Using Smart Card to Achieve a Single Sign-on for Multiple Cloud Services

Cloud computing (CC) services can offer substantial cost-effective global operational and relationship benefits if the cooperation between logistics and CC services are resilient. Potential vulnerabilities to cooperation of CC and logistics service providers can occur with respect to vital factors such as security and trust. Extant studies have demonstrated CC benefits as well as few challenges associated with CC services application. However, no extant study has examined the inter-organisational benefits based on cooperative resilience between CC and logistics service providers in terms of both capability and trust vulnerability factors. This study examines the cooperative resilience of logistics and CC service providers based on innovation diffusion theory within a supply chain risk assessment framework. Using structural equation modelling techniques, we investigate the relationship between the vulnerability factor (trust), capability factor (security) and collaboration benefits (relationship and operational) offered by CC service providers based on 236 Chinese logistics service firms’ perceptions of CC adoption. The results indicate Chinese logistics companies perceive security impediments as a major factor affecting cooperative resilience between logistics service and CC service providers.

Moving data and applications to the cloud implies shifting their control from cloud consumers to the cloud service provider (CSP) indefinitely. Hence, the security and privacy (Saamp;P) of the consumers' assets becomes an important issue. Assessing and comparing potential cloud computing (CC) services, poses an issue for CC adopters to choose Saamp;P options that are sufficient and robust at the same time. In this paper, we describe CC adopters' Saamp;P concerns. We identify a set of attributes that reflect various aspects of cloud Saamp;P in an attempt to alleviate those concerns. We classify the attributes based on their tangibility and their relevance to Saamp;P threats. Every attribute in our list is represented by a set of considerations (i.e. polar questions) to assess its quality. We present a tool that embodies our set of attributes. We aim to enable consumers to assess and compare CC services, in terms of Saamp;P, so that they can make well-educated choices. CSPs can also make use of these attributes to offer better cloud Saamp;P.

Cloud computing is a new model for providing computing services, where computing is delivered as a service over the Internet. Cloud computing is a very popular choice among SMEs because computing services are provided at much lower prices compared to their own IT infrastructure. In the cloud computing model, computing services and data storage are outsourced to cloud service providers. Customers do not have full control over applications and their data. Therefore, an added overhead of security risks comes along, and the security of data becomes the primary concern for cloud customers when considering cloud services. This paper explores various deployment models of cloud computing services and IoT (Internet of Things), figures out associated data security issues with them, and suggests a metric-based solution to assess security provided by cloud services.

Cloud computing is a promising computing model that enables convenient and on-demand network access to a shared pool of configurable computing resources. The first offered cloud service is moving data into the cloud: data owners let cloud service providers host their data on cloud servers and data consumers can access the data from the cloud servers. This new paradigm of data storage service also introduces new security challenges, because data owners and data servers have different identities and different business interests. Therefore, an independent auditing service is required to make sure that the data is correctly hosted in the Cloud. In this paper, we investigate this kind of problem and give an extensive survey of storage auditing methods in the literature. First, we give a set of requirements of the auditing protocol for data storage in cloud computing. Then, we introduce some existing auditing schemes and analyze them in terms of security and performance. Finally, some challenging issues are introduced in the design of efficient auditing protocol for data storage in cloud computing.

The recent increase in the use of cloud service has led to the need for cloud service broker(CSB) for supporting the use of various cloud computing platforms. CSB plays the role of not only providing overall services needed for individuals and companies to use cloud computing but also managing and inspecting them. As cloud computing became commonplace, it is expected that the demand for more useful cloud-based service at more affordable prices will increase exponentially. Accordingly, the current situation calls for CSB that connects cloud service provider & customer and provides the service of managing and inspecting cloud service. This paper presents a framework of the components and role of cloud service broker system that supports the allocation, control and management of virtual system based on brokering function between cloud service provider(CSP) and cloud service customer (CSC) by integrating and managing cloud resources in multiple heterogeneous cloud environment. Based on this, it is expected that this paper will contribute to the revitalization of cloud service industry.

BPPIR: Blockchain-assisted privacy-preserving similarity image retrieval over multiple clouds

