution by verifying edited image without disclosing the original source. However, ZKPs typically come with high costs, particularly in terms of prover complexity and proof size. This paper presents VIMz, a framework for efficiently proving the authenticity of high-resolution images using folding-based zkSNARKs; a type of proving system that minimizes computational overhead by recursively folding multiple evaluations of the same constraints into a compact proof. As a complete proof system, VIMz proves the integrity of both the original and edited images, as well as the correctness of the transformation without revealing intermediate images within a chain of edits--only the final result is disclosed. Moreover, VIMz maintains the anonymity of the original signer and all subsequent editors while proving the authenticity of the final image. We also compare VIMz with the system model in Coalition for Content Provenance and Authenticity (C2PA) from different perspectives and show that VIMz offers higher level of security guarantee by eliminating the need to trust the editing environment. Experimental results show that VIMz performs efficiently in both prover and verifier sides. It can prove the transformations on 8K (33MP,i.e., 100MB) images with up to 13%~25% faster than the competition, while reaching to a peak memory of only 10 GB. Moreover, VIMz has a verification time of under 1 second and achieves succinct proofs of less than 11 KB for all resolutions, which is more than 90% improvement compared to the competition. VIMz's low memory complexity allows for proving multiple transformations in parallel to achieve a 3.5x additional speedup on average.
Open access
Advanced Steganography and Watermarking Techniques
Digital Media Forensic Detection
Physical Unclonable Functions (PUFs) and Hardware Security
We propose Data Tumbling Layer (DTL), a cryptographic scheme for non-interactive data tumbling. The core concept is to enable users to commit to specific data and subsequently re-use to the encrypted version of these data across different applications while removing the link to the previous data commit action. We define the following security and privacy notions for DTL: (i) no one-more redemption: a malicious user cannot redeem and use the same data more than the number of times they have committed the data; (ii) theft prevention: a malicious user cannot use data that has not been committed by them; (iii) non-slanderabilty: a malicious user cannot prevent an honest user from using their previously committed data; and (iv) unlinkability: a malicious user cannot link tainted data from an honest user to the corresponding data after it has been tumbled. To showcase the practicality of DTL, we use DTL to realize applications for (a) unlinkable fixed-amount payments; (b) unlinkable and confidential payments for variable amounts; (c) unlinkable weighted voting protocol. Finally, we implemented and evaluated all the proposed applications. For the unlinkable and confidential payment application, a user can initiate such a transaction in less than $1.5$s on a personal laptop. In terms of on-chain verification, the gas cost is less than $1.8$ million.
Log files are essential assets for IT engineers engaged in the security of server and computer systems. They provide crucial information for identifying malicious events, conducting cybersecurity incident analyses, performing audits, system maintenance, and ensuring compliance with security regulations. Nevertheless, there is still the possibility of deliberate data manipulation by own personnel, especially with regard to system access and configuration changes, where error tracking or debugging traces are vital. To address tampering of log files, this work proposes a solution to ensure data integrity, immutability, and non-repudiation through different blockchain-based public registry systems. This approach offers an additional layer of security through a decentralized, tamper-resistant ledger. To this end, this manuscript aims to provide a solid guideline for creating secure log storage systems. For this purpose, methodologies and experiments using two different blockchains are presented to demonstrate their effectiveness in various contexts, such as transactions with and without metadata. The findings suggest that Solana’s response times make it well suited for environments with moderately critical records requiring certification. In contrast, Cardano shows higher response times, thus making it suitable for less frequent events with metadata that requires legitimacy.
