Search Results (12)

As medical technology develops and digital demands grow, personal health records (PHRs) are becoming more patient-centered than before based on cloud-based health information exchanges. While enhancing data accessibility and sharing, these systems present privacy and security issues, including data breaches and unauthorized access. We developed a post-quantum, group-oriented encryption scheme using the Crystal-Kyber Key encapsulation mechanism (KEM). Leveraging lattice-based post-quantum cryptography, this scheme ensures quantum resilience and chosen ciphertext attack security for layered cloud PHR environments. It supports four encryption modes: individual, group, subgroup-specific, and authorized subgroup decryption, meeting diverse data access needs. With efficient key management requiring only one private key per user, the developed scheme strengthens the privacy and security of PHRs in a future-proof, flexible, and scalable manner. Full article

Data sharing has dramatically promoted the efficient use of data resources. The target sharing of confidential data is increasingly becoming urgent for enterprises or organizations to solve business problems, such as data sharing between group users with the same attribute characteristics. The confidentiality and relative privacy of shared data, whether in plaintext or ciphertext, largely depend on the encryption keys used during the sharing process and the storage security of the sharing platform. In order to solve the problem of secure sharing, this paper proposes a data-sharing scheme based on group attribute characteristics. The sharer segments and encrypts the data and stores most of the data and encryption keys on the cloud platform, while a small part of the residual is stored on the edge server. The sharer specifies group users by defining user attribute values and implements access control of encryption keys and shared data through CP-ABE. In particular, the private servers of the organizations involved in data sharing act as the edge servers, which are responsible for the storage of residuals with the final authorization of data access, and try their best to ensure that the data are shared with the target users. The security analysis and data collection time overhead experiments show that the scheme further guarantees data sharing with specified target users, which is one more layer of guarantee than sharing in multi-cloud environment and cloud-encrypted sharing, and the time overhead has about a 15% improvement over sharing in a multi-cloud environment. Full article

Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) have revolutionised e-learning by creating personalised, adaptive, and secure environments. However, challenges such as privacy, bias, and data limitations persist. E-FedCloud aims to address these issues by providing more agile, personalised, and secure e-learning experiences. This study introduces E-FedCloud, an AI-assisted, adaptive e-learning system that automates personalised recommendations and tracking, thereby enhancing student performance. It employs federated learning-based authentication to ensure secure and private access for both course instructors and students. Intelligent Software Agents (ISAs) evaluate weekly student engagement using the Shannon Entropy method, classifying students into either engaged or not-engaged clusters. E-FedCloud utilises weekly engagement status, demographic information, and an innovative DRL-based early warning system, specifically ID2QN, to predict the performance of not-engaged students. Based on these predictions, the system categorises students into three groups: risk of dropping out, risk of scoring lower in the final exam, and risk of failing the end exam. It employs a multi-disciplinary ontology graph and an attention-based capsule network for automated, personalised recommendations. The system also integrates performance tracking to enhance student engagement. Data are securely stored on a blockchain using the LWEA encryption method. Full article

Even though both internet-of-cloud services and biometric systems (BSs) are used worldwide, popular and expanded among public and private services, their utilization has not been extended among Greek users, and in particular within Greek HEIs. This paper aims to examine the University of the Aegean (UA) students’ perceptions, especially on BS acceptance, determining the impact of their sociodemographic characteristics toward this. An online instrument was developed based on constructs of technology acceptance models, and previous research focused on BS acceptance, including a great variety of sociodemographic variables. The authors collected 768 complete responses to explore the social and demographic attributes that impact on students’ BS acceptance through exploratory descriptive research. This study found that several UA students’ sociodemographic attributes are linked to their BS acceptance. Specifically, gender, age, study level, year of study, professional profile and fathers’ occupation are useful to determine which students’ groups are in favor of BS, while employment status, annual income and mothers’ occupation are weak toward this. Security and privacy concerns are indicated to influence users’ BS acceptance as well. This study provides a unique approach to better understanding the Greek students’ BS acceptance, with important implications for improved BS marketing in Greece in synergy with the internet-of-cloud services and their potential adoption in HEIs internal settings. It also provides developers with further knowledge for security and privacy non-functional requirements in order to increase users’ acceptance and to address these challenges within the internet of cloud. Full article