Background: The integration of mobile computing and cloud computing has the potential to revolutionize healthcare delivery by providing ubiquitous access to resources and enabling new service development and delivery models. While cloud computing has been extensively studied in fields such as genomics and molecular medicine, its application in healthcare beyond these domains remains relatively unexplored. This scoping review aims to identify the current state and emerging research topics in cloud computing in healthcare outside of the traditional “OMICS context.” Methods: A comprehensive search was conducted in MEDLINE in July 2013 and December 2014 using keywords related to cloud computing and cloud-based services. The identified journal and conference articles were independently categorized and summarized by two researchers, who subsequently consolidated their findings. Results: A total of 102 publications were analyzed, revealing six main topics in cloud computing in healthcare: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Common features utilized in these applications included broad network access for data sharing and access, as well as rapid elasticity to meet computing demands. While some articles highlighted the cost-effectiveness of pay-per-use cloud services, only 14 articles reported successful implementations, with many publications focusing on conceptual or prototypic projects. Additionally, several articles equated cloud computing with internet-/web-based data sharing, failing to illustrate the unique benefits of the cloud computing paradigm. Conclusions: Although the integration of mobile computing and cloud computing in healthcare is gaining attention, successful implementations in the field are still limited. Many papers use the term “cloud” interchangeably with “virtual machines” or “web-based” without clearly demonstrating the advantages of the cloud paradigm. Data safety and security concerns associated with involving external cloud partners remain significant barriers to adoption in the healthcare domain. As of now, cloud computing is primarily favored for its individual features, such as elasticity, pay-per-use models, and broad network access, rather than as a comprehensive cloud computing paradigm.

Cloud Computing (CC) is a paradigm shift with the potential of transforming the information and communication technology (ICT) industry. ICT is an integral part of all businesses, and CC helps in lightening the burden of massive ICT investments. Thus, it is essential to understand the factors that influence CC adoption. The purpose of this study is to identify and rank critical factors for CC adoption in the Indian context. The research has adopted mixed methodology (qualitative and quantitative). Experts from 13 organizations (including 8 cloud service providers (CSPs) and 5 cloud service users (CSUs)) are interviewed. Content analysis is used to confirm existing factors and identify new factors in the Indian context. Qualitative analysis has identified four new factors, namely, ‘time to market’, ‘futuristic’, ‘resistance to change’ and ‘financial losses’ (arising from security and resource availability). The quantitative part of the research used analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (FAHP) techniques to rank the factors. The analysis revealed ‘IT service cost’ and ‘time to market’ as the most critical factor through FAHP and AHP respectively. However, ‘organization size’ is reported the least critical for CC adoption through both the methods. The results also highlight divergence among the criticality of CC adoption factors using the two techniques. The study is very useful for CSPs and key decision-makers to understand the critical adoption factors and judiciously strategize for CC service promotions. It will also help users to wisely decide while making CC adoption decision.

Cloud computing provides facilities. These facilities increased demand for its using as institutions and individuals moved to the cloud service. Therefore, cloud service providers must provide services to users based on the expected quality. One of the main challenges presented by the cloud computing is the Quality of Service management. QoS management is defined as allocating resources to applications to ensure service based on reliability, performance and availability. It is necessary to allocate resources based on load balancing that allows avoiding overloading or low loading in virtual machines, and this is a challenge for researchers in the field of cloud computing. This research highlights the importance of cloud computing, its types and importance, It also reviews some researches in the field of quality assurance of service in computing.

Identity-based mutual authentication and key agreement (ID-MAKA) between a mobile user and cloud service provider is necessary for accessing any cloud services. In recent years, there are a large number of ID-MAKA schemes had been proposed on mobile cloud computing services to make authentication and accessing process more usability, security, and scalability. In this paper, we propose a new ID-MAKA scheme for mobile cloud computing, which firstly achieves remote biometric-based authentication(remote servers authenticate user’s biometrics), single sign-on (a single credential and single registration for accessing multiple servers) and center-less authentication(the registration center does not participate in the access procedure) in one scheme. In order to realize this target, we design a ZK-token based on ECC and cryptographic hash function, and then artfully employ it to introduce the fuzzy extractor technology and zero-knowledge technology into our scheme. Therefore, the user can access multiple cloud computing servers by registering only once in the registration center, and cloud computing servers can complete the biometric-based remote authentication and key agreement for the user without the registration center participating. In this way, our scheme greatly improves usability, scalability, and security compared to other existing solutions. We give a formal security proof for our scheme by using Real-Or-Random(RoR) model and Burrows-Abadi-Needham (BAN) logic to show that the present scheme is secure and security analysis for other known attacks. Finally, according to the experiment result, our scheme has lower computation and communication cost compared with most existing related schemes.

With the rapid development of cloud computing, more and more cloud services are provided to users. Faced with multiple cloud services, how to scientifically predict and assess the performance of cloud service is an imperative task. To cope with the challenge, an prediction scheme via JOGM(1,1) model is proposed based on grey system theory, in which the performance of cloud service is quantified as the response time. Thus cloud users and the third-party institutes of cloud service performance evaluation can predict and assess the performance of cloud service as accurate as possible. In return, this will contribute to the cloud service provider selection for better performance on behalf of cloud consumers. The simulation results show that the proposed scheme has higher prediction precision compared with classic GM(1,1) model and weighted moving average model, which verifies the effectiveness of the proposed prediction scheme and the feasibility of forecasting the performance of cloud service employing grey system theory.

