Securing IoT Data: FDUP-RDIC—A Fully Decentralized Approach for Privacy-Preserving and Efficient Data Integrity

Cloud computing provides an effective way to manage and share massive medical data for Electronic Medical Record (EMR), hence establishing cloud-based EMR has attracted more and more attention. The data integrity and privacy issue in cloud-based EMR should be emphasized since users do not want their medical records to be damaged or disclosed to others. To address the concern in this paper, we propose an efficient and secure Data Integrity Auditing scheme with Traceability for cloud-based EMR (DIAT), which provides data integrity and privacy. We store multiple copies so that data can be recovered quickly from damage as long as one copy remains intact; meanwhile, data cannot be leaked to unauthorized entities since it is stored as ciphertext. For supporting data dynamics, we have designed a two-dimensional data structure, called Dynamic Mapping Hash Table (DMHT). It does not require large auxiliary validation information, nor does it affect the sequence numbers of other blocks. Moreover, data traceability is achieved by organizing all versions of a data block as a chain so that doctors are enabled to track the changes of patients condition in their records. In addition, formal security analysis and experiment results confirm that DIAT is provably secure and efficient.

Decentralized storage powered by blockchain is becoming a new trend that allows data owners to outsource their data to remote storage resources offered by various storage providers. Unfortunately, unqualified storage providers easily encounter unpredictable downtime due to security threats, such as malicious attacks or system failures, which is unacceptable in many real-time or data-driven applications. As a result, continuous data integrity should be guaranteed in decentralized storage, which ensures that data is intact and available for the entire storage period. However, this requires frequent checking for long time periods and incurs heavy burdens of both communication and computation, especially in a big data scenario. In this paper, we propose an efficient continuous big data integrity checking approach for decentralized storage. We design a data-time sampling strategy that randomly checks the integrity of multiple files at each time slot with high checking probability. Furthermore, to tackle the fairness problem derived from the sampling strategy, we propose a fair approach by designing an arbitration algorithm with the verifiable random function. Security analysis shows the security of our approach under the random oracle model. Evaluation and experiments demonstrate that our approach is more efficient in the big data scenario compared with the state-of-the-arts.

Most of the data generated on high-performance computing systems are transferred to storage in remote systems for various purposes such as backup. To detect data corruption caused by network or storage failures during data transfer, the receiver system verifies data integrity by comparing the checksum of the data. However, the internal operation of the storage device is not sufficiently investigated in the existing end-to-end integrity verification techniques. In this paper, we propose an efficient and robust data integrity verification scheme for large-scale data transfer between computing systems with high-performance storage devices. To ensure the robustness of the integrity verification, we control the order of I/O operations. In addition, we parallelize checksum computing and overlap it with I/O operations to make the integrity verification efficient.

INTRODUCTION: With the rapid development of cloud computing and intelligent technology, traditional accounting informatization systems are gradually migrating to cloud computing platforms, promoting financial management's automation and intelligence. OBJECTIVES: However, data security in the cloud computing environment, especially the issue of data integrity, has become one of the core challenges for intelligent accounting informatization systems. Accounting informatization systems rely on the storage and processing of a large amount of financial, tax, and transaction data, and the integrity of these data is directly related to the financial transparency, compliance, and decision-making accuracy of an enterprise. METHODS: Therefore, how to design an efficient and scalable cloud data integrity verification algorithm becomes the key to ensuring the reliability and security of intelligent accounting systems. This paper proposes a cloud data integrity verification algorithm for smart accounting informationization based on a cloud computing environment. The algorithm combines the efficient data processing capability of cloud computing with the automation requirements of smart accounting systems to ensure data integrity during storage, transmission, and processing through various data validation techniques such as digital signatures, hash algorithms, and blockchain-based distributed ledgers. RESULTS: The algorithm design considers the dynamics and scalability of the cloud computing environment. It can realize fast, real-time data validation and integrity detection in a large-scale data environment. Through experimental verification, the algorithm proposed in this paper performs well in processing large-scale accounting data with high verification efficiency and accuracy. CONCLUSION: Compared with traditional validation methods, the algorithm improves the speed of data validation. It enhances the system's ability to prevent data tampering and loss, providing a new cloud data integrity assurance scheme for intelligent accounting informatization systems.

Efficient Data Integrity and Auditing in Cloud by using Block Chain

Due to the characteristics of resource-constrained in wireless sensor networks (WSNs), energy consumption is a major concern. Data aggregation is an important method to reduce the energy consumption and communication overhead ; however, it suffers from the security problems of data integrity. In fact, designing integrity schemes for data aggregation is an imperative problem for securing WSNs. In this paper, we propose a secure data aggregation based on homomorphic MAC scheme that provide efficient secure data integrity with different trade-offs between security assumptions, computation cost, and communication payload. The scheme uses two types of homomorphic MAC (i.e., MACs and EMACs). Each MAC provides integrity of the transmitted message and each EMAC provides integrity of the MACs. Our experiments show that our scheme requires less computation overheads and energy consumption than previously methods and can effectively preserve data integrity.