Cloud storage services are an important application of cloud computing. An increasing number of data owners store their data on cloud platforms. Since cloud platforms are far away from users, data security and privacy protection are very important issues that need to be addressed. Identity-based broadcast encryption (IBBE) is an important method to provide security and privacy protection for cloud storage services. Because the side channel attacks may lead to the disclosure of the key information of the cryptographic system, which will damage the security of the system, this paper provides an identity-based broadcast encryption with leakage resilience by state partition (LR-SP-IBBE). By using a binary extractor to compensate for the loss in entropy of the symmetric key caused by side-channel attacks, the proposed scheme randomizes the encapsulated symmetric key. Furthermore, using a state partition technique, we split the private key into two parts, and the corresponding decryption was divided into two stages. Through the double-system encryption skill, the security and leakage-resilience were proved in the composite order group model. Full article

The extensive use of cloud computing influences changes in managing information technology and communication systems. The term “Cloud Computing” refers to a new management information system that emphasizes the distribution of various computer services across the internet, such as the World Wide Web. Security and privacy concerns and the deployment of resources in shared settings are only a few of the difficulties posed by cloud computing. This study’s overarching goal is to aid Jordanian higher education institutions (JHEIs) in making informed decisions about cloud computing by creating a framework that considers the most important elements influencing adoption. This study, therefore, presents a framework for the adoption of cloud computing in JHEIs by modifying the Diffusion of Innovation (DOI) theory, the Technology Acceptance Model (TAM), and the Technology, Organization, and Environment (TOE) framework. To better understand the elements influencing the adoption of cloud computing in the context of JHEIs, the authors offer a framework they call the Technology-Organization-Environment-Quality of Cloud Computing Adoption (TOEQCC), which builds on the fundamental theories and proposed models. The study aimed to solve the problem of cloud computing adoption at higher educational institutions through suggesting a new framework, which aims to improve the awareness of cloud computing factors as well as the roadmap for the adoption process. Eleven different Jordanian universities (both governmental and private) collaborated on this study. In addition to gathering data from the Jordanian Minister of Higher Education (JMHE) and the Jordanian Higher Education Accreditation Commission, the research team also performed three focus groups with Jordanian students and distributed three hundred questionnaires (JHEAC). NVivo was used to analyze the data following the steps: data reduction, data visualization, and conclusion drawing/verification. Statistics and frequency data are shown in tables, pie charts, bar charts, and column charts. Other tools were employed, such as Microsoft Visio and Microsoft Business Intelligence. Full article

This paper suggests a methodology (conception and principles) for building two-mode monitoring systems (SMs) for industrial facilities and their adjacent territories based on the application of unmanned aerial vehicle (UAV), Internet of Things (IoT), and digital twin (DT) technologies, and a set of SM reliability models considering the parameters of the channels and components. The concept of building a reliable and resilient SM is proposed. For this purpose, the von Neumann paradigm for the synthesis of reliable systems from unreliable components is developed. For complex SMs of industrial facilities, the concept covers the application of various types of redundancy (structural, version, time, and space) for basic components—sensors, means of communication, processing, and presentation—in the form of DTs for decision support systems. The research results include: the methodology for the building and general structures of UAV-, IoT-, and DT-based SMs in industrial facilities as multi-level systems; reliability models for SMs considering the applied technologies and operation modes (normal and emergency); and industrial cases of SMs for manufacture and nuclear power plants. The results obtained are the basis for further development of the theory and for practical applications of SMs in industrial facilities within the framework of the implementation and improvement of Industry 4.0 principles. Full article

Nowadays, the Government as a Platform (GaaP) based on cloud computing and network, has come to be considered a new structure to manage efficiently data-driven administration in the public sector. When the GaaP concept was first introduced, the ICT infrastructures that could underpin GaaP were not sufficiently developed. However, the recent digital transformation has transformed the previous electronic government, which was system- and architecture-oriented. As part of the next generation of government models, GaaP may reinvent the government at a lower cost but with better performance, similar to the case of electronic government two decades ago. This study attempted to determine the priority of factors of GaaP by using the analytic hierarchy process (AHP) methodology. Because of the GaaP characteristics, we drew the main components for building GaaP from previous studies and a group interview with experts. The study results show that experts tend to prefer publicness in terms of building GaaP. Most of the factors that the experts weighed with the highest importance are related to the public sector, which revealed that governments should focus on their primary duty, regardless of the origin and characteristics of the platform in GaaP. However, since GaaP allows governments to be more horizontal and innovative, the platform approach can fundamentally shift the existing processes and culture of the public sector. The enhanced activity of citizens with ICT can also accelerate the introduction of GaaP. Finally, the study showed that a data-driven GaaP is necessary to efficiently handle big data, contract services, and multiple levels of on-line and off-line channels. In this public platform, government, citizens, and private sector organizations can work cooperatively as partners to seamlessly govern the hyper-connected society. Full article

