Blockchain is a promising infrastructure for the internet and digital economy, but it has serious scalability problems, that is, long block synchronization time and high storage cost. Conventional coarse-grained data deduplication schemes (block or file level) are proved to be ineffective on improving the scalability of blockchains. Based on comprehensive analysis on typical blockchain workloads, we propose two new locality concepts (economic and argument locality) and a novel fine-grained data deduplication scheme (transaction level) named Alias-Chain. Specifically, Alias-Chain replaces frequently used data, for example, smart contract arguments, with much shorter aliases to reduce the block sizes, which results in both shorter synchronization time and lower storage cost. Furthermore, to solve the potential consistency issue in Alias-Chain, we propose two complementary techniques: one is generating aliases from history blocks with high consistency, and the other is speeding up the generation of aliases via a specific algorithm. Our simulation results show: (1) the average transfer and SC-call transaction (a transaction used to call the smart contracts in the blockchain) sizes can be significantly reduced by up to 11.03% and 79.44% in native Ethereum, and up to 39.29% and 81.84% in Ethereum optimized by state-of-the-art techniques; and (2) the two complementary techniques well address the inconsistency risk with very limited impact on the benefit of Alias-Chain. Prototyping-based experiments are further conducted on a testbed consisting of up to 3200 miners. The results demonstrate the effectiveness and efficiency of Alias-Chain on reducing block synchronization time and storage cost under typical real-world workloads.
Zero Knowledge Proof (ZKP) is a very effective method of preserving privacy as it hides the most confidential information throughout the transaction. In this paper, we present a security and privacy-preserving approach for blockchain that relies on account and multi-data asset models using the Zero Knowledge Proof (ZKP) mechanism. We provide options for transferring data assets and detecting duplicate expenditures, and we also develop transaction structures, anonymised addresses and anonymised metadata for the data assets. To create and validate the ZKP, we use the zk-SNARKs algorithm and specify validation criteria for masked transactions, and finally conduct experimental tests to validate it. Creating better algorithms for ZKP will be the focus of our future efforts.
P. Rajasekar, K. Kalaiselvi, Raju Shanmugam, S. Tamilselvan · 5 authors
Cloud computing caused the paradigm shift in business performance, from scalability to flexibility as well as affordability in the management of computing resources. Nevertheless, ensuring security of the data remains a key issue in the cloud due to the centralized interactions between service provider and a single vulnerability in the network can put rest of the data at risk. Consequently, the application of DLT, in addition to other solutions such as DLT, demonstrates a big step towards the improvement of cloud security frameworks. This article focuses on the implementation of DLT for data protection applications that are based on a solid dataset and decentralized security procedures in cloud environments. DLT utilization, like blockchain, provides an organization with integrity data, transparency, and fitness to counter cyber threats. Architecture stacks up sponsors such as cloud providers, users, and applications and DLT is responsible for the security of the transaction and the security policy enforcement. Customers use those services via desktop based application with transparent security policy arisen from DLT. Moreover, DLT also does identity management in the way that is decentralized, data sharing in the manner that it is secure, and the compliance to regulatory frameworks, which in addition reduces the trust and privacy risks in the cloud ecosystems. The proposed architecture is genuinely a big jump toward protecting cloud security from centralized control interruptions and thus, enhancing resilience and stability in cloud computing.
Blockchain full nodes are pivotal for transaction availability, as they store the entire ledger, but verifying their storage integrity faces challenges from malicious remote storage attacks such as Sybil, outsourcing, and generation attacks. However, there is no suitable proof-of-storage solution for blockchain full nodes to ensure a healthy number of replicas of the ledger. Existing proof-of-storage solutions are designed for general-purpose settings where a data owner uses secret information to verify storage, rendering them unsuitable for blockchain where proof-of-storage must be fast, publicly verifiable, and data owner-agnostic. This paper introduces a decentralised and quantum-resistant solution named Non-interactive Practical Proof of Storage (nPPoS) with an asymmetric encoding and decoding scheme, for fast and secure PoStorage, and Zero-Knowledge Scalable Transparent Arguments of Knowledge (zk-STARKs), for public variability in blockchain full nodes. The algorithm with asymmetric times for encoding and decoding creates unique block replicas and corresponding proofs for each storage node to mitigate malicious remote attacks and minimise performance degradation. The intentional resource-intensive encoding deters attacks, while faster decoding minimises performance overhead. Through zk-STARKs, nPPoS achieves public verifiability enabling one-to-many verification for scalability, quantum resistance and decentralisation. It also introduces a two-phase randomisation technique and a time-weighted trustworthiness measurement for scalability and adaptability.
