In electronic healthcare, patient medical imaging data is critical for remote diagnostic procedures. The increasing demand to harness the potential of these medical images necessitates their secure sharing among various entities, including hospitals, medical institutions, and insurance companies. However, third-party access and possible manipulation make it challenging to maintain the ownership and integrity of this data. This study introduces a novel approach that combines compression, digital watermarking, symmetric encryption, and blockchain technology to protect medical images from unauthorized third-party interventions. Using the Discrete Wavelet Transform, our proposed technique embeds a compressed watermark into the host image. Specifically, the watermark is encoded into vectors and inserted into the second-level approximation, i.e., the Low-Low of the image using the Least Significant Bit, producing a watermarked image. The watermarked data is encrypted and stored on a blockchain to further safeguard these images’ integrity. This multi-layer security framework not only preserves the integrity and confidentiality of the data but also facilitates transparent and secure sharing among stakeholders. The proposed method achieves a peak signal-to-noise ratio of 63.24dB and a structural similarity index of 1. These results demonstrate the robustness of our solution in protecting and exchanging medical images within the digital healthcare ecosystem, positioning it as an advanced and reliable option for secure data management.
Open access
Advanced Steganography and Watermarking Techniques
Muhammad Ahmad Nawaz Ul Ghani, She Kun, Muhammad Arslan Rauf, Shumaila Khan · 7 authors
In recent years, the extensive use of facial recognition technology has raised concerns about data privacy and security for various applications, such as improving security and streamlining attendance systems and smartphone access. In this study, a blockchain-based decentralized facial recognition system (DFRS) that has been designed to overcome the complexities of technology. The DFRS takes a trailblazing approach, focusing on finding a critical balance between the benefits of facial recognition and the protection of individuals' private rights in an era of increasing monitoring. First, the facial traits are segmented into separate clusters which are maintained by the specialized node that maintains the data privacy and security. After that, the data obfuscation is done by using generative adversarial networks. To ensure the security and authenticity of the data, the facial data is encoded and stored in the blockchain. The proposed system achieves significant results on the CelebA dataset, which shows the effectiveness of the proposed approach. The proposed model has demonstrated enhanced efficacy over existing methods, attaining 99.80% accuracy on the dataset. The study's results emphasize the system's efficacy, especially in biometrics and privacy-focused applications, demonstrating outstanding precision and efficiency during its implementation. This research provides a complete and novel solution for secure facial recognition and data security for privacy protection.
Open access
Biometric Identification and Security
Face recognition and analysis
Advanced Steganography and Watermarking Techniques
Email serves as the primary mode of communication in today’s interconnected digital world, encompassing business, education, and interpersonal relationships. However, email’s reliance on shared media makes it susceptible to interception and misuse of confidential data. Pretty Good Privacy (PGP) protects the privacy of email contents to address this problem. While PGP offers encryption, its key sharing has weaknesses. Blockchain technology is characterized by its immutability feature. Once information is stored in the blockchain, altering it becomes extremely difficult. This characteristic serves as a valuable defense against weaknesses in the PGP key sharing system. Furthermore, the implementation of smart contracts eliminates the need for a Man-in-the-Middle when sharing keys, thereby improving the security of key sharing and fostering trust among individuals. Blockchain and smart contracts improve security, but privacy remains a concern. To further bolster privacy protection, in this paper we propose the integration of Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARKs) and blockchain into PGP key sharing mechanism. zk-SNARKs enable efficient verification of encrypted data without revealing sensitive information, thus preventing exposure of user privacy. Additionally, we employ Elliptic Curve Cryptography (ECC) in order to guarantee the confidentiality of the PGP key. Through this holistic integration, the security of the PGP key is enhanced, ensuring both confidentiality and integrity while safeguarding user privacy. Furthermore, gas consumption and transaction costs were evaluated with and without zk-SNARKs. The results demonstrate that the proposed mechanism minimizes gas consumption and transaction costs.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Covert channels in blockchain networks achieve undetectable and reliable communication, while transactions incorporating secret data are perpetually stored on the chain, thereby leaving the secret data continuously susceptible to extraction. MTMM (IEEE Transactions on Computers 2023) is a state-of-the-art blockchain-based covert channel. It utilizes Bitcoin network traffic that will not be recorded on the chain to embed data, thus mitigating the above issues. However, we identify a distinctive pattern in MTMM, based on which we propose a comparison attack to accurately detect MTMM traffic. To defend against the attack, we present an improvement named ORIM, which exploits the permutation of transaction hashes within inventory messages to transmit secret data. ORIM leverages a pseudo-random function to obscure the transaction hashes involved in the permutation to ensure unobservability. The obfuscated values, rather than the original transaction hashes, are utilized to encode the confidential data. Furthermore, we introduce a variable-length encoding scheme predicated on complete binary trees. This scheme considerably amplifies the bandwidth and facilitates efficient encoding and decoding of secret data. Experimental results indicate that ORIM maintains unobservability and that ORIM’s bandwidth is approximately$3.7\times $of MTMM.
