Data privacy protection model based on blockchain in mobile edge computing

SummaryThe block chain is the emerging domain that offers the features like shared, immutable, and decentralized dataset that saves the asset's history. Security and storage are the most challenging aspect. The classical techniques' issues and challenges are an encouragement for developing a fresh block chain‐assisted IPFS model with access control policies. Hence, this research paper introduces an effective access control and authentication based on an interplanetary file system (IPFS)‐based block chain and access control system for attaining secured transactions. The developed method comprises five entities, that is smart contract, data owner, data requester, block chain and IPFS along with eight phases, to be exact setup, user registration, initialization, storage and data encryption, authentication, testing, access control, and decryption phase, to provide better access control and storage capacity. The proposed IPFS‐based block chain and access control system offered effective storage and secure transactions in the block chain network. The highest detection rate (0.870), lowest communication overhead (0.766 MB), and highest privacy rate (0.719) are all achieved by the proposed IPFS‐based block chain and access control system.

Personal Health Records (PHR) system has attracted intensive attention due to its universal accessibility and low cost in economics. Because of high cost of storing data and access control, most PHR systems adopt centralized management, where an authoritative management center controls the entire system and PHR data is stored in a trusted third-party service provider. However, there are some disadvantages, such as fully trusting to a control center, suffering from a single point of failure, and data deleting. In this paper, we propose a novel distributed framework based on blockchain and IPFS (Inter Planetary File System), and a suite of mechanisms for data access control to PHR data. Smart Contracts are designed on the blockchain, and all data operations are treated as transactions. The symmetric cryptographic algorithm is used to encrypt the PHR data, and then all encrypted data is stored on IPFS nodes securely in distributed environment. The ciphertext-policy attribute-based encryption (CP-ABE) is used to encrypt the symmetric secret keys, and the corresponding ciphertext is stored and published in IPNS (Inter Planetary Name Space), so as to achieve fine-grained access control. Analytical and experimental results are presented, which show that our framework has ability to provide authenticity, confidentiality, fine-grained access control, forward secrecy, and traceability simultaneously.

Nowadays, cloud-based storage systems play a vital role in IoT data storage, processing, and sharing. Despite its contribution, the current cloud-based architecture may cause severe data leakage or jeopardize user privacy. Meanwhile, the cloud-based architecture heavily relies on a trusted third-party auditor (TPA) and runs in a centralized control manner. However, the TPA may not be a completely trustworthy entity, and a single point of failure might cause the centralized system to collapse. Fortunately, with the advent of blockchain technology, the decentralized storage model has gained popularity. A decentralized storage system successfully eradicates the rule of TPA, solves the problem of a single point of failure, and has many advantages over a centralized control architecture, such as low storage prices and high throughput. This study offers a blockchain-based decentralized distributed storage and sharing scheme that provides end-to-end encryption and fine-grained access control. In our proposed IoTChain model, fine-grained permission is based on attribute-based access control (A-BAC) policy by employing the Ethereum blockchain as an auditable access control layer. Smart contracts are tailored for the IoTChain model, which combines the Ethereum blockchain and the interplanetary file system (IPFS). We used an advanced encryption standard (AES) for encryption and the elliptic curve Diffie-Hellman key exchange protocol for secret key sharing between data owners and users. Also, the proof-of-work (PoW) consensus mechanism is replaced with a proof-of-authority (PoA) to minimize system transaction cost and boost system throughput. Additionally, our solution has been tested on the Ethereum official test network Rinkeby, and the results demonstrate that our approach is realistic and economical on the IoT data.

With the advances and innovations in digital technologies, blockchain has empowered advancements in communications and networking, promising to build trust and establish secure decentralized communications networks. Unfortunately, current personal data privacy protection schemes still suffer from explicit storage, lack of data ownership and implementation of fine-grained access control by users, and lack of transparency and auditability of data. In this article, we propose a personal data privacy protection scheme based on consortium blockchain that stores original data encrypted with an improved Paillier homomorphic encryption mechanism, namely PDPChain, where users realize fine-grained access control based on ciphertext policy attribute-based encryption (CP-ABE) on blockchain. In this scheme, consortium blockchain combines distributed private clusters to store the encrypted data, improving data transmission efficiency, and guaranteeing user privacy and security through off-chain storage and on-chain transmission synergy. In addition, it is more lightweight encryption and demarcation, ultimately protecting personal data privacy and providing a secure and trusted way to obtain information for data mining. For the performance testing, data in the form of files are used as an example, and the scheme is designed and simulated on Hyperledger Fabric and InterPlanetary File System. Experimental results show that the improved Paillier encryption mechanism reduces the overall encryption and decryption elapsed time by 25% and encryption elapsed time by 48%. Furthermore, the proposed CP-ABE access control method is adaptive to storing and sharing a massive amount of data. With the increase in the number of access control policies, the overall time-consuming of the scheme does not increase, and the time-consuming of decryption can also be stabilized at about 2 s.