Andrew Jeffery, Julien Maffre, Heidi Howard, Richard Mortier
Software services are increasingly migrating to the cloud, requiring trust in actors with direct access to the hardware, software and data comprising the service. A distributed datastore storing critical data sits at the core of many services; a prime example being etcd in Kubernetes. Trusted execution environments can secure this data from cloud providers during execution, but it is complex to build trustworthy data storage systems using such mechanisms. We present the design and evaluation of the Ledger-backed Secure Key-Value datastore (LSKV), a distributed datastore that provides an etcd-like API but can use trusted execution mechanisms to keep cloud providers outside the trust boundary. LSKV provides a path to transition traditional systems towards confidential execution, provides competitive performance compared to etcd, and helps clients to gain trust in intermediary services. LSKV forms a foundational core, lowering the barriers to building more trustworthy systems.
Manav Pankaj Jariwala, Mohammad S. Obaidat, Mohammad Wazid, Amit Kumar Mishra · 5 authors
A decentralized file storage system is a system for storing the data. The files are stored across a distributed network of nodes. It does not rely on a centralized server. Each node in the network maintains a copy of the data. In this system, files are broken into smaller pieces and then distributed over multiple nodes. It improves redundancy and makes the system resilient. It leverages over peer-to-peer (P2P) networking protocols. It also utilizes blockchain technology to provide secure and efficient file storage. A decentralized file storage system has various applications, i.e., content distribution, file sharing and collaboration, decentralized applications (dApps), content deliv-ery networks (CDNs), personal data ownership and data backup and recovery. Though it is used in various applications, at the same time, it also has several issues, including data secrecy and data integrity. Therefore, in this paper, we propose a blockchain-based decentralized scheme for a secure file storage system. The proposed scheme offers a robust solution for addressing the security issues that are associated with centralized file storage systems. It is accomplished by utilizing the Ethereum blockchain, solidity smart contracts, Metamask, React.js, CSS, and Ethers.js. The evaluation of the implemented system has shown that it is effective in ensuring safe and decentralized file storage.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Blockchain interoperability still poses a significant challenge to the practical applicability of Distributed Ledger Technologies (DLTs). However, several cross-blockchain protocols already exist, allowing, e.g., the transfer of tokens between heterogenous blockchains. Unfortunately, executing these protocols is expensive and often does not consider eventual inconsistencies, which can occur if the involved blockchains fork.Therefore, we propose a cross-blockchain token transfer protocol operating on Layer 2 to decrease transaction costs and enable the ability to revert transactions. The protocol uses the approach of zk rollups to move storage and computation off-chain and only stores state commitments on Layer 1. Hence, the states of the involved token contracts can quickly revert to an older state root to account for possible forks of the involved blockchains and ensure consistency.
D. Dhinakaran, D. Selvaraj, N. Dharini, S. Edwin Raja · 5 authors
The intersection of cloud computing, blockchain technology, and the impending era of quantum computing presents a critical juncture for data security. This research addresses the escalating vulnerabilities by proposing a comprehensive framework that integrates Quantum Key Distribution (QKD), CRYSTALS Kyber, and Zero-Knowledge Proofs (ZKPs) for securing data in cloud-based blockchain systems. The primary objective is to fortify data against quantum threats through the implementation of QKD, a quantum-safe cryptographic protocol. We leverage the lattice-based cryptographic mechanism, CRYSTALS Kyber, known for its resilience against quantum attacks. Additionally, ZKPs are introduced to enhance data privacy and verification processes within the cloud and blockchain environment. A significant focus of this research is the performance evaluation of the proposed framework. Rigorous analyses encompass encryption and decryption processes, quantum key generation rates, and overall system efficiency. Practical implications are scrutinized, considering factors such as file size, response time, and computational overhead. The evaluation sheds light on the framework's viability in real-world cloud environments, emphasizing its efficiency in mitigating quantum threats. The findings contribute a robust quantum-safe and ZKP-integrated security framework tailored for cloud-based blockchain storage. By addressing critical gaps in theoretical advancements, this research offers practical insights for organizations seeking to secure their data against quantum threats. The framework's efficiency and scalability underscore its practical feasibility, serving as a guide for implementing enhanced data security in the evolving landscape of quantum computing and blockchain integration within cloud environments.
