Attribute-based data access control in mobile cloud computing: Taxonomy and open issues

In mobile cloud computing (MCC), data are stored and processed by more powerful computing platforms located in clouds to enhance the capability of mobile devices. Although MCC brings many benefits to users and organizations, security has become the main concern for MCC because it involves third party environment where data confidentiality is not a guarantee. To overcome this challenge, attribute-based encryption (ABE) technique, a promising cryptography method was introduced to support both data confidentiality and access control simultaneously. However, most of the ABE used single certification authority (CA) and disjoint attribute authority (AA) to verify user identity which can be a single point of failure. Therefore, a new approach was proposed in this research to deal with the single point of failure in the authority. Furthermore, the cache-based scheduling algorithm was upgraded to improve the response time of user jobs. The experimental results show that the approach performed better compared to its competitor in terms of reliability. Additionally, it significantly reduced the number of read operations compared to its counterpart.

Secure and quality-of-service-supported service-oriented architecture for mobile cloud handoff process

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.

The mode of outsourcing brings about new challenges for data security and access control in cloud computing. Ciphertext-Policy Attribute-based Encryption (CP-ABE) is considered to be a powerful tool for protecting data confidentiality in cloud storage system. Due to the large scale of cloud, there are many independent domains. It is impossible for a single authority to issue attributes to all of the users. In addition, single authority could be the bottleneck of system. Attribute revocation has always been the primary difficulty in ABE. In this paper, we propose a multi-authority cloud access scheme with mixed access structure to support universal attribute and more flexible access control in multi-authority cloud storage system. After adding owner-defined attribute to traditional access structure, owner can decide which user has the right to access data. Two kinds of revocation methods can provide real-time privilege updating in multi-authority system. Detailed security analysis shows that the proposed MMACS scheme meets the security requirements under existing security models. Performance evaluation also demonstrates its highly efficient in attribute revocation.

The widespread use of smartphones and other mobile devices has brought significant changes to the storage requirements of cloud systems, necessitating a reevaluation of security protocols. Mobile Cloud Computing (MCC) is a computing paradigm that combines the capabilities of mobile devices with the flexibility and scalability of cloud computing. MCC allows mobile users to access computational power, storage, and applications over the internet, facilitating resource-intensive tasks such as data analysis, gaming, and multimedia streaming on resource-constrained mobile devices. The integration of mobile and cloud technologies has revolutionized industries such as healthcare, education, and entertainment, offering benefits like enhanced mobility, improved resource utilization, and cost efficiency. Despite its advantages, MCC faces significant security challenges that could undermine user trust and disrupt its adoption. Since mobile devices and cloud servers are connected via insecure networks, malicious actors can exploit vulnerabilities in the system. This paper aims to analyze the primary security issues in MCC technology, focusing on data protection, authentication, access control, and other critical concerns. Unlike other issues, when dealing with business objectives, protection and privacy in financial activities are of paramount importance. This article examines mobile cloud computing, its technological model, and its role in detail. Keywords: Mobile cloud computing, Technology, Privacy issues, Security.

Data access control is an effective way to ensure the data security in the cloud. Due to data outsourcing and untrusted cloud servers, the data access control becomes a challenging issue in cloud storage systems. Ciphertext-Policy Attribute-based Encryption (CP-ABE) is regarded as one of the most suitable technologies for data access control in cloud storage, because it gives data owners more direct control on access policies. However, it is difficult to directly apply existing CP-ABE schemes to data access control for cloud storage systems because of the attribute revocation problem. In this paper, we design an expressive, efficient and revocable data access control scheme for multi-authority cloud storage systems, where there are multiple authorities co-exist and each authority is able to issue attributes independently. Specifically, we propose a revocable multi-authority CP-ABE scheme, and apply it as the underlying techniques to design the data access control scheme. Our attribute revocation method can efficiently achieve both forward security and backward security. The analysis and simulation results show that our proposed data access control scheme is secure in the random oracle model and is more efficient than previous works.

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.

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.

Cloud computing involves multidisciplinary development and integration, and is the result of information technology and related applications. In this study, Web of Science Core Collection database is used as data source. Using Excel, Bibexcel, VOSviewer and CiteSpace software for data mining and quantitative analysis of the 2005–2018 year research papers on cloud computing, we explore the trend of change, the distribution of research forces, key areas, research hot spots and international cooperation. The results show that the number of documents in cloud computing has been growing, and there are many subjects involved in the research of cloud computing technology, mainly Computer Science, Engineering and Telecommunications. There are many research papers on cloud computing in China and the United States; China is most prominent in international cooperation and has strong cooperative relations with the major countries; Chinese Academy of Sciences is very active in the research of cloud computing, and its papers are far ahead of other institutions. The main focuses of the study are virtualization, mobile cloud computing, big data, security, etc. The main hot spots of research are mobile cloud computing, big data, fog computing, secure, storage, access control, sever consolidation, etc.