Open access
Blockchain Technology Applications and Security
Digital and Cyber Forensics
Advanced Steganography and Watermarking Techniques
Abstract Privacy is one of the major security concerns. The zero-knowledge proof enables the transmission of data from the sender to the receiver without disclosing the actual content of the data. The proposed work uses the ZK-STARK (Zero-Knowledge Scalable Transparent ARgument of Knowledge) Algorithm for transaction privacy in the organic jaggery supply chain. The paper emphasizes a detailed mathematical model, involving two key participants: the prover (food processor) and the verifier (distributor). The prover calculates the polynomial for the problem, its composition polynomial, and provides its Merkle proof to the verifier. The verifier conducts queries to confirm and validate the accuracy of the information. Using the fast reed-solomon interactive oracle proofs protocol, the proof is validated. It measures performance as proof generation and verification time, proof size, and throughput. Plans involve increasing the domain size of this algorithm, varying the polynomial interpolation, and evaluating its performance measures by integrating it into Blockchain.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
With the continuous development of blockchain technology, an increasing number of scholars have begun to consider the harm of data leakage during on-chain transactions and the requirement for privacy data protection. Zero-knowledge range proof, as a cryptographic technology, can perform legitimacy verification of data while hiding private data, effectively realizing the protection of private data on the blockchain, so it is increasingly used to protect blockchain privacy. The mainstream construction methods for range proofs can be mainly divided into two categories: n-ary decomposition and square decomposition. This paper introduces and analyzes the advantages and disadvantages of these construction methods in detail. Then, based on these two methods, a zero-knowledge range proof scheme based on multibit split square decomposition (ZKRPMSSD) is proposed, which requires no trusted third-party setting and can achieve range proofs for arbitrary ranges. The proposed ZKRPMSSD scheme processes the original data based on the multibit split idea, and the acquisition method of secret value components is optimized so that the acquisition of components does not depend on the scale of the original problem. Additionally, the algorithms for proof generation and verification in the ZKRPMSSD scheme are redesigned based on the \(\Sigma\) protocol and Pedersen commitments, effectively reducing the computational cost of the proof generation and verification process. Finally, typical n-ary decomposition and square decomposition zero-knowledge range proof construction schemes are taken for comparative analysis. Under 256-bit security and the same problem scale, experimental results indicate that ZKRPMSSD has advantages in proof and verification time costs.
Open access
Cryptography and Data Security
Digital Filter Design and Implementation
Advanced Steganography and Watermarking Techniques
Data security during transmission over public networks has become a key concern in an era of rapid digitization. Image data is especially vulnerable since it can be stored or transferred using public cloud services, making it open to illegal access, breaches, and eavesdropping. This work suggests a novel way to integrate blockchain technology with a Chaotic Tent map encryption scheme in order to overcome these issues. The outcome is a Blockchain driven Chaotic Tent Map Encryption Scheme (BCTMES) for secure picture transactions. The idea behind this strategy is to ensure an extra degree of security by fusing the distributed and immutable properties of blockchain technology with the intricate encryption offered by chaotic maps. To ensure that the image is transformed into a cipher form that is resistant to several types of attacks, the proposed BCTMES first encrypts it using the Chaotic Tent map encryption technique. The accompanying signed document is safely kept on the blockchain, and this encrypted image is subsequently uploaded to the cloud. The integrity and authenticity of the image are confirmed upon retrieval by utilizing blockchain's consensus mechanism, adding another layer of security against manipulation. Comprehensive performance evaluations show that BCTMES provides notable enhancements in important security parameters, such as entropy, correlation coefficient, key sensitivity, peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), and number of pixels change rate (NPCR). In addition to providing good defense against brute-force attacks, the high key size of [Formula: see text] further strengthens the system's resilience. To sum up, the BCTMES effectively addresses a number of prevalent risks to picture security and offers a complete solution that may be implemented in cloud-based settings where data integrity and privacy are crucial. This work suggests a promising path for further investigation and practical uses in secure image transmission.
Open access
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
In view of the problems of false property rights and difficulties in identity authentication in intellectual property transactions, an identity authentication model for intellectual property transactions based on an alliance chain is proposed. Firstly, the two-factor identity authentication model's roles, functions, and processes are constructed. Secondly, the two-factor authentication mechanism of ID password combined with physiological and property rights features is proposed, the identity identification generation method of fingerprint biometrics and intellectual property features is established, and the constraint compression strategy based on Poseidon hash is designed to reduce the workload of zero-knowledge proof algorithm and realize the consistency of property rights identity. Finally, the security and performance analysis of the authentication model is carried out, and the comparison and validation of related models are carried out, which shows that the model has good security and reliability.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid intellectual property rights violations and inappropriate misuse in software development. High-quality watermarks adhering to the detectability-fidelity-robustness tri-objective are limited due to codes' low-entropy nature. Watermark verification, however, often needs to reveal the signature and requires re-encoding new ones for code reuse, which potentially compromising the system's usability. To overcome these challenges, RoSeMary obtains high-quality watermarks by training the watermark insertion and extraction modules end-to-end to ensure (i) unaltered watermarked code functionality and (ii) enhanced detectability and robustness leveraging pre-trained CodeT5 as the insertion backbone to enlarge the code syntactic and variable rename transformation search space. In the deployment, RoSeMary uses zero-knowledge proofs for secure verification without revealing the underlying signatures. Extensive evaluations demonstrated RoSeMary achieves high detection accuracy while preserving the code functionality. RoSeMary is also robust against attacks and provides efficient secure watermark verification.
