In the ever-expanding landscape of cloud computing, concerns over the privacy of sensitive data have become paramount. This chapter delves into the intricate realm of privacy-preserving data storage and processing in the cloud. It addresses the challenges posed by data ownership, control, and the ever-looming threat of data breaches in cloud environments. Focusing on innovative techniques, the chapter explores encryption mechanisms, secure multi-party computation, and trusted execution environments for privacy-preserving data storage. Additionally, it delves into cutting-edge methods such as privacy-preserving machine learning, secure query processing, and tokenization for safeguarding privacy during data processing in the cloud. Real-world case studies exemplify successful implementations, providing insights into practical applications. The chapter concludes by envisioning future trends, including the integration of blockchain and zero-knowledge proofs, and highlights the challenges and opportunities that lie ahead in the pursuit of privacy preservation in cloud computing.
Faton Kabashi, Halil Snopçe, Artan Luma, Vehbi Neziri
The increasing demand for a secure and transparent mechanism for verifying academic credentials has led to the exploration of blockchain technology (BT) as a viable solution. This paper presents a three-layered application for the reliable verification of academic credentials, leveraging the immutable and decentralized nature of BT. The system includes a data layer (DL), a blockchain layer (BL), and an application layer (AL). The DL records student records, faculty staff records, and credentials. The BL utilizes smart contracts to record and verify academic records, ensuring their authenticity and integrity. The AL provides a userfriendly interface for various stakeholders, such as students, educational institutions, and employers, to communicate with the system. This effort aims to determine how BT can be utilized to enhance the security, transparency, and efficiency of academic credential verification processes. Efficiency in academic credential verification processes ultimately contributes to a more reliable and effective educational ecosystem.
The rapid growth of electronic health (eHealth) systems has led to serious security and privacy challenges, highlighting the critical importance of protecting sensitive healthcare data. Although researchers have employed blockchain to tackle data management and sharing within eHealth systems, substantial privacy concerns persist as a primary challenge. In this paper, we introduce TrustHealth, a secure data sharing system that leverages trusted execution environment (TEE) and blockchain technology. TrustHealth leverages blockchain to design smart contracts to offer robust hashing protection for patients’ healthcare data. We provide a secure execution environment for SQLCipher, isolating all sensitive operations of healthcare data from the untrusted environment to ensure the confidentiality and integrity of the data. Additionally, we design a TEE-empowered session key generation protocol that enables secure authentication and key sharing for both parties involved in data sharing. Finally, we implement TrustHealth using Hyperledger Fabric and ARM TrustZone. Through security and performance evaluation, TrustHealth is shown to securely process massive encrypted data flows at a rate of 5000 records per second, affirming the feasibility of our proposed scheme. We believe that TrustHealth offers valuable guidelines for the design and implementation of similar systems, providing a valuable contribution to ensuring the privacy and security of eHealth systems.
Dincy R. Arikkat, Mert Cihangiroglu, Mauro Conti, Rafidha Rehiman K. A. · 7 authors
The rise of IT-dependent operations in modern organizations has heightened their vulnerability to cyberattacks. Organizations are inadvertently enlarging their vulnerability to cyber threats by integrating more interconnected devices into their operations, which makes these threats both more sophisticated and more common. Consequently, organizations have been compelled to seek innovative approaches to mitigate the menaces inherent in their infrastructure. In response, considerable research efforts have been directed towards creating effective solutions for sharing Cyber Threat Intelligence (CTI). Current information-sharing methods lack privacy safeguards, leaving organizations vulnerable to proprietary and confidential data leaks. To tackle this problem, we designed a novel framework called SeCTIS (Secure Cyber Threat Intelligence Sharing), integrating Swarm Learning and Blockchain technologies to enable businesses to collaborate, preserving the privacy of their CTI data. Moreover, our approach provides a way to assess the data and model quality and the trustworthiness of all the participants leveraging some validators through Zero Knowledge Proofs. Extensive experimentation has confirmed the accuracy and performance of our framework. Furthermore, our detailed attack model analyzes its resistance to attacks that could impact data and model quality. • Definition of a Swarm Learning approach for collaborative CTI. • Definition of a Blockchain-based solution for privacy preservation in CTI sharing. • Secure CTI validation using a consensus mechanism and Zero-Knowledge Proof.
