Blowfish Hybridized Weighted Attribute-Based Encryption for Secure and Efficient Data Collaboration in Cloud Computing

Attribute-based encryption (ABE) for cloud computing access control is reviewed in this article. A taxonomy and comprehensive assessment criteria of ABE are first proposed. In the taxonomy, ABE schemes are assorted into key-policy ABE (KP-ABE) schemes, ciphertext-policy ABE (CP-ABE) schemes, anti-quantum ABE schemes, and generic constructions. In accordance with cryptographically functional features, CP-ABE is further divided into nine subcategories with regard to basic functionality, revocation, accountability, policy hiding, policy updating, multi-authority, hierarchy, offline computation, and outsourced computation. In addition, a systematical methodology for discussing and comparing existing ABE schemes is proposed. For KP-ABE and each type of CP-ABE, the corresponding access control scenario is presented and explained by concrete examples. Specifically, the syntax of ABE is given followed by the adversarial model and security goals. ABE schemes are discussed according to the design strategies and special features and are compared in the light of the proposed assessment criteria with respect to security and performance. Compared to related state-of-the-art survey papers, this article not only provides a broader 12 categories of ABE schemes, but also makes a more comprehensive and holistic comparison. Finally, a number of open research challenges in ABE are pointed out.

In the cloud, for achieving access control and keeping data confidential, the data owners could adopt attribute-based encryption to encrypt the stored data. Users with limited computing power are however more likely to delegate the mask of the decryption task to the cloud servers to reduce the computing cost. As a result, attribute-based encryption with delegation emerges. Still, there are caveats and questions remaining in the previous relevant works. For instance, during the delegation, the cloud servers could tamper or replace the delegated ciphertext and respond a forged computing result with malicious intent. They may also cheat the eligible users by responding them that they are ineligible for the purpose of cost saving. Furthermore, during the encryption, the access policies may not be flexible enough as well. Since policy for general circuits enables to achieve the strongest form of access control, a construction for realizing circuit ciphertext-policy attribute-based hybrid encryption with verifiable delegation has been considered in our work. In such a system, combined with verifiable computation and encrypt-then-mac mechanism, the data confidentiality, the fine-grained access control and the correctness of the delegated computing results are well guaranteed at the same time. Besides, our scheme achieves security against chosen-plaintext attacks under the k-multilinear Decisional Diffie-Hellman assumption. Moreover, an extensive simulation campaign confirms the feasibility and efficiency of the proposed solution.

Some of the most challenging issues in data outsourcing scenario are the enforcement of authorization policies and the support of policy updates. Ciphertext-policy attribute-based encryption is a promising cryptographic solution to these issues for enforcing access control policies defined by a data owner on outsourced data. However, the problem of applying the attribute-based encryption in an outsourced architecture introduces several challenges with regard to the attribute and user revocation. In this paper, we propose an access control mechanism using ciphertext-policy attribute-based encryption to enforce access control policies with efficient attribute and user revocation capability. The fine-grained access control can be achieved by dual encryption mechanism which takes advantage of the attribute-based encryption and selective group key distribution in each attribute group. We demonstrate how to apply the proposed mechanism to securely manage the outsourced data. The analysis results indicate that the proposed scheme is efficient and secure in the data outsourcing systems.

Security concerns have been rapidly increasing because of repeated security incidents such as unexpected personal information leakage. Since XML [38] has been playing an important role in IT systems and applications, a big surge of requirements for legislative compliance is driving enterprises to protect their XML data for secure data management as well as privacy protection, and the access control mechanism is a central control point. In this chapter, we are concerned with fine-grained (element- and attribute-level) access control for XML database systems, rather than with document-level access control. We use the term XML access control to address such fine-grained access control. The XML access control deals with XML data and access control policies as well as schema definitions, e.g. XML Schema [40], and queries, e.g. XQuery [36]. The scope of XML access control is not limited to a specific application but covers broader areas that involve XML-based transactional systems such as e-commerce applications (Commerce XML [7] etc.), medical and health record applications (HL7 [16] etc.), and newspaper article distribution and applications (NewsML [17] etc.).