Chen Chang Lew, Christof Ferreira Torres, Shweta Shinde, Marcus Brandenburger
Blockchain technology offers decentralized security but fails to ensure data confidentiality due to its inherent data replication across all network nodes. To address these confidentiality challenges, integrating blockchains with Trusted Execution Environments (TEEs), such as Intel SGX, offers a viable solution. This approach, by encrypting all data outside the SGX enclave and making them unrecognizable to untrusted network nodes, ensures secure processing of data and computations within TEEs. Fabric Private Chaincode (FPC), an enhancement of Hyperledger Fabric, demonstrates this integration by securing smart contracts in enclaves, thereby enhancing confidentiality. However, FPC's reliance on states stored on the blockchain introduces vulnerabilities, especially to rollback attacks. This work provides a detailed analysis of rollback attacks in FPC, evaluates existing protection mechanisms, and proposes a solution: a Merkle Tree approach implemented in an FPC application named Secret Keeper. Through experimental validation, this solution shows significant security enhancements against rollback attacks within FPC contexts.
The sharing of private information is a daunting, multifaceted, and expensive undertaking. Furthermore, identity management is an additional challenge that poses significant technological, operational, and legal obstacles. Present solutions and their accompanying infrastructures rely on centralized models that are susceptible to hacking and can hinder data control by the rightful owner. Consequently, blockchain technology has generated interest in the fields of identity and access control. This technology is viewed as a potential solution due to its ability to offer decentralization, transparency, provenance, security, and privacy benefits. Nevertheless, a completely decentralized and private solution that enables data owners to control their private data has yet to be presented. In this research, we introduce DeAuth, a novel decentralized, authentication and authorization scheme for secure private data transfer. DeAuth combines blockchain, smart-contracts, decentralized identity, and distributed peer-to-peer (P2P) storage to give users more control of their private data, and permissioning power to share without centralized services. For this scheme, identity is proven using decentralized identifiers and verifiable credentials, while authorization to share data is performed using the blockchain. A prototype was developed using the Ethereum Blockchain and the InterPlanetary Files System, a P2P file sharing protocol. We evaluated DeAuth through a use-case study and metrics such as security, performance, and cost. Our findings indicate DeAuth to be viable alternative to using centralized services; however, the underlying technologies are still in its infancies and require more testing before it can supplant traditional services.
Introduction: The Identity of a user in digital world is an important factor for an individual. Identity management has been handled by various models which, over the period of time have been prone various security breaches. The foremost integral part of any identity model is the centralized storage, access of data. Considering this, in recent years, there has been evolution from centralization to de-centralization of Identity management. With respect to this new aspect, this paper proposes a solution to the centralized management problems, as a decentralized Identity Management System. The said approach utilizes Ethereum blockchain, IPFS, both supporting distributed data accessibility and data storage respectively. This paper also sheds light on the W3C specification of DID (De-centralized Identifier) which supports the Self-Sovereign Identity principles of Identity Management and are vital for de-centralization of Identity Management
Intention adoption represents a migration from an imperative to a declarative paradigm, which is expected to significantly improve the user experience in blockchain. While the development of account abstraction has expanded the range of possibilities for intent expression, the architecture for intent-centric collaboration and coordination remains underdeveloped. Existing works depend on trusted centralized entities and employ broadcasts to the network to disseminate user intent, risking single points of failure and privacy leakage. In addition, no standard intent architecture has been proposed. In this paper, we propose a novel decentralized privacy-preserving optimizer architecture for executing intents on the EVM blockchain. We first propose standard intent structures and zero-knowledge intent structures. Our architecture allows users to transform raw intent structures into zero-knowledge intent structures and send them to a set of trusted optimizers. The optimizers can optimize and execute the intents without revealing the content of the intents. We use zero-knowledge proof and public-key encryption to ensure the privacy and correctness of the intents, and smart contracts to ensure the security and verifiability of the execution. We also design a quantization function to evaluate and compare solutions from different optimizers. We analyze the security and performance of our architecture and show that it can achieve privacy, efficiency, and scalability of intent execution on the EVM blockchain.