PurposeThe purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud.Design/methodology/approachThis section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design.FindingsFor health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning.Originality/valueThe Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients’ health issues at any time and from any location. Medical IoT devices monitor patients’ health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning.

An adaptive access control scheme based on trust degrees for edge computing

Scalable and secure access control policy update for outsourced big data

-Enabling cryptographically enforced access controls for data hosted in untrusted cloud is attractive for many users and organizations. However, designing efficient cryptographically enforced dynamic access control system in the cloud is still challenging. In this paper, we propose Crypt-DAC, a system The rapid increase in textual data in navigation tasks for devices like GPS or smart assistants creates challenges for managing and storing data in large-scale systems. Data deduplication, which reduces storThis project presents AgriSafe, a secure and transparent land registration system designed specifically for the agricultural sector, integrating blockchain and artificial intelligence (AI) technologies. Recognizing the challenges posed by fraud and manipulation in traditional land registration systems, AgriSafe leverages blockchain to ensure immutability and tamper-proof storage of land ownership records. Advanced AI models—including logistic regression, support vector machines, and random forests—are employed to detect and eliminate fraudulent data before it is committed to the blockchain, ensuring only verified land data is stored. The system utilizes smart contracts for automated validation of land data, improving efficiency and accuracy. Furthermore, verified land information is securely stored on the Interplanetary File System (IPFS), with only the data hash stored on the blockchain, ensuring both security and accessibility. AgriSafe undergoes comprehensive evaluation, including AI model accuracy, blockchain scalability, and smart contract vulnerability assessment, delivering a robust, scalable, and fraud-resistant solution for agricultural land registration.age needs by eliminating duplicate data, offers a solution but raises security concerns. This paper introduces DEDUCT, a new method that combines cloud-side and client-side deduplication to achieve high data compression while protecting data privacy. Designed for devices with limited resources, such as IoT devices, DEDUCT includes lightweight preprocessing and safeguards against security risks like side-channel attacks. Testing on a navigation dataset shows that DEDUCT can compress data by up to 66%, significantly cutting storage costs while keeping data secure, making it an efficient choice for managing large-scale data systems. KeyWords: :Blockchain, Artificial Intelligence, Land Registration, Agriculture, Fraud Detection, Smart Contracts, IPFS, Logistic Regression, Support Vector Machine, Random Forest, Data Integrity, Scalability, AgriSafe.

In this work, an oblivious transfer with complex access control scheme that is constructed based on ciphertext policy attribute based encryption (CP-ABE) scheme is proposed. In this scheme, the database server can enforce fine grained access control for each record where the authorized user is allowed to access, but the unauthorized user cannot, whereas it learns neither which record a user accesses, nor which attributes a user has. This scheme has the advantages as follows: First, it allows the expressive access control policies where access structures are based on linear secret sharing scheme that directly supports AND, OR and Threshold gates. Second, the communication complexity in this scheme is constant in the numbers of records which have been accessed. Third, this scheme is constructed in prime order bilinear group. Fourth, this scheme is secure in the standard model. To the best of our knowledge, this scheme is the first to obtain these features simultaneously.

For enterprise systems running on public clouds in which the servers are outside the control domain of the enterprise, access control that was traditionally executed by reference monitors deployed on the system servers can no longer be trusted. Hence, a self-contained security scheme is regarded as an effective way for protecting outsourced data. However, building such a scheme that can implement the access control policy of the enterprise has become an important challenge. In this paper, we propose a self-contained data protection mechanism called RBAC-CPABE by integrating role-based access control (RBAC), which is widely employed in enterprise systems, with the ciphertext-policy attribute-based encryption (CP-ABE). First, we present a data-centric RBAC (DC-RBAC) model that supports the specification of fine-grained access policy for each data object to enhance RBAC’s access control capabilities. Then, we fuse DC-RBAC and CP-ABE by expressing DC-RBAC policies with the CP-ABE access tree and encrypt data using CP-ABE. Because CP-ABE enforces both access control and decryption, access authorization can be achieved by the data itself. A security analysis and experimental results indicate that RBAC-CPABE maintains the security and efficiency properties of the CP-ABE scheme on which it is based, but substantially improves the access control capability. Finally, we present an implemented framework for RBAC-CPABE to protect privacy and enforce access control for data stored in the cloud.

Electronic health record (EHR) allows patients to use an open channel (ie, Internet) to control, share and manage their health records among family members, healthcare providers and other third party data users. Thus, in such an environment, privacy, confidentiality, and data consistency are the major challenges. Although cloud‐based EHR addresses the aforementioned discussions, these are prone to various malicious attacks, trust management and non‐repudiation among servers. Recently, due to the property of immutability, blockchain technology has been introduced to be as an auspicious solution for achieving EHR sharing with privacy and security preservation. Motivated by the above debates, we present BFHS, a blockchain‐based fine‐grained secure EHR sharing mechanism. On BFHS, we encrypt the EHR using ciphertext‐policy attribute‐based encryption (CP‐ABE) and upload it to the interplanetary file system (IPFS) for storage, while the matching index is encrypted via proxy re‐encryption and kept in a medical consortium blockchain. In addition, we created a credit assessment mechanism and incorporated it into the smart contract. Smart contracts, proxy re‐encryption, a credit evaluation mechanism, and IPFS all work together to give patients with a trustworthy EHR sharing environment and a dynamic access control interface. The thorough comparison and experimental analysis show that the proposed BFHS has more comprehensive security features and is more practicable.

The control instructions of industrial control systems are prone to threats such as unauthorized access and tampering during transmission and interaction, and access control is a fundamental method to protect data security. Due to the cyber-physical integration and availability constraints in industrial control systems, existing access control methods cannot be directly applied. In this paper, we propose an access control policy for control instructions based on the ciphertext policy attribute-based encryption (CP-ABE) under the availability constraints in industrial control systems. First, we analyze the abnormal behaviors of control instructions in process industrial monitoring systems, and model the attributes associated with field control business and integrate them into CP-ABE to achieve fine-grained access control and avoid non-compliant operations. Second, we adopt a trusted computing mechanism to protect the identity trustworthiness of the transmission node; the confidentiality of the transmitted control instruction is guaranteed by the negotiated symmetric key and the key authorization is realized by the CP-ABE. We further optimize the measuring frequency of the trusted measurement and the deployment policy of the access control method to guarantee business availability. Finally, we conduct formal analysis and experimental validation of the proposed method, and the results show that the proposed access control policy can prevent unauthorized access and non-compliant tampering by industrial control devices and achieve trustworthy delivery of control instructions with controlled computational complexity.

Lattice-based Attribute-based encryption is a well-known cryptographic mechanism that can resist quantum attacks and has the ability of fine-grained access control, and it has a wide range of application scenarios in current Internet of Thing (IoT) era. However, lack of efficiency and existing the problem of large ciphertext expansion rate are the main disadvantages impede the applications of this mechanism. Thus, we propose an efficient and practical ciphertext policy attribute-based encryption (CP-ABE) scheme from lattices in the paper. In this scheme, to make the secret key reusable, we adjust access tree and propose a basic access tree structure, which can be converted from disjunctive normal form, and combine it with a light post-quantum scheme of Kyber. In addition, the compression method and plaintext expansion method are introduced to optimize the scheme. Our CP-ABE scheme is secure against chosen plaintext attack under the hardness of module learning with errors problem. We implement our scheme and compare it with three recent related schemes in terms of security, function and communication cost. Experiments and comparisons show that our CP-ABE scheme has advantages in high encryption efficiency, small matrix dimension, small key sizes, and low ciphertext expansion rate, which has some merit in practice.

Traditional access control mechanisms prevent illegal access by controlling access right before executing an action; they belong to a class of a priori security solutions and, from this point of view, they have some limitations, like inflexibility in unanticipated circumstances. By contrast, a posteriori mechanisms enforce policies not by preventing unauthorized access, but rather by deterring it. Such access control needs evidence to prove violations. Evidence is derived from one or several log records, which trace each user's actions. Efficiency of violation detection mostly depends on the compliance of log records with the access control policy. In order to develop an efficient method for finding these violations, we propose restructuring log records according to a security policy model. We illustrate our methodology by applying it to the healthcare domain, taking care of the IHE (Integrating the healthcare enterprise) framework, particularly its basic security profile, ATNA (Audit Trail and Node Authentication). This profile defines log records established on the analysis of common health practice scenarios. We analyze and establish how ATNA log records can be refined in order to be integrated into an a posteriori access and usage control process, based on an expressive and contextual security policy like the OrBAC policy.

Recently, most of the Internet of things (IoT) infrastructures are highly centralized with single points of failure, which results in serious security and privacy issues of IoT data. Fortunately, blockchain technique can provide a decentralized and secure IoT framework to deal with security issues based on the characteristics of decentralization, non-tampering, openness, transparency, and traceability. However, the blockchain consensus protocol guarantees the safety and reliability of data, but it also brings problems such as scalability limitations and poor storage extensibility, resulting in the inability to directly integrate blockchain and the IoT in existing conditions. In this article, a private three-tier local blockchain, Three-tier architecture Blockchain (TBchain), is proposed to solve the problem by splitting part of the transactions in the public blockchain and locking them in a higher-level blockchain TBchain. Additionally, the private blockchain TBchain is connected to the public blockchain to build a hierarchical blockchain network to provide privacy protection for the IoT data stored on the blockchain. Finally, we implement an IoT framework based on TBchain and the InterPlanetary File System (IPFS) to realize the decentralized IoT, which guarantees the user’s access control right to personal data. Experimental results show that the IoT framework based on TBchain and IPFS realizes the user’s access control right to personal data by verifying in advance to ensure the confidentiality and security of shared data, and improves the security and privacy of IoT data and transactions. Moreover, we prove that the scalability and storage extensibility of the blockchain is positively correlated with the number of data blocks in TBchain.