The increasing integration of the Internet of Health Things (IoHT) in the eHealth sector has significantly advanced the collection of Electronic Health Records (EHR). While blockchain technology offers enhanced data integrity and traceability for EHR, its inherent immutability often clashes with user concerns regarding security and privacy and prevents records from being securely updated. To address these challenges, our paper presents an innovative redactable blockchain mechanism tailored for EHR management. This approach leverages a decentralized, attribute-based chameleon hash function, enabling transaction-level redactions without succumbing to the vulnerabilities of a single point of failure. We implemented the proposed system based on the Charm cryptographic library and revocable IPFS scheme. The Chameleon hash function can support redactable operation for on-chain EHR-related information in seconds level. We also conducted extensive experiments on blockchain performance and IPFS performance, highlighting that the proposed redactable blockchain is efficient in practice for EHR management.
The concept of the Internet of Medical Robotics Things (IoMRT) is where intelligent robots assess surrounding events, combine information from their sensors, use both local and dispersed intelligence to determine the best course of action, and move or command objects. Telesurgery is one application of IoMRT (TS). With 5G-enabled Tactile Internet (TI) enabling telesurgery (TS), there is ample opportunity to provide exceptional, accurate, ultra-responsive, and real-time virtual surgical procedures. The potential for accurate surgical diagnosis involving the exchange of patient electronic medical records (EMR) with several doctors using an assistant robot (AR) could be greatly useful in the medical field. As a part of this, permission delegation has emerged as a novel approach for data sharing in TI. Robust control of access guidelines combined with a configurable permission scheme promise secure EMR exchange. The present research proposes a multi-hop permission delegation strategy for EMR exchange based on blockchain technology and with configurable delegation depth. Furthermore, the original EMRs are stored on the interplanetary file system (IPFS). Permission delegation uses smart contracts and proxy re-encryption technology. Attribute-based encryption, which offers fine-grained management of access, is used to guarantee data security. Blockchain is also utilized to accomplish immutability and traceability. Delegators may regulate the depth of delegation by using smart contracts. The suggested approach satisfies the intended aims, according to analysis of the protocol. Lastly, the Ethereum test chain is used to assess and put the suggested method into practice. The outcomes of the conducted experiments demonstrate that the suggested protocol operates better than the competitors.
This research introduces the Blockchain Academic Credential Interoperability Protocol (BACIP), designed to significantly enhance the security, privacy, and interoperability of verifying academic credentials globally, addressing the widespread issue of academic fraud. BACIP integrates dual blockchain architecture, smart contracts, and zero-knowledge proofs to offer a scalable and transparent framework aimed at reducing fraud and improving the mobility and opportunities for students and professionals worldwide. The research methodology adopts a mixed-methods approach, involving a rigorous review of pertinent literature and systematic integration of advanced technological components. This includes both qualitative and quantitative analyses that underpin the development of a universally compatible system. Preliminary evaluations suggest that BACIP could enhance verification efficiency and bolster security against tampering and unauthorized access. While the theoretical framework and practical implementations have laid a solid foundation, the protocol's real-world efficacy awaits empirical validation in a production environment. Future research will focus on deploying a prototype, establishing robust validation policies, and defining precise testing parameters. This critical phase is indispensable for a thorough assessment of BACIP's operational robustness and its compliance with international educational standards. This work contributes significantly to the academic field by proposing a robust model for managing and safeguarding academic credentials, thus laying a strong foundation for further innovation in credential verification using blockchain technology.
