Sealed computation: a mechanism to support privacy-aware trustworthy cloud service

2019 ◽  
Vol 27 (5) ◽  
pp. 601-620
Author(s):  
Lamya Abdullah ◽  
Juan Quintero
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Data Privacy ◽  
International Workshop ◽  
Cloud Service ◽  
Security And Privacy ◽  
User Requirement ◽  
Content Type ◽  
Single Entity ◽  
Preliminary Version

Purpose The purpose of this study is to propose an approach to avoid having to trust a single entity in cloud-based applications. In cloud computing, data processing is delegated to a remote party for efficiency and flexibility reasons. A practical user requirement usually is data privacy; hence, the confidentiality and integrity of data processing needs to be protected. In the common scenarios of cloud computing today, this can only be achieved by assuming that the remote party does not in any form act maliciously. Design/methodology/approach An approach that avoids having to trust a single entity is proposed. This approach is based on two concepts: the technical abstraction of sealed computation, i.e. a technical mechanism to confine a privacy-aware processing of data within a tamper-proof hardware container, and the role of an auditing party that itself cannot add functionality to the system but is able to check whether the system (including the mechanism for sealed computation) works as expected. Findings Discussion and analysis of the abstract, technical and procedural requirements of these concepts and how they can be applied in practice are explained. Originality/value A preliminary version of this paper was published in the proceedings of the second International Workshop on SECurity and Privacy Requirements Engineering (SECPRE, 2018).

Perception of cloud computing in developing countries

2016 ◽  
Vol 65 (1/2) ◽  
pp. 33-51 ◽  
Author(s):  
Mayank Yuvaraj
Keyword(s):  
Cloud Computing ◽  
Academic Libraries ◽  
Data Privacy ◽  
Service Providers ◽  
Cloud Service ◽  
Survey Method ◽  
Technological Advancement ◽  
Content Type ◽  
Computing Paradigm ◽  
Library Professionals

Purpose – The purpose of this paper is to explore the perceptions of librarians engaged in Indian academic libraries towards cloud computing. Design/methodology/approach – A structured questionnaire was used to collect responses from the library professionals engaged in Indian academic libraries. Overall, 339 respondents participated in the survey. Descriptive survey method was used in the study. Findings – The findings of the study reveal that library professionals are using cloud-computing tools in their daily works. They want to adopt cloud computing in the libraries to improve library services and avoid redundancy of works. Ubiquitous availability, economy and the various service layers are the core drivers of its adoption in the libraries. The respondents showed their concern over security and data privacy in cloud. Practical implications – The study establishes the fact that the benefits of cloud computing are inadequate to convince the libraries to migrate from the traditional computing paradigm to the cloud. Technological advancement may not transform the cloud into a mainstream technology. To motivate the expansion of cloud computing adoption, emphasis has to be laid upon collaboration between the cloud service providers supplemented by solid cloud legislations which need to be worked out. Originality/value – The paper provides the perceptions of library professionals in response to the adoption of cloud computing.

scholarly journals Improvement of Privacy and Security in Hybrid Cloud with Attribute Group Based Access Control

2019 ◽  
pp. 57-61
Author(s):  
Kayalvili S ◽  
Sowmitha V
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Security Requirements ◽  
Security And Privacy ◽  
Data Outsourcing ◽  
Privacy And Security ◽  
Control Approach

Cloud computing enables users to accumulate their sensitive data into cloud service providers to achieve scalable services on-demand. Outstanding security requirements arising from this means of data storage and management include data security and privacy. Attribute-based Encryption (ABE) is an efficient encryption system with fine-grained access control for encrypting out-sourced data in cloud computing. Since data outsourcing systems require flexible access control approach Problems arises when sharing confidential corporate data in cloud computing. User-Identity needs to be managed globally and access policies can be defined by several authorities. Data is dual encrypted for more security and to maintain De-Centralization in Multi-Authority environment.

scholarly journals eHealth Cloud Security Challenges: A Survey

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yazan Al-Issa ◽  
Mohammad Ashraf Ottom ◽  
Ahmed Tamrawi
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Energy Savings ◽  
Service Providers ◽  
Healthcare Providers ◽  
Cloud Service ◽  
Cloud Security ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Sensitive Data

Cloud computing is a promising technology that is expected to transform the healthcare industry. Cloud computing has many benefits like flexibility, cost and energy savings, resource sharing, and fast deployment. In this paper, we study the use of cloud computing in the healthcare industry and different cloud security and privacy challenges. The centralization of data on the cloud raises many security and privacy concerns for individuals and healthcare providers. This centralization of data (1) provides attackers with one-stop honey-pot to steal data and intercept data in-motion and (2) moves data ownership to the cloud service providers; therefore, the individuals and healthcare providers lose control over sensitive data. As a result, security, privacy, efficiency, and scalability concerns are hindering the wide adoption of the cloud technology. In this work, we found that the state-of-the art solutions address only a subset of those concerns. Thus, there is an immediate need for a holistic solution that balances all the contradicting requirements.

scholarly journals Structural equation modeling in cloud computing studies: a systematic literature review

Kybernetes ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 982-1019
Author(s):  
Erhan Pişirir ◽  
Erkan Uçar ◽  
Oumout Chouseinoglou ◽  
Cüneyt Sevgi
Keyword(s):  
Cloud Computing ◽  
Structural Equation Modeling ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Structural Equation ◽  
Security And Privacy ◽  
Equation Modeling ◽  
Content Type ◽  
Current State ◽  
Sem Studies

Purpose This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design. Design/methodology/approach Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions. Findings A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors. Originality/value Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.

The adoption of cloud computing in small and medium enterprises: a developing country perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abul Khayer ◽  
Nusrat Jahan ◽  
Md. Nahin Hossain ◽  
Md. Yahin Hossain
Keyword(s):  
Cloud Computing ◽  
Firm Performance ◽  
Small And Medium Enterprises ◽  
Security And Privacy ◽  
Content Type ◽  
Cloud Computing Adoption ◽  
Effort Expectancy ◽  
Toe Framework ◽  
Medium Enterprises ◽  
Organisational Agility

Purpose The purpose of this paper is to examine the determinants of cloud computing adoption in small and medium enterprises (SMEs), further, to measure the effect of cloud computing adoption on cloud-supported firm performance through enhancing organisational agility. Design/methodology/approach The research model is developed by combining two popular theoretical models, namely, the unified theory of acceptance and use of technology (UTAUT) and the technology–organisation–environment (TOE) framework. Data are collected from 372 SMEs to test the model. The strengths of widely used structural equation modelling (SEM) are applied to analyse the data. Findings This study reveals that the significant predictors of cloud computing adoption are performance expectancy; effort expectancy; absorptive capacity; data security and privacy; and perceived trust. Also, cloud computing adoption positively influences firm performance directly and through organisational agility. The results of importance–performance map analysis indicate that effort expectancy falls in the critical zone, which needs to be improved. Originality/value This research is one of few that blends the strengths of UTAUT and TOE framework. The research outcomes yield noteworthy suggestions to cloud providers, managers and government policymakers on ways of motivating the spread of cloud computing in developing countries.

IoT ecosystem faces fragmented future

2019 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Internet Of Things ◽  
Data Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Content Type ◽  
Iot Devices ◽  
The Internet Of Things

Subject IoT ecosystem. Significance The market for the Internet of Things (IoT) or connected devices is expanding rapidly, with no manufacturer currently forecast to dominate the supply chain. This has fragmented the emerging IoT ecosystem, triggering questions about interoperability and cybersecurity of IoT devices. Impacts Firms in manufacturing, transportation and logistics and utilities are expected to see the highest IoT spending in coming years. The pace of IoT adoption is inextricably linked to that of related technologies such as 5G, artificial intelligence and cloud computing. Data privacy and security will be the greatest constraint to IoT adoption.

Research of Distributional Ecology Cloud-Structure

2013 ◽  
Vol 760-762 ◽  
pp. 1758-1761
Author(s):  
Ji Ming Lan ◽  
Shu Jie Lu ◽  
Li Ming Zhang
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Real Time ◽  
Service Management ◽  
Cloud Model ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Structure ◽  
Mass Data ◽  
Multiple Dimension

Proposed that idea of cloud computing ecology development, supports and guiding cloud model deployment, the cloud service management and Clouds protocols observes the purification of mix cloud environment. Has designed the multiple dimension data saving structure and real-time mass-data processing of model as well as the asynchronous overall construction distributional ecology cloud structure. It has been shown that this ecology cloud structure is healthy.

scholarly journals Cloud Computing Cloud Computing in Remote Sensing : High Performance Remote Sensing Data Processing in a Big data Environment

2021 ◽  
Vol 16 (6) ◽  
Author(s):  
Yassine Sabri ◽  
Aouad Siham
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Data Processing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Remote Sensing Data ◽  
Cloud Service ◽  
Intermediate Data ◽  
High Level

Multi-area and multi-faceted remote sensing (SAR) datasets are widely used due to the increasing demand for accurate and up-to-date information on resources and the environment for regional and global monitoring. In general, the processing of RS data involves a complex multi-step processing sequence that includes several independent processing steps depending on the type of RS application. The processing of RS data for regional disaster and environmental monitoring is recognized as computationally and data demanding.Recently, by combining cloud computing and HPC technology, we propose a method to efficiently solve these problems by searching for a large-scale RS data processing system suitable for various applications. Real-time on-demand service. The ubiquitous, elastic, and high-level transparency of the cloud computing model makes it possible to run massive RS data management and data processing monitoring dynamic environments in any cloud. via the web interface. Hilbert-based data indexing methods are used to optimally query and access RS images, RS data products, and intermediate data. The core of the cloud service provides a parallel file system of large RS data and an interface for accessing RS data from time to time to improve localization of the data. It collects data and optimizes I/O performance. Our experimental analysis demonstrated the effectiveness of our method platform.

scholarly journals Secure Distributed Data using Multi-Cloud

2020 ◽  
Vol 9 (4) ◽  
pp. 2998-3003
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Cloud Service ◽  
Security And Privacy ◽  
Distributed Data ◽  
Second Stage ◽  
The Third ◽  
Third Stage ◽  
Three Stages ◽  
Access To Data

Implementing cloud computing provides many paths for web-based service. But, data security and privacy requirement become an important problem that limits several cloud applications. One of the key security and privacy concerns is the fact that cloud service suppliers have access to data. This concern greatly reduces the usability of cloud computing in many areas, such as financial business and government agencies. This paper focuses on this important issue and suggests a new approach, so cloud providers cannot directly access data. The proposed approach is divided into two sides: upload side and download side. In upload side, there is three stages, at the first stage; the transmitted file is splitted and then encrypted in order to achieve the data security requirement. At the second stage, the splitted data are integrity checked by MD5 algorithm, in order to achieve integrity requirement. At the third stage, the checked splitted data are stored separately in three -clouds, in order to achieve distribution requirement. In download side, also there is three stages. At the first stage, the data is retrieved from the three-clouds. At the second stage, data integrity is performed using MD5. At the third stage, data decryption and merging are done. The proposed approach is successfully implemented on (25 KB) image. The proposed model is successfully implemented in uploading side dependent on shares3 because provide high security with total time of (8.144 sec), and in downloading side with total side of (9.42).

Sign in / Sign up

Export Citation Format

Share Document