Federico Badaloni, Sebastian Holler, Chrysoula Oikonomou, Pedro Moreno-Sánchez · 5 authors
A smart contract is an interactive program that governs funds in the realm of a single cryptocurrency. Yet, the many existing cryptocurrencies have spurred the design of cross-chain applications that require interactions with multiple cryp-tocurrencies simultaneously. Currently, cross-chain applications are implemented as use-case-specific cryptographic protocols that serve as overlay to synchronize smart contract executions in the different cryptocurrencies. Hence, their design requires substantial expertise, as well as a security analysis in complex cryptographic frameworks. In this work, we present$BitML^{x}$, the first domain-specific language for cross-chain smart contracts, enabling interactions with several users that hold funds across multiple Bitcoin-like cryptocurrencies. We contribute a compiler to automatically translate a$BitML^{x}$contract into one contract per involved cryp-tocurrency and a user strategy that synchronizes the execution of these contracts. We prove that an honest user, who follows the prescribed strategy when interacting with the several contracts, ends up with at least as many funds as in the corresponding execution of the$BitML^{x}$contract. Last, but not least, we implement the$BitML^{x}$compiler and demonstrate its utility in the design of illustrative examples of cross-chain applications such as multi-chain donations or loans across different cryptocurrencies.
Open access
3 source records
cs.CR
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The rapid development of blockchain has significantly promoted research on zero-knowledge proofs (ZKPs), especially zero-knowledge succinct noninteractive arguments of knowledge (zk-SNARK). As is well known, protocol proof and verification time, as well as proof size, are the main obstacles that restrict the implementation of ZKPs in practical applications, so they have become the main concerns of researchers in recent years. This work achieves a new recursive zk-SNARK called GENES, which does not have a trusted setup and is secure under the standard discrete logarithm assumption. GENES is designed from the form of the rank-1 constraint system (R1CS) satisfiability problem. Recursive proof composition is achieved by merging multiple R1CS instances, which transforms the verification of numerous proofs into the verification of a single proof. Moreover, multi-helpers amortize proof commitments in this study, significantly reducing the computational pressure and time cost of proof generation. Compared with previous work, GENES effectively improves the proof time and verification time, but at the cost of larger proof sizes. We provide a blockchain Layer-1 scaling solution leveraging GENES to demonstrate its practicality.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Many blockchain-based crowdsourcing frameworks currently struggle to address the high costs associated with on-chain storage and computation effectively, and they lack a quality-driven incentive mechanism tailored to bounding box annotation scenarios. To address these challenges, this paper proposes CrowdBA: A low-cost, quality-driven crowdsourcing architecture. The CrowdBA utilizes the Ethereum public blockchain as the foundational architecture and develops corresponding smart contracts. First, by integrating Ethereum with the InterPlanetary File System (IPFS), storage and computation processes are shifted off-chain, effectively addressing the high costs associated with data storage and computation on public blockchains. Additionally, the CrowdBA introduces a Dynamic Intersection over the union-weighted bounding box fusion (DWBF) algorithm, which assigns dynamic weights based on IoU to infer true bounding boxes, thereby assessing each worker’s annotation quality. Annotation quality then serves as a key criterion for incentive distribution, ensuring fair and appropriate compensation for all contributors. Experimental results demonstrate that the operational costs of each smart contract function remain within reasonable limits; the off-chain storage and computation approach significantly reduces storage and computation expenses, and the DWBF algorithm shows marked improvements in accuracy and robustness over other bounding box fusion methods.
Open access
Blockchain Technology Applications and Security
Mobile Crowdsensing and Crowdsourcing
Advanced Steganography and Watermarking Techniques
In smart applications, streaming IoT data is essential to building trust in sustainable IoT solutions. However, most existing systems for storing and disseminating IoT data streams lack reliability, security, and transparency, primarily due to centralized architectures that create single points of failure. To address these limitations, this research introduces TraVel, a blockchain and transfer learning-based framework for secure IoT data management. TraVel leverages decentralized IPFS storage to handle large data volumes effectively, integrating with a private Ethereum blockchain to enhance data integrity and accessibility. In the proposed scheme, the smart home ([Formula: see text]) data is collected securely and accessed over the BC with a unique hash key generated on the IPFS for all the files. Self-executing Ethereum smart contracts enforce access control and verify data integrity, allowing only validated, non-malicious data to be stored. An adversarial domain adaptation (DA) learning model is employed to detect and filter malicious data before it enters the blockchain. TraVel's performance is evaluated on blockchain parameters, with simulations conducted on REMIX IDE and InterPlanetary File System (IPFS), demonstrating its reliability and scalability for secure IoT data dissemination.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
R. Vijay Anand, G. Magesh, I. Alagiri, Madala Guru Brahmam · 9 authors