Advanced Steganography and Watermarking Techniques
Dharminder Chaudhary, P. Santhi, M. S. P. Durgarao, A Padmavathi · 6 authors
Truck platooning uses networking technology and automated driving support systems to join multiple trucks in a group. When these vehicles interact for particular journey stages, such as on highways, they autonomously maintain a predefined, tight spacing among themselves. Platooning improves transportation by making better use of highways, delivering cargo faster, and minimizing congestion in traffic. Therefore, safety and platooning are two important attributes of an intelligent truck system. This paper discusses a quantum-safe blockchain-empowered authentication mechanism for autonomous truck platooning. The proposed idea is to use blockchain to combine multiple nodes and ensure authenticity with the help of an aggregation technique. The proposed design ensures authenticity to the system due to hard assumptions:1) Learning With Error (LWE) and 2) Short Integer Solution (SIS) on random module generated lattice. This paper uses operations over module lattices to be more efficient than general lattices. We can perform operations on module lattices with the help of fast algorithms for polynomial arithmetic.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Archana Chhabra, Rahul Saha, Gulshan Kumar, Tai-hoon Kim
Blockchain networks provide a reliable and secure mode of communication due to their decentralized and distributed nature. The emergence of amalgamated blockchain-based internet-of-things (IoT) systems has generated a huge amount of data to be online. Though blockchains show potential for ensuring transparency, traceability, and immutable records, the privacy of online data in blockchains becomes a question. The privacy of blockchain transactions is at stake as various privacy breaching methods are used by attackers such as linking the transactions, deanonymization, etc. However, the benefits of blockchain make the technology a dominator in the present and future technological paradigms. The other side of the coin deals with privacy information retrieval (PIR), which is necessary to retrieve private information from servers without much revealing. However, the conjunction of blockchain privacy and PIR is very critical and an important aspect of blockchain solutions. In this present survey, we pioneer in analyzing the privacy factors of existing blockchain solutions. We discuss the privacy parameters and important privacy enhancement techniques for blockchains comprehensively. We show the applicability of privacy in various domains including e-commerce, supply chain, healthcare, and IoT. We also discuss PIR-related issues and solutions in the existing literature. We highlight open research problems and discuss the benefits of collaborating with PIR and blockchain systems to improve privacy in blockchains. Our survey is beneficial for academia and industries to be aware of the present status of privacy solutions in blockchains and to address the identified loopholes to make the systems better.
Open access
Blockchain Technology Applications and Security
Privacy, Security, and Data Protection
Advanced Steganography and Watermarking Techniques
Minjae Seo, Jaehan Kim, Myoungsung You, Seungwon Shin · 5 authors
Blockchain technology has ushered in a transformative paradigm of decentralized and transparent systems, offering innovative solutions across diverse sectors. While these systems strive for unparalleled transparency and trustlessness in a fully distributed framework, permissionless blockchains, such as Bitcoin and Ethereum, encounter vulnerabilities due to their intrinsically public nature. Addressing these vulnerabilities, the emergence of permissioned blockchains presents a fortified alternative, incorporating rigorous access controls and authentication protocols to ensure participation exclusivity and transaction confidentiality. Nevertheless, a keen observation reveals that, despite encryption, the operational traffic within these blockchains manifests distinct time-series patterns and operational relations during sensitive data exchanges. Such patterns hold the potential to inadvertently expose critical details about the network, encompassing its topology and the operational dependencies among nodes. In light of this revelation, we introduce a pioneering blockchain fingerprinting mechanism, denoted as gShock. This system meticulously analyzes periodic patterns and the context of operational relations from the collected blockchain network traffic. It employs a Graph Neural Network (GNN)-based model, adept at capturing the intricate characteristics innate to specialized blockchain operations. Through empirical experiments conducted in a realistic permissioned blockchain environment, comprising various nodes, we ascertain that gShock demonstrates a remarkable proficiency in classifying blockchain operational traffic with an F1-score of$\geq 96$% and identifying individual dependencies with a macro F1-score of$\geq 93$%.
Open access
Advanced Steganography and Watermarking Techniques
Blockchain-based censorship-resistant systems enable the user to access the blocked content through a covert channel while avoiding a suspicious network connection between the user and the proxy. However, state-of-the-art blockchain-based censorship-resistant schemes cannot satisfy both low communication fees and unobservability, and their method of identifying transactions with covert data may inadvertently expose the covert channel. In this paper, we present Hades, a blockchain-based covert channel framework that aims to circumvent censorship. Hades allows users to encode covert data as a transaction field, and identify transactions with covert data by using another transaction field as a label. We also present the security model for Hades, which defines the unobservability of Hades as the indistinguishability of transactions with covert data from normal transactions. We further propose two cost-friendly and unobservable instantiations of Hades: the basic RDSAC and the improved DDSAC. RDSAC uses private keys to encode covert data and utilizes random factors in the signing process as labels, while incurring a communication delay. DDSAC avoids the delay by encoding covert data into random factors and sampling a transaction amount from normal transactions as the label. We implement a prototype system of Hades and evaluate its performance. Experiment results show that our Hades prototype is unobservable, robust, and efficient. RDSAC and DDSAC can identify 1,654 transactions in 6.054 seconds and 0.071 seconds, respectively. Hades supports 1KB data transfer at $0.44 on the Bitcoin mainnet and cost-free data transfer on the Bitcoin testnet.