Auditability and verifiability are critical elements in establishing trustworthiness in federated learning (FL). These principles promote transparency, accountability, and independent validation of FL processes. Incorporating auditability and verifiability is imperative for building trust and ensuring the robustness of FL methodologies. Typical FL architectures rely on a trustworthy central authority to manage the FL process. However, reliance on a central authority could become a single point of failure, making it an attractive target for cyber-attacks and insider frauds. Moreover, the central entity lacks auditability and verifiability, which undermines the privacy and security that FL aims to ensure. This article proposes an auditable and verifiable decentralized FL (DFL) framework. We first develop a smart-contract-based monitoring system for DFL participants. This monitoring system is then deployed to each DFL participant and executed when the local model training is initiated. The monitoring system records necessary information during the local training process for auditing purposes. Afterward, each DFL participant sends the local model and monitoring system to the respective blockchain node. The blockchain nodes representing each DFL participant exchange the local models and use the monitoring system to validate each local model. To ensure an auditable and verifiable decentralized aggregation procedure, we record the aggregation steps taken by each blockchain node in the aggregation contract. Following the aggregation phase, each blockchain node applies a multisignature scheme to the aggregated model, producing a globally verifiable model. Based on the signed global model and the aggregation contract, each blockchain node implements a consensus protocol to store the validated global model in tamper-proof storage. To evaluate the performance of our proposed model, we conducted a series of experiments with different machine learning architectures and datasets, including CIFAR-10, F-MNIST, and MedMNIST. The experimental results indicate a slight increase in time consumption compared with the state-of-the-art, serving as a tradeoff to ensure auditability and verifiability. The proposed blockchain-enabled DFL also saves up to 95% communication costs for the participant side.
Leonardo Juan Ramírez López, David Millan Mayorga, Luis Hernando Martinez Poveda, Andres Amaya · 5 authors
The management of large medical files poses a critical challenge in the health sector, with conventional systems facing deficiencies in security, scalability, and efficiency. Blockchain ensures the immutability and traceability of medical records, while the cloud allows scalable and efficient storage. Together, they can transform the data management of electronic health record applications. The method used was the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to choose and select the relevant studies that contribute to this research, with special emphasis set on maintaining the integrity and security of the blockchain while tackling the potential and efficiency of cloud infrastructures. The study’s focus is to provide a comprehensive and insightful examination of the modern landscape concerning the integration of blockchain and cloud advances, highlighting the current challenges and building a solid foundation for future development. Furthermore, it is very important to increase the integration of blockchain security with the dynamic potential of cloud computing while guaranteeing information integrity and security remain uncompromised. In conclusion, this paper serves as an important resource for analysts, specialists, and partners looking to delve into and develop the integration of blockchain and cloud innovations.
To ensure the quantum security requirement in Internet of Things (IoT) scenarios, we first propose certificateless anti-quantum blind signature (CLAQBS) for blockchain-based logistics donation system in IoT scenario, its security relies on the hardness of small integer problem on ring in number theory research unit lattice; the ethereum lightning network enhances the transaction speed of consortium blockchain and the rejection sampling algorithm improves the signature speed; it has short signature key and high-execution efficiency. Then, we propose certificateless anti-quantum sequential aggregate signature (CLAQSAS) for IoT intelligent invoice system, the signer performs sequential aggregate signature on invoice information of each different goods to generate a new signature; it ensures the anti-quantum security because of the unique nonsampling algorithm, trapdoor generation algorithm and matrix preimage sampling algorithm in lattice.
The use of log files in digital forensics highlights the importance of ensuring their data integrity for auditing purposes. However, traditional centralized audit log systems face challenges in maintaining data integrity due to log injection attacks and single-point failures. Although blockchain technology can accurately process and replicate log files, existing blockchain-based audit log systems still suffer from security and reliability issues due to their weak threat models and limited scalability. To address these concerns, we propose a blockchain-based audit log system that ensures data integrity under a general threat model where a part of the nodes, including loggers and auditors, are untrusted. First, our proposed system resists collusion attacks by incorporating multiple nodes for system processes and utilizing smart contracts to enforce consensus algorithms. Second, to save blockchain storage space, we design an efficient log integrity proof method, which generates a sub-Non-Fungible Token (sub-NFT) for each log file and keeps it on the blockchain as integrity proof. The single-point failure problem is resolved by outsourcing log files to a distributed file system. To evaluate the proposed system, we implement a prototype based on Hyperledger Fabric. Experimental results show that our proof generation method can reduce storage space usage in comparison to other blockchain-based audit log systems, saving approximately 50% of space in Hyperledger Fabric. The security analysis proves that our system can ensure log file data integrity under the proposed threat model.
