Slicing, Tokenization, and Encryption Based Combinational Approach to Protect Data-at-Rest in Cloud Using TF-Sec Model

2020 ◽  
Vol 17 (12) ◽  
pp. 5296-5306
Author(s):  
N. Keerthana ◽  
Viji Vinod ◽  
Sudhakar Sengan

Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories, and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.

Cloud computing or in other words, shared computing is a unique way of sharing resources via the Internet. It combines and extends features of parallel processing, grid computing, and distributed computing. Cloud Computing environments provide a competent way to schedule and process various jobs on remote machines. Rather than relying on local machines, Cloud users access services remotely via high-speed networks. Various users submitting jobs to be processed to Cloud would expect Quality of Service (QoS). So, currently, many researchers are proposing various heuristics that provide QoS to cloud users. The job scheduler is responsible for scheduling various jobs to its best-matched resource to achieve desired QoS. There are Service Level Agreements (SLAs) between Cloud Service Providers (CSPs) and Cloud users, which need to be followed by both the parties. Benefits would be affected in case of not complying with SLAs. In this paper various SLAs like Hard SLA, Best Effort SLA and Soft SLA are proposed. Jobs with required QoS parameters like Reliability, Execution Time and Priority are submitted to the scheduler. QoS of resources is determined by parameters like Reliability, Job Completion Time and the Cost of the resource. Schedulers then assign the Job to the best-matched resource according to specified SLA. Simulation is performed for First Fit and Best Fit heuristic approaches. Performances of both the heuristic approaches are evaluated with performance parameters like Average Resource Utilization (ARU), Success Rate of Jobs (SR) and Total Completion Time (TCT). This research work is useful for various organizations that provide various Cloud services to users who seek different levels of QoS for various applications.


Author(s):  
Junfeng Tian ◽  
He Zhang

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.


2013 ◽  
Vol 427-429 ◽  
pp. 2377-2382
Author(s):  
Ying Liu ◽  
Yan Wang ◽  
Xian You Sun

Among the wide range of cloud service providers with different performance characteristics, in order to let the cloud users find cloud services which satisfy its performance preferences and specific trust levels,it needs to establish a reasonable and scientific cloud service trust evaluation system. This paper introduces a membership degree theory into trust evaluation model. First, it designs the trust evaluation system framework of cloud services, and establishes a trust evaluation model of cloud services. Next, it calculates the trust level of cloud services with the comprehensive trust cloud center of gravity evaluation method (CCGE). Finally, the experiment results show that this model can build precise trust relationship between cloud users and cloud services based on users performance demands.


2019 ◽  
Vol 16 (9) ◽  
pp. 3989-3994
Author(s):  
Jaspreet Singh ◽  
Deepali Gupta ◽  
Neha Sharma

Nowadays, Cloud computing is developing quickly and customers are requesting more administrations and superior outcomes. In the cloud domain, load balancing has turned into an extremely intriguing and crucial research area. Numbers of algorithms were recommended to give proficient mechanism for distributing the cloud user’s requests for accessing pool cloud resources. Also load balancing in cloud should provide notable functional benefits to cloud users and at the same time should prove out to be eminent for cloud services providers. In this paper, the pre-existing load balancing techniques are explored. The paper intends to provide landscape for classification of distinct load balancing algorithms based upon the several parameters and also address performance assessment bound to various load balancing algorithms. The comparative assessment of various load balancing algorithms will helps in proposing a competent load balancing technique for intensify the performance of cloud data centers.


2013 ◽  
Vol 660 ◽  
pp. 196-201 ◽  
Author(s):  
Muhammad Irfan ◽  
Zhu Hong ◽  
Nueraimaiti Aimaier ◽  
Zhu Guo Li

Cloud Computing is not a revolution; it’s an evolution of computer science and technology emerging by leaps and bounds, in order to merge all computer science tools and technologies. Cloud Computing technology is hottest to do research and explore new horizons of next generations of Computer Science. There are number of cloud services providers (Amazon EC2), Rackspace Cloud, Terremark and Google Compute Engine) but still enterprises and common users have a number of concerns over cloud service providers. Still there is lot of weakness, challenges and issues are barrier for cloud service providers in order to provide cloud services according to SLA (Service Level agreement). Especially, service provisioning according to SLAs is core objective of each cloud service provider with maximum performance as per SLA. We have identified those challenges issues, as well as proposed new methodology as “SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services”. Currently, cloud service providers are using “orchestrations” fully or partially to automate service provisioning but we are trying to integrate and drive orchestration flows from SLAs. It would be new approach to provision cloud service and deliver cloud service as per SLA, satisfying QoS standards.