Disclosure of sensitive data leads to identity theft and violation of privacy. The untrusted cloud service provider (CSP) may try to disclose/misuse the data. It is necessary to provide access control and security over the outsourced and shared data to hide it from the CSP and unauthorized users. Traditional access control schemes are prone to security threats in the cloud environment. Attribute-based access control schemes (ABAC) are well suited for the cloud environment. Attribute-based encryption (ABE) is a promising cryptographic solution to provide fine-grained access control over the shared data. It selectively shares the data among the users and hides data from the CSP and unauthorized users. It preserves the privacy of users and the security of data being shared. Users can decrypt the data only if their attributes are satisfied with the access policy associated in the ciphertext. This paper presents a comprehensive survey of the ABE schemes. Taxonomy, performance comparison, and applications of ABE schemes are dealt with. The taxonomy and performance comparison help the selection of the most suitable ABE scheme based on specific usage scenarios. Thus, the survey opens up very interesting avenues for further research in this area, which are also discussed.

Revocable attribute-based access control in mutli-autority systems

Most data nowadays are stored in the cloud; therefore, cloud computing and its extension—fog computing—are the most in-demand services at the present time. Cloud and fog computing platforms are largely used by Internet of Things (IoT) applications where various mobile devices, end users, PCs, and smart objects are connected to each other via the internet. IoT applications are common in several application areas, such as healthcare, smart cities, industries, logistics, agriculture, and many more. Due to this, there is an increasing need for new security and privacy techniques, with attribute-based encryption (ABE) being the most effective among them. ABE provides fine-grained access control, enables secure storage of data on unreliable storage, and is flexible enough to be used in different systems. In this paper, we survey ABE schemes, their features, methodologies, benefits/drawbacks, attacks on ABE, and how ABE can be used with IoT and its applications. This survey reviews ABE models suitable for IoT platforms, taking into account the desired features and characteristics. We also discuss various performance indicators used for ABE and how they affect efficiency. Furthermore, some selected schemes are analyzed through simulation to compare their efficiency in terms of different performance indicators. As a result, we find that some schemes simultaneously perform well in one or two performance indicators, whereas none shines in all of them at once. The work will help researchers identify the characteristics of different ABE schemes quickly and recognize whether they are suitable for specific IoT applications. Future work that may be helpful for ABE is also discussed.

Hierarchical attribute-based encryption and scalable user revocation for sharing data in cloud servers

In this paper, a variety of cloud service combinations is used to form the control core of a smart home, realize data forwarding, storage, and analysis in the cloud, and complete the remote management of smart home devices. This paper studies the secure access control of smart home data combined with the blockchain technology and password technology to realize the secure and efficient access control of smart home data. The system can achieve the goal of independent research and development. Aiming at the problem that the access control of a smart home is generally managed by third‐party authorized institutions and there is an unauthorized access, a blockchain‐based smart home (BSH) access control scheme is proposed. The scheme extends the attribute‐based access control model (ABAC) and applies the blockchain technology to the smart home ABAC model to realize fine‐grained access control. In the scheme, the resource provider first publishes the access control policy of the resource to the blockchain. If the resource visitor wants to access the resource, he needs to submit an access request to the blockchain and use an SM2 threshold signature to process the transaction proposal. The endorsement peer node in the blockchain runs the access control policy smart contract to decide whether to grant access rights. This scheme can ensure that resource providers can participate in all the processes of access control and avoid the risk of unauthorized access caused by the centralized management of the third party. Finally, the simulation experiment is carried out on the Hyperledger Fabric alliance chain development platform. The results show that the BSH access control scheme has good applicability in the smart home scenario.

Attribute-based encryption has been widely employed to achieve data confidentiality and fine-grained access control in cloud storage. To enable users to identify accessible data in numerous dataset, clear attributes should be appended to the ciphertext, which results in the exposure of attribute privacy. In this paper, we propose an efficient attribute-based access control with authorized search scheme (EACAS) in cloud storage by extending the anonymous key-policy attribute-based encryption (AKP-ABE) to support fine-grained data retrieval with attribute privacy preservation. Specifically, by integrating the key delegation technique into AKP-ABE, EACAS enables data users to customize search policies based on their access policies, and generate the corresponding trapdoor using the secret key granted by the data owner to retrieve their interesting data. In addition, a virtual attribute with no semantic meaning is utilized in data encryption and trapdoor generation to empower the cloud to perform an attribute-based search on the outsourced ciphertext without knowing the underlying attributes or outsourced data. The data owners can achieve fine-grained access control on their outsourced data, and the data users are flexible to search their interesting data based on protected attributes through customizing the search policies. Finally, we demonstrate that EACAS is more efficient than existing solutions on computation and storage overheads.

Verifiable outsourcing EMRs scheme with attribute-based encryption in cloud-edge environments

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.