Cloud computing has become popular in various application domains based on infrastructure, platform, and software as a service model. Rapid deployment, high scalability, on-demand, and (theoretically) infinite resources have driven the industry towards the wide adoption of cloud computing services. However, the difficulty of cross-provider resource allocation and seamless resource transition is a major concern for such services. Therefore, the segregated cloud market forces its clients to use provider-specific and pre-configured options for their required resources and services. Thus, the overall market, even with the presence of multiple cloud service providers, operates as a direct service from the providers to the clients, and with non-negotiable pricing strategies for the cloud services. In this article, we propose Bepari, a cost-driven model for opaque service platforms for cloud computing. Bepari acts as a negotiation-based approach to deliver composite cross-provider cloud-based services to the end-users. Bepari provides a detailed service-oriented architecture for multiple cloud service providers to provide cross-platform and composite services. Furthermore, Bepari delivers a detailed cost model and comparison between establishing a cloud service vs. an opaque cloud service. Our empirical framework allows a Bepari service provider to analyze the profit model and create a market niche accordingly. Simulation results are provided, which validate the efficiency of a negotiated pricing strategy in terms of maximized resource utilization and profits for cloud service providers and cost reduction for the cloud users.

Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functional requirements of services but ignore the links between providers and requesters of service, which result to the service position is not accurate. Focus on the problems, this study intends to model the relationship of the cloud services participants with the format of heterogeneous information network, which intend to mine the hidden relationships between services participants in the cloud computing environment. In theoretical research, we proposed a cloud service heterogeneous network extraction and automatic maintenance model, proposed a new service recommendation system based on heterogeneous service network ranking and clustering.

Nowadays, more and more people choose to upload their data and information to cloud. The cloud saves users’ data and information and starts providing computing services and artificial intelligence analysis. However, the privacy of users’ information and data will be completely exposed to the cloud without any protection. In this paper, we propose two methods of the blind (privacy-preserving) background extraction from video surveillance for both scenarios with the single-party cloud server (SCS) and multi-party cloud servers (MCS). We combine 1D logistics chaotic encryption with background subtraction based on a mixed Gaussian model, and propose a blind background subtraction method for a single server (SCS) . We combine the Chinese Remainder Theorem (CRT) and the ViBE background subtraction method and propose a multi-server blind background subtraction method (MCS). The test set for the experiment is CDW-2014, the experimental results show that our method has satisfactory results in recognition accuracy, recognition speed, and security analysis. The proposed methods have several advantages: (1) Based on our encryption method, the background extraction method in the original video does not need to be changed; (2) The server does not recognize any valid information for the calculation results; (3) Single cloud server (SCS) uses the chaotic mapping can ensure high-level security and resistance to several attacks; (4) Multiple cloud servers (MCS) can improve data security and improve processing efficiency. This method can accurately extract the background like the original ViBE algorithm while protecting the privacy of client video data.

PurposeCloud computing becomes mobile when a mobile device tries to access the shared pool of computing resources provided by the cloud, on demand. Mobile applications may enrich their functionality by delegating heavy tasks to the clouds as the remote processing and storage have become possible by adding asynchronous behavior in the communication. However, developing mobile cloud applications involves working with services and APIs from different cloud vendors, which mostly are not interoperable across clouds. Moreover, by adding asynchronicity, mobile applications must rely on push mechanisms which are considered to be moderately reliable, and thus not recommended in scenarios that require high scalability and quality of service (QoS). To counter these problems, and the purpose of this paper, is to design a middleware framework, Mobile Cloud Middleware (MCM), which handles the interoperability issues and eases the use of process‐intensive services from smartphones by extending the concept of mobile host.Design/methodology/approachMCM is developed as an intermediary between the mobile and the cloud, which hides the complexity of dealing with multiple cloud services from mobiles. Several applications are presented to show the benefits of mobiles going cloud‐aware. Moreover, to verify the scalability of MCM, load tests are performed on the hybrid cloud resources using well known load balancing mechanisms like HAProxy and Tsung.FindingsFrom the study it was found that it is possible to handle hybrid cloud services from mobiles by using MCM. The analysis demonstrated that the MCM shows reasonable performance levels of interaction with the user, thus validating the proof of concept. Moreover, MCM decreases the effort in developing mobile cloud applications and helps in keeping soft‐real time responses by using its asynchronous approach.Originality/valueMCM fosters the utilization of different types of cloud services rather than the traditional mobile cloud services based on data synchronization. By offloading heavy tasks to the clouds, the framework extends the processing power and storage space capabilities of the constrained smart phones. The applications mentioned in the paper bring an added value by being success stories for mobile cloud computing domain in general.