2021 ◽  
Author(s):  
Kashif Mehboob Khan ◽  
Junaid Arshad ◽  
Waheed Iqbal ◽  
Sidrah Abdullah ◽  
Hassan Zaib

AbstractCloud computing is an important technology for businesses and individual users to obtain computing resources over the Internet on-demand and flexibly. Although cloud computing has been adopted across diverse applications, the owners of time-and-performance critical applications require cloud service providers’ guarantees about their services, such as availability and response times. Service Level Agreements (SLAs) are a mechanism to communicate and enforce such guarantees typically represented as service level objectives (SLOs), and financial penalties are imposed on SLO violations. Due to delays and inaccuracies caused by manual processing, an automatic method to periodically verify SLA terms in a transparent and trustworthy manner is fundamental to effective SLA monitoring, leading to the acceptance and credibility of such service to the customers of cloud services. This paper presents a blockchain-based distributed infrastructure that leverages fundamental blockchain properties to achieve immutable and trustworthy SLA monitoring within cloud services. The paper carries out an in-depth empirical investigation for the scalability of the proposed system in order to address the challenge of transparently enforcing real-time monitoring of cloud-hosted services leveraging blockchain technology. This will enable all the stakeholders to enforce accurate execution of SLA without any imprecisions and delays by maintaining an immutable ledger publicly across blockchain network. The experimentation takes into consideration several attributes of blockchain which are critical in achieving optimum performance. The paper also investigates key characteristics of these factors and their impact to the behaviour of the system for further scaling it up under various cases for increased service utilization.


2019 ◽  
pp. 903-922
Author(s):  
Junfeng Tian ◽  
He Zhang

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.


Author(s):  
Yasmine M. Afify ◽  
Ibrahim F. Moawad ◽  
Nagwa. L. Badr ◽  
Mohamed F. Tolba

Cloud computing is an information technology delivery model accessed over the Internet. Its adoption rate is dramatically increasing. Diverse cloud service advertisements introduce more challenges to cloud users to locate and identify required service offers. These challenges highlight the need for a consistent cloud service registry to serve as a mediator between cloud providers and users. In this chapter, state-of-the-art research work related to cloud service publication and discovery is surveyed. Based on the survey findings, a set of key limitations are emphasized. Discussion of challenges and future requirements is presented. In order to contribute to cloud services publication and discovery area, a semantic-based system for unified Software-as-a-Service (SaaS) service advertisements is proposed. Its back-end foundation is the focus on business-oriented perspective of the SaaS services and semantics. Service registration template, guided registration model, and registration system are introduced. Additionally, a semantic similarity model for services metadata matchmaking is presented.


Author(s):  
Jose Luis Vazquez-Poletti ◽  
Rafael Moreno-Vozmediano ◽  
Ignacio M. Llorente

Cloud computing is a paradigm that allows the flexible and on-demand provisioning of computing resources. For this reason, many institutions and enterprises have moved their data centers to the Cloud and, in particular, to public infrastructures. Unfortunately, an increase in the demand for Cloud results in resource shortages affecting both providers and consumers. With this factor in mind, Cloud service providers need Admission Control algorithms in order to make a good business decision on the types of requests to be fulfilled. Cloud providers have a desire to maximize the net income derived from provisioning the accepted service requests and minimize the impact of unprovisioned resources. This chapter introduces and compares Admission Control algorithms and proposes a service model that allows the definition of Service Level Agreements for the Cloud.


2018 ◽  
Vol 8 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval

Infrastructure-as-a-service is a cloud service model that allows customers to outsource computing resources such as servers and storage. This article evaluates four IaaS cloud services - Amazon EC2, Microsoft Azure, Google Compute Engine and Rackspace Cloud in a vendor-neutral approach with regards to system parameter usage including server, file I/O and network utilization. Thus, system-level benchmarking provides objective comparison of cloud providers from performance standpoint. Unixbench, Dbench and Iperf are the System-level benchmarks chosen to test the performance of server, file I/O and network respectively. In order to capture the variation in performance, the tests were performed at different times on weekdays and weekends. With each offering, the benchmarks are tested on different configurations to provide an insight to the cloud users in selection of provider followed by appropriate VM sizing according to the workload requirement. In addition to the performance evaluation, price-per-performance value of all the providers is also examined and compared.


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