With the rapid growth in demand for mobile data fueled by the emergence of new consumer applications that require high quality of service, existing static mobile data pricing plans are no longer suitable. Although several dynamic pricing mechanisms have been proposed in the literature, they have not been widely adopted due to their associated implementation complexity, the lack of trust in the associated platforms, and the absence of automatic enforcement. To address these challenges, we propose a credible trust framework (CREDIT) that leverages well-established Ethereum smart contracts for service-level agreement (SLA) enforcement. CREDIT introduces a novel SLA verification mechanism through fair auditor selection and auditor payoff to ensure truthfulness, and hence reinforces trust between the various parties involved in CREDIT. A detailed game-theoretic analysis is provided to prove the credibility of CREDIT by using the principle of a strong Nash equilibrium. In addition, CREDIT is prototyped by leveraging the smart contracts of Ethereum Blockchain. The results achieved provide a valuable validation of the feasibility of CREDIT.
B Mohanraj, M Kalpana A, Mohana Priya, D Abdul Jaleel · 6 authors
Recent advancements in blockchain-based cloud computing highlight its potential in providing robust data security, integrity, and confidentiality. While cloud computing is increasingly utilized for remote resource access, it presents significant security challenges that necessitate innovative solutions. This research proposes a novel SecureCloudChain IoT (SCC-IoT) architecture, which integrates blockchain technology into cloud-supportive platforms to enhance security measures. The SCC-IoT architecture includes a distributed blockchain approach to ensure data security while maintaining privacy and integrity. This system is designed to be adaptable and scalable, meeting real-world requirements effectively. By promoting a decentralized and efficient environment, SCC-IoT improves the reliability, stability, and load balancing of cloud services. Performance assessments through various experimental conditions have been conducted to evaluate the proposed system. The results demonstrate SCC-IoT’s effectiveness in mitigating potential attacks and ensuring secure and reliable cloud computing. This research highlights the significance of integrating blockchain technology into cloud platforms, paving way for more secure and efficient cloud computing solutions.
Kulvinder Singh, R. P. S. Tomar, Vansh Chaudhary, Mridul Jain
The cloud-based meteorological data management offers vast potential for research and collaboration, but inherent privacy concerns and data integrity risks necessitate robust solutions. This research suggests a new, multi-layered method to improve integrity and privacy in this field. By utilizing homomorphic encryption, this study makes it possible to perform calculations on encrypted meteorological data while keeping private information hidden from cloud service providers. Federated learning promotes cooperation without compromising the privacy of raw data by enabling distributed learning on local datasets. Lastly, zero-knowledge proofs are integrated to confirm the accuracy of computations made on encrypted data, ensuring the validity of outcomes without disclosing the underlying data. This integrated strategy presents a viable path for reliable and safe cloud-based meteorological data administration, promoting cutting-edge study and creativity while protecting private data.
Nowadays, technology is increasingly being adopted in different kinds of businesses to process, store, and share sensitive information in digital environments that include enormous numbers of users. However, this has also increased the likelihood of cyberattacks and misuse of information, potentially causing severe damage. One promising technology, which can provide the required security services with an improved level of efficiency, is blockchain. This research explores the use of Ethereum blockchain and smart contracts to create a secure and efficient quality assurance system (QAS) for academic programs. By utilizing blockchain and smart contracts, the proposed approach improves the integrity and reliability of sensitive information processed by the QAS, promotes transparency and governance, and reduces the time and effort required for quality operations. The current approach uses an additional access control layer to further enhance user privacy. Smart contracts automate various quality transactions and saves time and resources, and hence increases the efficiency of the QAS. The interplanetary file system (IPFS) is used to address the challenge of size limitations in blockchain. Additionally, this research investigates the use of various cryptographic schemes to provide robust security services at the application layer. The experimental results showed that the use of a hybrid cryptosystem relying on an Elliptic curve digital signature and AES encryption (AES_ECCDSA) outperforms other counterparts’ cryptosystems using an RSA digital signature and AES encryption (AES_RSADSA) and Elliptic Curve Integrated Encryption Scheme (ECIES) in terms of speed. The performance results showed that AES_ECCDSA consumes 188 ms to perform the required cryptographic operations for a standard-quality document with a size of 8088 KB, compared to the 231 ms and 739 ms consumed by the AES_RSADSA and ECIES schemes, respectively. This study presents a prototype implementation of the blockchain-based QAS, which outlines the processing model and system requirements for key QAS processes. It has been found that the cost and time required for blockchain operations vary depending on the size of the input data—a larger data size requires more time and costs more to process. The results of the current study showed that the time delay for blockchain transactions ranges from 15 to 120 s, while the cost ranges from USD 50 to USD 400. This research provides evidence that blockchain and smart contract technologies have the potential to create a secure, efficient, and trustworthy QAS environment for academic programs.