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.

Software defined networking (SDN) separates the data layer and the control layer to achieve logical centralization, scalability and programmability. In hierarchical software defined networking (HSDN), controllers are classified into the upper controller- Root Controller (RC) and the lower controller- Local Controller (LC) to improve the scalability of the network. HSDN effectively relieve the workload of controllers. However, the features of HSDN puts forward higher requirements of data privacy protection and access control. Because RC stores global network data, it must ensure authorized access and prevent the forged data. The attribute-based encryption scheme can provide fine-grained data access control and data privacy protection of controllers at the same time. When LC accesses data in RC, the algorithm of ciphertext-policy attribute-based encryption with identity authentication (CP-ABE-IA) is presented to protect the data privacy of RC and guarantee the legitimate access of LC. When LC sends message to RC, we propose an algorithm of key-policy attribute based signcryption for multi-access structures (KP-ABSC-MAS). KP-ABSC-MAS provides data privacy protection and verification as well as the authentication of LC.

Mobile cloud computing (MCC) is a technique or model, in which mobile applications are built, powered and hosted using cloud computing technology. It refers to the availability of Cloud Computing services in a mobile environment and it is the combination of the heterogeneous fields like mobile phone device, cloud computing and wireless networks. Of all that has been written about cloud computing, precious little attention has been paid to authentication in the cloud. In this paper we have designed a new effective security model for mobile cloud Database as a Service (DBaaS). A user can change his/her password, whenever demanded. Furthermore, security analysis realizes the feasibility of the proposed model for DBaaS and achieves efficiency. We also proposed an efficient authentication scheme to solve the authentication problem in MCC. The proposed solution which we have provided is based mainly on improved Needham-Schroeder’s protocol to prove the users’ identity to determine if this user is authorized or not. The results showed that this scheme is very strong and difficult to break it.

Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients' control over access to their own PHRs, it is a promising method to encrypt the PHRs before outsourcing. Yet, issues such as risks of privacy exposure, scalability in key management, flexible access, and efficient user revocation, have remained the most important challenges toward achieving fine-grained, cryptographically enforced data access control. In this paper, we propose a novel patient-centric framework and a suite of mechanisms for data access control to PHRs stored in semitrusted servers. To achieve fine-grained and scalable data access control for PHRs, we leverage attribute-based encryption (ABE) techniques to encrypt each patient's PHR file. Different from previous works in secure data outsourcing, we focus on the multiple data owner scenario, and divide the users in the PHR system into multiple security domains that greatly reduces the key management complexity for owners and users. A high degree of patient privacy is guaranteed simultaneously by exploiting multiauthority ABE. Our scheme also enables dynamic modification of access policies or file attributes, supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios. Extensive analytical and experimental results are presented which show the security, scalability, and efficiency of our proposed scheme.

Mobile cloud computing (MCC) is the availability of cloud computing services in a mobile environment. By providing optimal services for mobile users, MCC incorporates the elements of mobile networks and cloud computing. In mobile cloud computing, all the data and complicated computing modules can be processed in clouds, and mobile devices do not need a powerful configuration like CPU speed, memory capacity, etc. However, the mobile devices are facing up with many struggles in their resources (e.g., battery life, storage, and bandwidth) and communications (e.g., privacy, mobility, and security). These challenges have a significant effect on the improvement of service qualities. In this paper, a literature survey on the MCC and security issues in MCC has presented.

In recent years, mobile networks have faced with the increase of traffic demand. By emerging mobile applications and cloud computing, Mobile Cloud Computing (MCC) has been introduced. In this research, we focus on the 4th and 5th generation of mobile networks. Data Centers (DCs) are connected to each other by high-speed links in order to minimize delay and energy consumption. By considering a model of the geographical distribution of DCs which uses a wideband optical network, renewable energy and sharing resources for new generations of mobile networks, the real effect of issues on the consumed energy, cost, and profit in the mobile cloud computing are investigated. We derived a penalty function for cost and then by using Lyapunov optimization theorem; we designed an algorithm to minimize the average cost of energy consumption based on the online information in MCC. The time average cost is at most O(1/V) above the optimum target, while the average queue size is O(V). The parameter V can be tuned to make the time average cost as close to (or below) the optimum as desired. We designed three scenarios and two classes of applications to set up our simulation environment. The provided results illustrate the efficiency of our proposed scheme and validate the mathematical model.