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
In today's world of internet marketing product review plays a crucial role. Often E-Commerce companies are accused of manipulating with the data and it suffers from biasing. Biasing leads to wrong customer's view creation thereby prediction for a top rating product fails. This study shows how crowd annotation prevents this biasness and thereby design a smart contract which ultimately will help to eliminate the data manipulation. The smart contract is deployed and tested to see if data can be saved in the run time storage memory regions of the Ethereum blockchain, and the test results are positive. In future this will help to get the unbiased data and better machine learning results, which will ultimately be beneficial for the economy.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cryptocurrency tracker is an online platform that provides a userfriendly experience. Users get a simple and userfriendly experien ce through the user interface. Users can sign into their account with Gmail or a mobile number for easy access to their account. U sers can track prices of different cryptocurrencies and view currency charts. Using this user interface, users can find prices and ot her relevant information about cryptocurrencies. The app helps users to create watchlists and we can track prices. We can set alerts for cryptocurrency prices. We can customize notifications and help understand new cryptocurrency trends. Users can easily find various cryptocurrencies and track future crypt currency trends. It helps users invest in new popular cryptocurrencies that will be more useful to them in the future. Overall, the Cryptocurrency Tracker web app is a valuable tool for anyone looking to invest, trade, or just keep an eye on the cryptocurrency market. It provides realtime data and insights that can help users make informed investment decisions and stay abrea st of the latest industry trends and developments.
A. Sasikumar, Logesh Ravi, Malathi Devarajan, A. Selvalakshmi · 8 authors
The edge devices will produce enormous quantities of data daily as the Industrial Internet of Things (IIoT) expands in scope. Still, most IIoT data is stored in data centers, making it challenging to transfer data between domains safely. Smart logistic products have dramatically changed due to the prevalence of decentralized edge computing and blockchain in the industry sector. To address the need to exchange data between logistics networks, we proposed a novel decentralized hierarchical attribute-based encryption (HABE) scheme combining edge computing and blockchain. To begin, we offer an IoT data encryption strategy in which edge devices can send data to a nearby cloud network for data processing while maintaining privacy. In addition, we developed a blockchain-integrated data-sharing scheme that makes it possible for users to share data via the use of edge and cloud storage. In particular, an IoT device incorporates an encryption-based authentication system to verify users’ access rights at the network’s periphery in a decentralized manner. Using HABE, we provide a blockchain-integrated architecture for the IoT that protects user privacy. The suggested design utilizes the edge and cloud network paradigms and HABE to maintain privacy and works well with smart logistics applications. The authentication time of the proposed model is reduced by 1.5 times compared with the centralized model. The analyses and experimental findings show that the proposed blockchain-integrated edge computing architecture is better than the existing schemes in terms of data sharing, data privacy, and security.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
<abstract> <p>This paper proposes a deterministic nonce generation technique to address the catastrophic issues associated with nonce reuse in message signing and to enhance the efficiency of Schnorr multi-signature schemes. Additionally, this research aims to reduce computational complexity and bandwidth requirements in digital and multi-signature schemes while maintaining robust security against common attacks. The proposed method was inspired by the EdDSA approach. The methodology includes a comprehensive mathematical analysis of digital signature algorithms and a rigorous examination of their vulnerabilities to well-known cryptographic attacks. This analysis evaluates the effectiveness and robustness of the proposed nonce generation technique within the frameworks of the Schnorr digital signature and the two-round MuSig schemes. Techniques and tools employed in this research involve deterministically generating nonces by hashing the private key and subsequently hashing the result with the message. Furthermore, it is proposed to exclude the public nonce R from the challenge calculations and to allow signers to directly prove possession of their secret keys through the aggregated public key, thereby eliminating the need for non-interactive zero-knowledge (NIZK) proofs. The findings demonstrate significant reductions in computational complexity and operational requirements, thereby improving bandwidth efficiency and making this method well-suited for resource-constrained devices. The approach also exhibits strong resistance to various attacks, including nonce reuse, key cancellation, rogue keys, and virtual machine rewinding.</p> </abstract>
Open access
Handwritten Text Recognition Techniques
Advanced Steganography and Watermarking Techniques
Smart contracts on the Ethereum blockchain have revolutionized decentralized applications (dApps) but remain vulnerable to various security threats. In response, this paper introduces EthereumGuard, a pioneering Embedded Intrusion Detection System (EIDS) designed to bolster the security of smart contracts. By embedding intrusion detection mechanisms directly within contract code, EthereumGuard proactively monitors and identifies anomalous behavior, enabling swift responses to potential attacks. Leveraging blockchain transparency and deterministic execution, EthereumGuard offers robust protection against a spectrum of threats, including reentrancy and denial-of-service attacks.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques