Cloud Clients Research Articles

Exploring infrastructure support for app-based services on cloud platforms

Major infrastructure-as-a-cloud (IaaS) providers have recently been building marketplaces of “cloud apps,” which are VMs pre-installed with a variety of software stacks. Clients of cloud computing leverage such markets by downloading and instantiating the apps that best suit their computing needs, thereby saving the effort needed to configure and build VMs from scratch.We posit that the notion of cloud apps as defined by these marketplaces is nascent and does not allow apps to leverage the benefits of virtual machine (VM) introspection technology developed over the past decade. We envision a marketplace of apps that can interact with client VMs in a rich set of ways to provide a number of services that are currently supported only by cloud providers. This allows clients to deploy services such as VM introspection-based security tools and network middleboxes on their work VMs without requiring the cloud provider to deploy these services on their behalf.This paper presents models to support such a marketplace of expressive cloud apps. We present a study of the design space of these models to understand their performance and deployment tradeoffs. We also consider the design of a permissions-based framework to contain untrusted third-party cloud apps. Finally, we demonstrate the utility of our models by building and evaluating a number of security tools built as cloud apps.

Efficient keyword search over encrypted data in multi-cloud setting

With the emergence of cloud storage, enabling cloud clients to securely store and efficiently retrieve ciphertext is a fundamental issue in cloud computing as data outsourcing can greatly ease heavy computation and management burden locally. Unfortunately, two challenging issues i.e., data security and privacy dramatically impede the adaption and practicability of cloud storage due to honest-but-curious cloud service provider CSP. Furthermore, data encryption mechanism seriously makes the information retrieval over ciphertext extremely difficult. Besides, dealing with single CSP is predicted to become less popular with cloud customers for fear of risks of single-point failure threats and potential malicious insiders. To this end, we propose two efficient keyword search over encrypted data in multi-cloud setting schemes which exploit Identity-Based Encryption IBE and Key-Policy Attribute-Based Encryption KP-ABE, respectively. Formal security analysis proves that our schemes can guarantee data privacy and reliability. As a further contribution, experimental results over real-world dataset show that our proposed schemes are feasible and efficient in practical applications. Copyright © 2016 John Wiley & Sons, Ltd.

The business value of cloud computing: the partnering agility perspective

Purpose– The purpose of this paper is to focus on the value creation potential of cloud computing in inter-firm partnerships. It examines how cloud-based IT infrastructure capabilities in flexibility and integration contribute to partnering agility and, consequently, firm performance. This study also introduces business lifecycle and market turbulence as internal and external context variables, respectively, to investigate the different roles of cloud computing in value creation.Design/methodology/approach– A questionnaire was used to collect data from 184 client firms of the largest cloud computing services provider in China (Alibaba Cloud). The theoretical model was tested using PLS analysis.Findings– Cloud infrastructure (CI) flexibility has a positive effect on partnering agility, while the effect of CI integration on partnering agility is moderated by business lifecycle and market turbulence.Research limitations/implications– The surveyed firms are all Alibaba Cloud clients, which may limit the generalization of the findings.Practical implications– The study suggests that besides the cost benefits, the value creation aspect of cloud computing should also be emphasized in research and practice. The study provides a new perspective to understand the business value of cloud computing in inter-firm partnerships.Originality/value– The study suggests that the flexibility-related and integration-related features of cloud computing can create value for firms by facilitating inter-firm collaboration in exploiting business opportunities.

Intra State Recovery System Design for Cloud based Applications

Background/Objectives: Considering the growing demand for cloud services for development and deploying of critical business applications, it is extremely important that cloud provider guarantees a reliable and robust service by providing fault tolerance mechanisms that enable seamless execution of the business transaction execution even in presence of faulty components. The objective of this paper is to propose a collaborative fault tolerant mechanism between cloud provider and cloud client. Methods/Statistical Analysis: The collaborative fault tolerance approach considers collaboration between the cloud provider and the cloud client to develop a comprehensive fault tolerance solution that can be customised to suit to the hosted cloud applications needs.The proposed design is based on usage of Persistent Map based strategy. Findings: The Persistent Map based strategy saves the state information of execution in the form of P-maps. The P-map is a persistent hash map that stores the current state of execution of a given task. In the case of failure, it can be used to restart the process from the last state at which the task failed and resume the application execution from that point as though no failure occurred.The P-map storage is a crucial element to be considered in the design of the system, that requires careful analysis and can have a huge impact on the execution of an application. Application/Improvements: The authors have considered an approach which requires a collaboration between cloud providers and cloud client to design a fault tolerance mechanism that takes into consideration the complex cloud infrastructure as well behaviour and functionality of the application in focus.

Business in the Cloud: Research Questions on Governance, Audit, and Assurance

ABSTRACTCloud computing services are finding rapid adoption as organizations seek cost reduction, technical expertise, flexibility, and adaptable mechanisms to attain advantages in fast-moving business environments. The related considerations of governance, audit, and assurance of cloud computing services might be inadvertently overlooked in a rush to adopt these cloud services. This paper focuses on cloud computing governance and audit issues by presenting research questions informed by both practice and research. A cloud computing ecosystem is presented and an IT Governance framework (Wilkin and Chenhall 2010) is referenced as a means to structure research questions. Key issues of risk, security, monitoring, control, and compliance should be considered early in the cloud services decision process. The tight coupling of intercompany operations between the cloud client and cloud provider(s) forms an interdependent, operationally coupled ecosystem. Planned governance is needed to achieve a well-governed, functional, and secure cloud computing environment. The audit role is complicated when the organization's financial data and/or critical applications are hosted externally with a cloud service provider that may use other cloud service providers.

A Protocol for Preventing Insider Attacks in Untrusted Infrastructure-as-a-Service Clouds

Recent technical advances in utility computing have allowed small and medium sized businesses to move their applications to the cloud, to benefit from features such as auto-scaling and pay-as-you-go facilities. Before clouds are widely adopted, there is a need to address privacy concerns of customer data outsourced to these platforms. In this paper, we present a practical approach for protecting the confidentiality and integrity of client data and computation from insider attacks such as cloud clients as well as from the Infrastructure-as-a-Service (IaaS) based cloud system administrator himself. We demonstrate a scenario of how the origin integrity and authenticity of health-care multimedia content processed on the cloud can be verified using digital watermarking in an isolated environment without revealing the watermark details to the cloud administrator. Finally to verify that our protocol does not compromise confidentiality and integrity of the client data and computation or degrade performance, we have tested a prototype system using two different approaches. Formal verification using ProVerif tool shows that cryptographic operations and protocol communication cannot be compromised using a realistic attacker model. Performance analysis of our implementation demonstrates that it adds negligible overhead.

Cloud storage forensics: MEGA as a case study

The increasing use of smartphones and cloud storage apps allows users to access their data anywhere, anytime. Due to the potential of mobile devices being used and/or targeted by criminals, such devices are an important source of evidence in investigations of both cybercrime and traditional crimes, such as drug trafficking. In this paper, we study the MEGA cloud client app, an increasingly popular alternative to Google Drive, Dropbox and OneDrive, on both Android and iOS platforms. In our study, we identify a range of artefacts arising from user activities, such as login, uploading, downloading, deletion, and the sharing of files, which could be forensically recovered, as well as findings such as modification of files’ timestamps. Our findings contribute to an up-to-date understanding of cloud storage forensics.

AN QUALITY BASED ENHANCEMENT OF USER DATA PROTECTION VIA FUZZY RULE BASED SYSTEMS IN CLOUD ENVIRONMENT

So far, in cloud computing distinct customer is accessed and consumed enormous amount of services through web, offered by cloud service provider (CSP). However cloud is providing one of the services is, security-as-a-service to its clients, still people are terrified to use the service from cloud vendor. Number of solutions, security components and measurements are coming with the new scope for the cloud security issue, but 79.2% security outcome only obtained from the different scientists, researchers and other cloud based academy community. To overcome the problem of cloud security the proposed model that is, Quality based Enhancing the user data protection via fuzzy rule based systems in cloud environment, will helps to the cloud clients by the way of accessing the cloud resources through remote monitoring management (RMMM) and what are all the services are currently requesting and consuming by the cloud users that can be well analyzed with Managed service provider (MSP) rather than a traditional CSP. Normally, people are trying to secure their own private data by applying some key management and cryptographic based computations again it will direct to the security problem. In order to provide good quality of security target result by making use of fuzzy rule based systems (Constraint & Conclusion segments) in cloud environment. By using this technique, users may obtain an efficient security outcome through the cloud simulation tool of Apache cloud stack simulator.

Forensic investigation of OneDrive, Box, GoogleDrive and Dropbox applications on Android and iOS devices

In today’s Internet-connected world, mobile devices are increasingly used to access cloud storage services, which allow users to access data anywhere, anytime. Mobile devices have, however, been known to be used and/or targeted by cyber criminals to conduct malicious activities, such as data exfiltration, malware, identity theft, piracy, illegal trading, sexual harassment, cyber stalking and cyber terrorism. Consequently, mobile devices are an increasing important source of evidence in digital investigations. In this paper, we examine four popular cloud client apps, namely OneDrive, Box, GoogleDrive, and Dropbox, on both Android and iOS platforms (two of the most popular mobile operating systems). We identify artefacts of forensic interest, such as information generated during login, uploading, downloading, deletion, and the sharing of files. These findings may assist forensic examiners and practitioners in real-world examination of cloud client applications on Android and iOS platforms.

Using Machine Learning Algorithms for Cloud Client Prediction Models in a Web VM Resource Provisioning Environment

In order to meet Service Level Agreement (SLA) requirements, efficient scaling of Virtual Machine (VM) resources in cloud computing needs to be provisioned ahead due to the instantiation time required by the VM. One way to do this is by predicting future resource demands. The existing research on VM resource provisioning are either reactive in their approach or use only non-business level metrics. In this research, a Cloud client prediction model for TPC-W benchmark web application is developed and evaluated using three machine learning techniques: Support Vector Regression (SVR), Neural Networks (NN) and Linear Regression (LR). Business level metrics for Response Time and Throughput are included in the prediction model with the aim of providing cloud clients with a more robust scaling decision choice. Results and analysis from the experiments carried out on Amazon Elastic Compute Cloud (EC2) show that Support Vector Regression provides the best prediction model for random-like workload traffic pattern.

Improved TOPSIS Method Based Trust Evaluation Framework for Determining Trustworthiness of Cloud Service Providers

Trust is one of the most challenging issues in the emerging cloud computing era. Over the past few years, numerous cloud service providers have been emerged providing similar kinds of services. It has become incredibly complex for the cloud clients to make a distinction among multiple cloud service providers offering similar kinds of services. Cloud clients need trustworthy service providers who provide services exactly as per the SLA and do not deviate from their promises. Though, there have been significant efforts to form trust between service providers and the clients by providing data, storage and network security, but relatively fewer efforts have been made in the field of trustworthiness determination by monitoring the compliance of offered services as per the SLA. This paper presents the design of a trust evaluation framework that uses the compliance monitoring mechanism to determine the trustworthiness of service providers. The compliance values are computed and then processed using a technique known as the Improved Technique for Order of Preference by Similarity to Ideal Solution (Improved TOPSIS) to obtain trust on the service providers. Case study based approach has been followed to demonstrate the usability and the applicability of the proposed framework. Experiments have been performed using the real cloud data extracted from the Cloud Harmony reports. From the experimental results, it is clear that the proposed framework can be used in real cloud environments to determine the trustworthiness of service providers by employing the real time monitoring of their services.

A NOVEL SECURITY MODEL FOR DATA MANAGEMENT IN CLOUD COMPUTING

Data security is always the focus of huge possible cloud clients, also a big obstacle for itsextensive applications. Till now there is no proficient mechanism for data security accustomed for thecloud environment, and various service types need different solutions for data protection. The objectiveof this research is to develop a new data security model for the cloud environment. The proposed modelis decomposed of four modes of operations denoting the different ways for providing the service forbetter user convenience. The four modes are: Scheduling mode, Through-off mode, Virtual machinemode, and Batch mode. Analyzing the proposed model shows the advantages it has over previousmodels. Based on extensive experiments, the proposed model covers many security cases, and is robustin handling security threats while gaining user convenience.