Blockchain technology is a game-changing, enhancing security for the supply chain of smart additive manufacturing. Blockchain enables the tracking and recording of the history of each transaction in a ledger stored in the cloud that cannot be altered, and when blockchain is combined with digital signatures, it verifies the identity of the participants with its non-repudiation capabilities. One of the weaknesses of blockchain is the difficulty of preventing malicious participants from gaining access to public–private key pairs. Groups of opponents often interact freely with the network, and this is a security concern when cloud-based methods manage the key pairs. Therefore, we are proposing end-to-end security schemes by both inserting tamper-resistant devices in the hardware of the peripheral devices and using ternary cryptography. The tamper-resistant devices, which are designed with nanomaterials, act as Physical Unclonable Functions to generate secret cryptographic keys. One-time use public–private key pairs are generated for each transaction. In addition, the cryptographic scheme incorporates a third logic state to mitigate man-in-the-middle attacks. The generation of these public–private key pairs is compatible with post quantum cryptography. The third scheme we are proposing is the use of noise injection techniques used with high-performance computing to increase the security of the system. We present prototypes to demonstrate the feasibility of these schemes and to quantify the relevant parameters. We conclude by presenting the value of blockchains to secure the logistics of additive manufacturing operations. Full article

With the spread of the Internet, the speed of data spread is getting faster and faster. It benefits us a lot but also brings us many potential security problems, especially the problem of privacy leakage. For example, more and more people choose to store their private images in the cloud. Secret image sharing as a significant method has been widely applied in protecting images in the cloud, which reduces the risks of data leakage and data loss. Generally, the secret image sharing scheme would encrypt the secret image into a series of shares and then stored these shares in a cloud. However, when this cloud has been attacked, the secret may meet a risk of leakage. A solution to solve the problem is that the generated shares are distributed storage in multiple clouds. Each cloud is independent and all clouds can have a collaboration to manage the secret image. To address this issue, a novel hierarchical secret image sharing scheme with multi-group joint management is proposed in this paper, which is suitable for protecting the security of the secret image by distributed storage over multiple clouds. In the proposed scheme, the secret image would be shared among multiple groups with different thresholds. The number of each group’s shareholders is determined by a sequence of thresholds. Therefore, the proposed scheme is a hierarchical secret image sharing scheme in which the secret image can be reconstructed if and only if the number of shares has met all threshold conditions. In addition, the generated shares have the same weight, which is more suitable for universal applicability. Both the system analysis and the simulation results prove that the proposed scheme is efficient and practical. Full article

Cryptographic cloud storage (CCS) is a secure architecture built in the upper layer of a public cloud infrastructure. In the CCS system, a user can define and manage the access control of the data by himself without the help of cloud storage service provider. The ciphertext-policy attribute-based encryption (CP-ABE) is considered as the critical technology to implement such access control. However, there still exists a large security obstacle to the implementation of CP-ABE in CCS. That is, how to identify the malicious cloud user who illegally shares his private keys with others or applies his keys to construct a decryption device/black-box, and provides the decryption service. Although several CP-ABE schemes with black-box traceability have been proposed to address the problem, most of them are not practical in CCS systems, due to the absence of scalability and expensive computation cost, especially the cost of tracing. Thus, we present a new black-box traceable CP-ABE scheme that is scalable and high efficient. To achieve a much better performance, our work is designed on the prime order bilinear groups that results in a great improvement in the efficiency of group operations, and the cost of tracing is reduced greatly to $O\left(N\right)$ or $O\left(1\right)$ , where N is the number of users of a system. Furthermore, our scheme is proved secure in a selective standard model. To the best of our knowledge, this work is the first such practical and provably secure CP-ABE scheme for CCS, which is black-box traceable. Full article

Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users’ medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs’ applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs’ deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models. Full article