Decentralized applications (Dapps), based on smart contract technology, have been increasingly applied in various fields such as healthcare, industrial IoT, agriculture, financial services, supply chain management, and insurance. In certain complex business scenarios, blockchain may require machine learning models to assist contract business. However, on-chain computations are often costly and slow, and there are limitations on contract size. Due to the transparency of on-chain data, there are also privacy concerns regarding user data during model training and inference. To address these challenges, we propose a trusted off-chain machine learning solution that integrates ZK-SNARK and Oracle technologies. Following the principle of “off-chain computation, on-chain verification”,our approach leverages ZK-SNARK to delegate the computation tasks of machine learning models to a trusted environment under the Oracle off-chain server. This solution significantly reduces the computational costs of the blockchain. User data and models are executed off-chain, effectively safeguarding user privacy. The execution results generate zero-knowledge proofs returned for on-chain verification. We have implemented TOMLS-ZKSO and conducted relevant experiments on insurance contract business on the Chainmaker. Experimental results demonstrate the effectiveness of our approach, with model proof generation taking approximately 0.4 seconds and Dapp response time around 0.52 seconds.
In the context of the rapid development of Internet of Things (IoT) technology and the extensive proliferation of the global Internet, the authenticity of data has become a focal point of societal demand. It plays a decisive role in enhancing the quality of decision-making and operational efficiency. However, the storage and authenticity verification of large-scale IoT real-time data present unprecedented technical challenges. Faced with the inherent data security risks of traditional centralized cloud storage, blockchain technology reveals its unique potential for solutions with its inherent immutability and decentralization. Nevertheless, current blockchain-based data storage solutions are still restricted by high costs and inefficiency. To address these challenges, this paper innovatively proposes the BI-TSFID framework, which leverages the benefits of Ethereum and IPFS and optimizes the Merkle Tree structure and verification mechanisms. The BI-TSFID framework adopts a strategy of on-chain data summary storage and off-chain computation. This approach provides IoT with efficient and reliable data storage, reduces operational costs, and simplifies the verification process. This research has improved the data computation efficiency by refining the structure of the Merkle Tree and analyzed its optimal branch number. Additionally, the study introduces a sampling-based data integrity verification method that significantly reduces resource consumption during the verification process. Experimental results show that the solutions proposed in this paper effectively enhance the efficiency and security of IoT data management and provide valuable guidance for the theory and practice of real-time data storage and verification, further promoting the development and innovation in the related technological fields.
With the development of Internet of Things technology, intelligent door lock devices are widely used in the field of house leasing. In the traditional housing leasing scenario, problems of door lock information disclosure, tenant privacy disclosure and rental contract disputes frequently occur, and the security, fairness and auditability of the housing leasing transaction cannot be guaranteed. To solve the above problems, a blockchain-based proxy re-encryption scheme with conditional privacy protection and auditability is proposed. The scheme implements fine-grained access control of door lock data based on attribute encryption technology with policy hiding, and uses proxy re-encryption technology to achieve auditable supervision of door lock information transactions. Homomorphic encryption technology and zero-knowledge proof technology are introduced to ensure the confidentiality of housing rent information and the fairness of rent payment. To construct a decentralized housing lease transaction architecture, the scheme realizes the efficient collaboration between the door lock data ciphertext stored under the chain and the key information ciphertext on the chain based on the blockchain and InterPlanetary File System. Finally, the security proof and computing performance analysis of the proposed scheme are carried out. The results show that the scheme can resist the chosen plaintext attack and has low computational cost.
The use of digital certificates is crucial for verifying the authenticity of various credentials in our digital age.However, traditional digital certificate systems suffer from centralization, vulnerability to tampering, and the risk of loss.This paper presents an approach to issuing and managing certificates as Non-Fungible Tokens (NFTs) on the Ethereum blockchain, ensuring their immutability and perpetual existence.The proposed system aims to overcome the limitations of traditional methods by utilizing decentralized storage through the InterPlanetary File System (IPFS) and implementing a robust incentive mechanism for voting and Proof of Stake; the goal is to achieve true permanence and enhanced security for digital certificates.A first phase of a smart contract and front-end interface was achieved, to preserve diplomas and provide a reliable method for verifying their authenticity for employers and other stakeholders.This paper is part of an ongoing effort to develop a robust system, create a prototype to validate the perpetuity assumption, and propose improvements for a global, enduring repository of certificates.