The cloud computing standard ISO/IEC 27018 through the lens of the EU legislation on data protection

In July 2014 ISO and IEC published a standard relating to public cloud computing and data protection. The standard aims to address the down-sides of cloud computing and the concerns of the cloud clients, mainly the lack of trust and transparency, by developing controls and recommendations for cloud service providers acting as PII processors. At the same time, the standard aims to assist providers to demonstrate transparency and accountability in the handling of data and information in the cloud. This paper looks briefly at the data protection and security challenges of cloud computing. It discusses the provisions and added value of the standard in the context of the European data protection legislation and also looks at the uptake of the standard one year after its publication.

Extracting Potential Forensic Evidences from Cloud Client Device using own Cloud as a Case Study

The highly distribution of cloud storage as a mean to store data rises the need to find a suitable forensic methods to extract forensic evidences during investigating criminal or illegal activities on cloud accounts. Most accurate evidences can be extracted from cloud serves; however forensic investigators cannot grant access to cloud servers due to privacy policies followed by cloud providers. Actually, amount of evidences can be extracted from client devices that may be of forensic investigator’s interests. This research utilizes open source cloud software to study cloud client structure to extract potential evidences from cloud client devices that will serve cloud forensic investigation field.

Enhanced Load Balancing Architecture using EE-GA

Cloud computing is the long dreamed vision of computing as a utility, where data owners can remotely store their data in the cloud to enjoy on-demand high-quality applications and services from a shared pool of configurable computing resources. In the meantime, the cloud environment represents various difficulties. Two players in distributed computing situations, cloud suppliers and cloud clients, seek after diverse objectives; suppliers need to amplify income by accomplishing high asset usage, while clients need to minimize costs while meeting their execution prerequisites. Nonetheless, it is hard to allot resources in a commonly ideal manner because of the absence of data sharing between them. In addition, continually expanding heterogeneity and variability of the surroundings poses considerably harder difficulties for both sides. This paper describes the work which mainly aimed at enhancing the load balancing architecture where firstly genetic algorithm is been implemented with simple architecture [1]. Secondly, genetic algorithm is been implemented with enhanced architecture named as E-GA where job grouping is done according to job‘s requirements. Finally the whole architecture is been enhanced by using job grouping method with enhanced genetic algorithm named as EE-GA. In enhanced genetic algorithm, artificial bee colony algorithm uses the output given by genetic algorithm as their input and provides efficient resources. Both E-GA and EE-GA have been successful in better resource utilization so that the jobs are handled in a more efficient manner and also time is saved [3]. All the comparison results prove that the EE-GA provides a more efficient way as compared to the others. General Terms Load Balancing, Cloud Computing, Genetic Algorithm, Job Grouping.

Trusted Cloud Computing Platform into Infrastructure as a Service Layer to Improve Confidentiality and Integrity of VMs

Out of the newly emerging and promising technologies is Cloud computing and Infrastructure-as-a-Service (IaaS) which can also be claimed as something the adoption of which is hampered by data security concerns. Simultaneously, Trusted Computing (TC) is also getting its burning interest as security mechanism for IaaS. This paper presents a protocol and addresses the issue of the lack of an implementable mechanism with a proportion that it will ensure the launch of a virtual machine (VM) instance on a trusted remote compute host. A trusted launch protocol for VM instances and images in public IaaS environments has been designed for Relying on Trusted Platform Module operations such as binding and sealing to provide integrity guarantees for clients that require a trusted VM launch. This paper also presents an evidence -of-concept implementation of the protocol that is solely based on Open Stack, an opensource IaaS platform. The proposed results would provide a strong stand for the use of TC mechanisms within IaaS platforms. It will also open the path for a bigger applicability of TC to IaaS security. This technology empowers the companies to take the costs down by outsourcing computations which are on-burning demand. Nevertheless, clients of cloud computing services at present do not have any means by which they can verify the confidentiality and integrity of their data and computation. This problem is addressed to propose the design of a trusted cloud computing platform (TCCP). To impart a closed box execution environment, TCCP empowers Infrastructure as a Service (IaaS) providers such as Open stack IaaS platform. It also ensures the confidential execution of guest virtual machines. Besides, it also lets the users confirm to the IaaS provider and determine if the service is secure before they launch their virtual machines.