A secure and scalable data integrity auditing scheme based on hyperledger fabric

Blockchain-based Order Management Process in Decentralized Production Networks: A Conceptual Framework

Cloud computing provides a novel computing paradigm for enterprises to store programs and data in the Cloud in a transparent manner, which poses the challenge of security and privacy. In this paper, based on homomorphic cryptography and Zero-Knowledge Proof, we present a novel privacy-preserving scheme for Cloud publish/subscribe service, which achieve efficient privacy-preserving authentication, data integrity, and publish-subscribe confidentiality. The performance evaluation and security analysis demonstrate the practice and validity of the proposed scheme.

The integrity of real-time data streams has not been solved for a long time and has gradually become a difficult problem in the field of data security. Most of the current data integrity verification schemes are constructed using cryptographic algorithms with complex computation, which cannot be directly applied to real-time stream computing systems. Aiming at the above issue, this paper adopts the Carter–Wegman MAC method, pseudo-random function and symmetric cryptography mechanism to construct the Real-Time Data Integrity Verification scheme based on symmetric key in stream computing systems (RT-DIV), which converts a one-time MAC to a multiple-time MAC and retains the advantage of security performance. Then, a security analysis is given under the standard model. Finally, experiments and data analysis are conducted in a simulated environment, and the experimental results show that the RT-DIV scheme can effectively guarantee the integrity of real-time data streams. Furthermore, the RT-DIV scheme lays the foundation for the secure application of the stream computing system.

Provable data deletion from efficient data integrity auditing and insertion in cloud storage

Recently released Intel processors have been equipped with hardware instruction tracing facilities to securely and efficiently record the program execution path. In this paper, we study a case for data integrity checking based on Intel Processor Trace (Intel PT), the instruction tracing facility on x86 processors. We incorporate software instrumentation and hardware instruction tracing to guarantee fine-grained data integrity without frequently switching the processor mode. We incorporate the idea in a system named DTrace which provides primitives to instruct Intel PT to capture the data load and store events, even current Intel PT implementations only record control transfers. The trace is analyzed before the program makes security-sensitive operations. We apply DTrace in several case studies to show that the primitives that DTrace provides are easy to use and help to enhance data integrity in applications. We further evaluate DTrace with several microbenchmarks to show the time cost that DTrace’s data tracing operation incurs. We also evaluate DTrace on Nginx to show the performance impact when Nginx is enhanced in security to provide the integrity during the runtime execution for programmer-defined security sensitive data. We find the performance overhead that DTrace incurs for the data tracing is moderate.

<p>The development of cloud storage is indispensable for today’s Internet information technology. The superiority of cloud storage is that the ownership of the storage medium and the ownership of the stored data are divided and held by two parties with respective interests - cloud server providers and data users. However, the transmission, storage and utilization of data constantly caused the violation of users’ rights and interests. Data integrity as a countermeasure has been paid growing attention to by researchers. Traditional data integrity protection schemes are based on the cloud server-client architecture, which requires high computational overhead and communication. To address this scenario, this paper proposes an improved data integrity verification scheme that enables local users to perform rapid and efficient data integrity verification of data stored on cloud servers, reduces the volume of communication data during the verification process, and effectively prevents the loss or tampering of data stored in the cloud server.</p> <p> </p>

Cloud computing has been envisioned as the next-generation architecture of IT enterprise. However the security problem of Cloud computing hinder itself from large-scale application. One major challenge is to verify the integrity of data at untrusted server under the condition of supporting public auditability and dynamic data operation. This paper analyzed the problems of existing schemes, introduced commutative hash into Merkle hash tree, aggregated basic block into subblock and block, constructed a kind of hierarchical Merkle hash tree by using the concept of hierarchical structure in granular computing and proposed an improved scheme to offer effective, multi-granular dynamic operation. We analyzed the efficiency and security of the protocol. The analysis result showed that the protocol is efficient and security.

Today’s engineering design is carried out in a distributed fashion geographically or physically. This places new requirements on the computational environments such as efficient integration and collaboration. With the advances of the Internet and Network environment recently, many researches have been proposed and at the same time, Web-based distributed design gives to a new paradigm in design and manufacturing fields. That is, Web-based technologies lead to reduce the product development times and to ensure a competitive product in order to exchange and interact of real-time design information that integrates the distributed design environment between departments as well as companies via Internet and Web. So, an efficient data communication for design information sharing is the foundation for collaborative systems in the distributed environment. Design data communication techniques such as CORBA, DCOM and RMI have been considered in the existing research but they have some problems that are limitations of interoperability and firewall problems in the Web. Therefore, this paper presents a Web-based distributed design application where distributed design information resources are integrated and exchanged using Web Services for supporting XML and HTTP without the interoperability and firewall problems through the 330K VLCC case.