With the advancement of this digital era and the emergence of DApps and Blockchain, secure, robust and transparent network transaction has become invaluable today. These traditional methods of securing the transactions and maintaining transparency have encountered many challenges. It includes some such issues as follows: data privacy, centralized vulnerability, inefficiency in fraud detection and much more. To that effect, and to address such limitations, this paper provides a blockchain technology framework that is driven by advanced machine learning techniques, which will enhance security and transparency throughout the network of transactions. We begin with a design framework based on Federated Learning for Blockchain Integration where distributed datasets across blockchain nodes contribute to a global machine learning model but do not share raw data samples. Different nodes learn their own models. After that, these local models are aggregated towards a common, global model using secure aggregation methods, which makes sure that there is nozza of data privacy and hence, in the process making sure that more accurate models can be obtained due to diversified data sets. With LSTMs Autoencoders, more excellent security protocols are created for anomaly detection and fraud. So, by training the autoencoder on normal transaction data, the system can alert transactions with high reconstruction errors, meaning real-time anomalies. This proactive detection of anomalies reduces fraudulent activities significantly as most of the threats are recognized early. To this end, this paper proposes Smart Contract-based Model Management for machine learning models in a decentralized environment. Smart contracts are responsible for the submission, validation, and execution of the locally updated models in a decentralized fashion such that the management process is transparent and tamper resistant. Integrity and authenticity requirements are fulfilled by enforcing consensus mechanisms. Privacy in Machine Learning is guaranteed through Differential Privacy and Homomorphic Encryption. Differential privacy techniques, so as to ensure individual transaction data privacy in the updates of the local model before aggregation. In homomorphic encryption, computations are made in the encrypted form so when forming privacy preserving global model, privacy is preserved. The Real-time analysis of the transactions can be done with CNNs to detect fraud. Streaming transaction data is analyzed by CNNs leveraging the privacy-preserving global model and producing immediate alerts and actions for detected fraud. This real timing makes the network even more reliable and trustworthy. Our proposed framework is effective according to the interim outcomes where the aggregation of local models occurred without data leakage, detected anomalies very efficiently, managed models very transparently, with privacy of data at a very high level, and easily detected fraudulent transactions. The work presented here provides a great boost to send secure and very easily transparent transactions across the network, and thus resulted in enhanced network trust and decentralization.
Open access
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
The cross-chain identity authentication method based on relay chains provides a promising solution to the issues brought by the centralized notary mechanism. Nonetheless, it continues to encounter numerous challenges regarding data privacy, security, and issues of heterogeneity. For example, there is a concern regarding the protection of identity information during the cross-chain authentication process, and the incompatibility of cryptographic components across different blockchains during cross-chain transactions. We design and propose a cross-chain identity privacy protection method based on relay chains to address these issues. In this method, the decentralized nature of relay chains ensures that the cross-chain authentication process is not subject to subjective manipulation, guaranteeing the authenticity and reliability of the data. Regarding the compatibility issue, we unify the user keys according to the identity manager organization, storing them on the relay chain and eliminating the need for users to configure identical key systems. Additionally, to comply with General Data Protection Regulation (GDPR) principles, we store the user keys from the relay chain in distributed servers using the InterPlanetary File System (IPFS). To address privacy concerns, we enable pseudonym updates based on the user’s public key during cross-chain transactions. This method ensures full compatibility while protecting user privacy. Moreover, we introduce Zero-Knowledge Proof (ZKP) technology, ensuring that audit nodes cannot trace the user’s identity information with malicious intent. Our method offers compatibility while ensuring unlinkability and anonymity through thorough security analysis. More importantly, comparative analysis and experimental results show that our proposed method achieves lower computational cost, reduced storage cost, lower latency, and higher throughput. Therefore, our method demonstrates superior security and performance in cross-chain privacy protection.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Using blockchain technology and smart transportation gadgets, this paper proposes the next-generation VANET system. While VANET has many advantages, it must first be improved in areas such as security and privacy if it is to be widely adopted. Nearby vehicles periodically exchange events providing their unique identifiers, locations, speeds, and statuses. Using key cryptography, it must verify the legitimacy of each car in the network before allowing it to participate, and it must take the blame for any malicious activity that occurs on the road. Due to the fast speeds of vehicles, limited communication capacity, and delay sensitive applications, traditional centralised security solutions are not applicable in VANET. The purpose of this study is to imagine a new blockchain protocol for secure event transactions in a virtual autonomous network (VANET). Blockchain is a distributed ledger system that facilitates resource tracking and administration without the need for a central authority. Therefore, a blockchain-based solution that offers transparency, tamper resistance, and immutability is preferable in a VANET scenario.
Open access
Blockchain Technology Applications and Security
Vehicular Ad Hoc Networks (VANETs)
Advanced Steganography and Watermarking Techniques