A novel memory management technique for cloud client devices

Cloud computing systems consist of cloud client devices, which support various cloud computing services. As memory bottleneck degrades the performance of computing systems including cloud client devices, increasing the hit rates of last level caches (LLC) can improve the performance of cloud computing systems. To enhance the hit rates of LLC, we propose a new spatial locality aware prefetch technique. The proposed prefetch technique can fetch the data from main memory prior to actual requests to reduce the long latency to the main memory. To support the proposed technique, we introduce a new structure, LLC buffer which contains several memory blocks nearby the previously referenced memory block. In case that the LLC capacity is not enough, the proposed spatial locality-aware prefetch technique can improve the performance of cloud client devices significantly, especially for executing high spatial locality applications. Simulation results show that the proposed technique decreases LLC miss rates by up to 70.26 %, leading to performance improvement by up to 39.12 %.

Verification of Authorized Auditing AccuracyUsing Genchallenge Method

Cloud computing provides various elastic and scalable IT services and users can reduce the huge capital investments in their own IT infrastructure. Cloud computing falls into three broad categories such as software as a service(Saas), infrastructure as a service(Iaas) and platform as a service(Paas). Third party auditor (TPA)allows to ensure the correctness of data on behalf of the cloud client and to verify the integrity of the data stored in the cloud. In this paper, we provide one of the TPA algorithms such as Genchallenge for accuracy of an authorized auditing and verification. The results demonstrate that our scheme can offer an enhanced security and flexibility and also significantly lower overhead for big data applications

An Autonomous Time-Dependent SLA Negotiation Strategy for Cloud Computing

Cloud service level agreement negotiation is a process of joint decision-making between cloud clients and providers to resolve their conflicting objectives. With the advances of cloud technology, operations such as discovery, scaling, monitoring and decommissioning are accomplished automatically. Therefore,negotiationbetweencloudclientsandproviderscanbeabottleneckifitiscarriedoutmanually. Our objective is to propose a state-of-the-art solution to automate the negotiation process for cloud environments and specifically infrastructure as a service category. The proposed negotiation strategy is based on a time-dependent tactic. For cloud providers, the strategy uniquely considers utilization of resources when generating new offers and automatically adjusts the tactic’s parameters to concedemoreonthepriceoflessutilizedresources.Inaddition,whilethepreviousnegotiationstrategiesinliteraturetrustofferedqualityofservicevaluesregardlessoftheirdependability,ourproposed strategy is capable of assessing reliability of offers received from cloud providers. Furthermore, to find the right configuration of the time-dependent tactic in cloud computing environments, we investigate the effect of modifying parameters such as initial offer value and deadline on negotiation outputsthatincluderatioofdealsmade,andinequalityindex.Theproposednegotiationstrategyistested with different workloads and in diverse market conditions to show how the time-dependent tactic’s settings can dynamically adapt to help cloud providers increase their profits.

Office 365 v. Google Apps: A data protection perspective

This article lists the requirements of European data protection law as regards the contents of a contract between cloud provider and cloud client. Based on these requirements the contracts for the provision of Google Apps for Work and Microsoft Office 365 for small and medium enterprises are evaluated and compared from the data protection perspective. The article also discusses the shortcomings of the current legal framework for data protection with regard to cloud computing, and analyses the possible improvements made by the General Data Protection Regulation.A cloud client usually plays the role of a data controller, while the provider may be a data controller, data processor or he may not fall under the scope of data protection law. The relationship between the client and cloud provider, as a data processor, must be governed by a contract stating that the provider is bound by the instructions of the client as well as describing the security measures.The contract for Microsoft Office 365 was found to be compliant with data protection law. The contract for Google Apps for Work suffers from several deficiencies that may cause a breach of data protection law.The current data protection framework lacks unification, clarity and scalability. With the exception of unification, the General Data Protection Regulation is not expected to bring a substantial improvement if it is adopted using the proposed wording. To cope with the current law, cloud clients and providers may use the Cloud Service Level Agreement Standardisation Guidelines.