The widespread developments of blockchain bring about diverse blockchain networks, where each stands as an isolated data island and operates independently. The need of interoperability and interconnection among kinds of blockchains inspires the emergence of the cross-chain technology. It enables the asset transfer and information interaction via crosschain transactions. The previous cross-chain transaction systems are almost implemented over the plain data, fully exposing the transaction-associated information. Cryptographic techniques such as non-interactive zero-knowledge proof can be used to protect the transaction privacy, while its high complexity incurs heavy running cost. The privacy of cross-chain transactions is still a challenging issue. In this paper, we propose a lightweight crosschain transaction privacy-preserving method named PTCross. It embeds Bulletproofs and Pedersen commitment to hide crosschain transaction information, meanwhile combining off-chain computation and on-chain contract verification. We instantiate and implement PTCross between ChainMaker and Bitcoin. The experimental results show that the proposed PTCross achieves both lightweight performance and strong privacy.
M. Sharmitha, M. P. Theeraj, P. V. Ranjith, S. Anitha
Individual health records (IHRs) hold paramount significance for individuals, serving as vital tools for the management and oversight of their medical data. Through electronic platforms, IHRs empower patients by granting them authority over their health information, thereby revolutionizing the conventional dynamics of the healthcare provider-patient relationship. Nonetheless, existing systems for managing IHRs face obstacles in providing patients with dependable, trackable, and secure control over their medical records, potentially compromising their authenticity and precision. Furthermore, the prevalent centralized methods of IHR management hinder the seamless exchange of medical data and introduce the risk of a singular point of failure.To address these challenges, a proposal is presented to utilize Ethereum blockchain-based smart contracts, providing patients with decentralized, immutable, and transparent management of their medical data. This solution also incorporate the decentralized storage feature of interplanetary file systems (IPFS). These integrated components collaborate effectively to securely access, store, and exchange patients’ medical information, with the overarching goal of enhancing the integrity and security of patient-controlled health records.
The lack of privacy-preserving capabilities hinders the further development of blockchains and smart contracts. While numerous privacy solutions have been proposed, limitations persist. First, most existing solutions focus on specific privacy protections such as anonymous payments, private data, or multi-party computation tasks. However, these solutions lack a general privacy ability, allowing users to deploy applications with diverse privacy requirements. Second, existing solutions have limited customizability, which means users cannot easily customize and adapt the privacy policies according to their specific demands or preferences. In this article, we present EtherCloak, which adopts trusted execution environments (TEEs) to achieve a general and customizable privacy policy on account model blockchains, enabling users to conceal any on-chain information. To address the security issues caused by the unreliability of the host the TEE runs on, we design the enclave state check and crash recovery mechanisms and employ them in the block generation process. In addition, we propose an access control mechanism for privacy policy management and data query. We prove that EtherCloak offers general and customizable privacy protection with a minimal increase in transaction size (less than triple) and communication overhead (approximately 10%) compared to Ethereum.
The emergence of the Internet of Vehicles (IoVs) has also exposed security challenges that require advanced strategies to maintain secure data provenance (SDP) and ensure data credibility and anomaly detection. This paper introduces an innovative framework tailored for the dynamic and distributed nature of IoVs that enables the secure tracing of data origins and ensures the reliability of data through plausibility checks. Our approach leverages the principles of decentralized SDP using Verifiable Credentials (VCs) and distributed ledger technology (DLT) to establish a traceable and tamper-evident data lineage, enhancing the integrity and authenticity of vehicular communications. To address the complexities of anomaly detection, we integrate checks that scrutinize data streams for abnormal patterns, enabling the timely identification and mitigation of potential security breaches. We also propose a robust mechanism to assess data plausibility, ensuring that only credible and verifiable data influence the decision-making processes in the IoVs ecosystem. Through detailed experimentation and analysis, our methodology demonstrates significant improvements in securing IoVs against common threats such as impersonation, data tampering, and privacy breaches. This fosters a trustworthy and resilient vehicular network environment.
Recently, there has been a notable increase in the advancement of multimodal emotion analysis systems. These systems try to get a comprehensive knowledge of human emotions by combining data from several sources, including text, voice, video, and images. This complete strategy tackles the constraints of text-only sentiment analysis, which could disregard subtle emotional expressions. This chapter examines the difficulties and approaches related to analyzing emotions utilizing many modes of data, specifically emphasizing combining data, extracting features, and ensuring scalability. This underscores the significance of creating strong fusion techniques and network architectures to integrate various data modalities efficiently. The research also explores the utilization of these systems in domains such as social media sentiment analysis and clinical evaluations, showcasing their capacity to improve decision-making and user experiences.