Nowadays, several universities and institutions make profit from the information technologies to enhance and develop their educational strategies and attract more learners. Therefore, distance learning (e-learning) and learning-on-the-go are technologies adopted by universities and service providers to afford more flexible education system. In fact, e-learning is gaining popularity worldwide and the number of learners enrolled in on-line courses is growing. This trend is explained mainly by the opportunities provided by Cloud Computing. In the cloud based educational context, the security factor in sharing the educational content is important and poses several security challenges, such as fine-grained access control and security preservation of content learning. Moreover, there is emergence of the new concept of User-Fog-Cloud architecture to bring closer the services to the client. In this paper, a new fog computing e-learning scheme is provided. Specifically, the proposed solution extends learning content from the cloud to the edge of the network. It can improve the efficiency of learning data analysis, reduces the encryption burden in terms of computation cost on user's devices by offloading part of encryption cost to fog servers and provides fine grained access control to learning content by encrypting the course and the exam with different cryptographic techniques like IBBE and CP-ABE. Further, we present a profile matching mechanism that helps teachers to find colleagues within their vicinity in an efficient and secure way. Security analysis shows that our scheme can achieve data confidentiality, fine-grained access control, collusion resistance and unforgeability. Performance evaluations demonstrate the efficiency of our solution, especially in terms of encryption computation costs.

Attribute-based encryption (ABE) has been envisioned as a promising cryptographic primitive for realizing secure and flexible access control. However, ABE is being criticized for its high scheme overhead as extensive pairing operations are usually required. In this paper, we focus on improving the efficiency of ABE by leveraging a previously overlooked fact, i.e., the often-found hierarchical relationships among the attributes that are inherent to many access control scenarios. As the first research effort along this direction, we coin the notion of hierarchical ABE (HABE), which can be viewed as the generalization of traditional ABE in the sense that both definitions are equal when all attributes are independent. We further give a concrete HABE construction considering a tree hierarchy among the attributes, which is provably secure. More importantly, our construction exhibits significant improvements over the traditional ABE when attribute hierarchies exist.

The rapid adoption of cloud computing has transformed the way data is stored, shared, and accessed across organizationsand individuals. Despite its scalability and cost efficiency, cloud storage introduces serious security and privacy challenges, particularly when sensitive data is outsourced to third-party cloud service providers. Traditional access control mechanisms often rely on the cloud provider’s trustworthiness, which may expose data to unauthorized access, insider threats, and data breaches. To address these concerns, CryptCloud+ is proposed as a secure and expressive data access control framework that enforces fine-grained authorization directly through cryptographic techniques. CryptCloud+ focuses on ensuring data confidentiality while enabling flexible and policy-driven access control over encrypted cloud data. The system leverages encryption-based access control, where data is encrypted before being uploaded to the cloud, and only authorized users possessing valid cryptographic credentials can decrypt and access the data. This approach eliminates the need to trust the cloud service provider, as all sensitive operations related to data access are handled at the client side. A key contribution of CryptCloud+ is its support for expressive access policies, allowing data owners to define complex rules based on user attributes such as roles, departments, access levels, or time constraints. These policies enable fine grained access control without requiring data owners to manage individual permissions manually. The framework ensures that users can access only the data they are authorized for, while unauthorized users, including cloud administrators, are unable to infer any meaningful information from the encrypted data. The proposed system is implemented using Python, taking advantage of its robust cryptographic libraries, simplicity, and integration capabilities. Python-based modules handle key generation, encryption, decryption, and policy enforcement, making the system modular and easy to extend. The implementation demonstrates how secure key management and attribute-based access enforcement can be achieved efficiently in a real-world cloud environment. CryptCloud+ also addresses scalability and performance concerns by minimizing computation overhead during data access. Encryption and decryption operations are optimized to ensure that system performance remains practical even as the number of users and data files increases. Experimental results indicate that the framework maintains strong security guarantees while providing acceptable response times for authorized users. In addition to security, the system enhances usability by allowing seamless data sharing among multiple users without re encrypting data for each individual. This significantly reduces management complexity for data owners while preserving strict access control policies. The system design ensures compatibility with existing cloud storage services, making itadaptable to various deployment scenarios. Overall, CryptCloud+ presents a secure, flexible, and effiient solution for cloud data access control. By combining cryptographic enforcement with expressive policy definition and Python-based implementation, the frameworkstrengthens data security, protects user privacy, and improves trust in cloud storage systems. The proposed model demonstrates the feasibility of practical, cryptography-driven access control for modern cloud environments.