Abstract Electronic health records (EHRs) are important for the efficient management of healthcare data. However, Healthcare data travels across an open route, i.e., the Internet, making EHR security a difficult process to do. This puts healthcare data vulnerable to cyber assaults. A possible method for protecting EHRs is blockchain technology. In this work, we develop an EHR architecture based on blockchain, which ensures all stakeholder's safety and privacy. We analyze various security architectures used for EHRs and the standard encryption system is integrated with quantum computing (QC). To safeguard the conventional traditional encrypting system against quantum assaults, we provide a hybrid signature technique that combines the Elliptic Curve Digital Signature Algorithm (ECDSA) and Dilithium within the anti-quantum lattice-based blind signature. Based on the difficulty of lattice problems over finite fields, Dilithium is a lattice-based signature method that is substantially safe against selected message assaults. The developed technique creates high entropy secret keys using the lattice basis delegation mechanism. The combination of ECDSA and Dilithium provides an efficient and secure signature system that is resilient to quantum attacks. The proposed scheme ensures that only authorized users with a defined role can use the database to access the data. We evaluate the efficiency of our scheme by comparing its performance to other state-of-the-art solutions in terms of transaction throughput, resource utilization, and communication cost. Results demonstrate that the developed technique outperforms the existing techniques in terms of efficiency and security.
Blockchain deployments require efficient consensus models in order to be scaled for larger networks. Existing consensus models either use stake-levels, trust-levels, authority-levels, etc. or their combinations in order to reduce mining delay while maintaining higher security levels. But these models either have higher energy requirements, lower security, or have linear/exponential relationship between mining delay and length of the chains. Due to these restrictions, the applicability of these models is affected when deployed under real-time network scenarios. To overcome these issues, this text proposes design of an efficient novel trust-based hybrid consensus model for securing blockchain deployments. The proposed model initially uses a hybrid consensus model that fuses Proof-of-Work (PoW), Proof-of-Stake (PoS) with Proof-of-Temporal-Trust (PoTT) for improving security while maintaining higher Quality of Service (QoS) levels. The PoTT Model fuses together temporal mining delay, temporal mining energy, throughput and block mining efficiency in order to generate miner-level trusts. These trust values are fused with Work efficiency and Stake levels and used for selection of miners. The selected miners are used for serving block addition requests, which assists in improving mining speed by 3.2%, reducing energy consumption 4.5%, and improving throughput by 8.5%, while improving block mining efficiency by 2.9% when compared with existing mining optimization models. This performance was validated under Sybil, Finney, Man-in-the-Middle, and Spoofing attacks. Performance of the model was observed to be consistent even under attacks, thereby making it useful for real-time network scenarios.
Anuj Nepal, Mohamed Ahzam Amanullah, Robin Doss, Frank Jiang
The evolution of the Internet of Vehicles (IoVs) presents many opportunities for intelligent transport systems; however, it brings significant security challenges that threaten the security and reliability of the data. Security, reliability, and trustworthiness are the essential critical requirements for the IoVs to ensure secure and efficient decision-making processes in an accurate, secure, and trustworthy manner. Traditional research paradigms have predominantly focused on data integrity, overlooking the essential need for data to be realistic, consistent, trustworthy, and reliable. Addressing this gap, our paper introduces a decentralized secure data provenance (SDP) protocol for the dynamic and distributed nature of IoVs to ensure verifiable security properties regarding data plausibility, source identity, data privacy, location authenticity, and data integrity, properties that are fundamental for achieving SDP. Our protocol integrates Verifiable Credentials (VCs) with distributed ledger technology (DLT), Road-Side Unit (RSU) infrastructure, cryptographic techniques, and plausibility checks to ensure secure, traceable, and tamper-evident data lineage. This comprehensive approach enables the timely identification and mitigation of potential security breaches, such as impersonation, data tampering, and privacy violations which are crucial for maintaining SDP and ensuring data credibility through anomaly detection and plausibility checks. Through detailed security analysis and validation, our methodology demonstrates improved resilience against common threats, ensuring that only credible and verifiable data inform its decision-making processes.