scholarly journals A Hybrid Method to Shorten Congestion and Implement Data Guarantee in Cloud Computing

2019 ◽  
Vol 8 (6S2) ◽  
pp. 739-741
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Hybrid Method ◽  
Data Security ◽  
Security Level ◽  
Present System ◽  
Customer Needs ◽  
Dynamic Task ◽  
Full Control ◽  
The Way

Distributed computing is used any place in light of the way that it gives on solicitation access of advantages and reduces cost, it offers dynamic task of benefits for guaranteed and trustworthy organizations. Customers store their data on a single virtual server, when customer needs to get to any data that data might be changed or balanced by unapproved people for malevolent reason since customer's don't have organize control of data So security is a noteworthy test for dispersed registering, to improve the immovable nature of organizations it is imperative to assemble the security level in the cloud where the customer should free from dependability, approval, rightness or protection. In this paper, I proposed another system for blockage control and data security in circulated figuring. Various makers have given their considerations on data security in cloud anyway no one gives the full control to the customer. This methodology control stop up by diminishing the proportion of data. In the present system cloud pro center uses weight strategy to diminish the degree of data after that scramble data that fabricates the proportion of ciphertext interestingly with compacted data. Another encryption framework is used to encode the pressed data that does not assemble the range of ciphertext. There are two rule ideal conditions of this methodology (I) it doesn't fabricate the range of ciphertext connection with existing strategy and (ii) reduce the blockage among server and customer by speedy transmission. In case we decline the range of data then data would be traded among customer and server in less proportion of time so for this circumstance this technique controls the blockage among customer and server.

Research on Data Security in Cloud Computing

2014 ◽  
Vol 926-930 ◽  
pp. 2811-2814 ◽  
Author(s):  
Zhi Hong Li
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Security ◽  
Cloud Model ◽  
Accessible Information ◽  
Cloud Providers ◽  
Security Problem ◽  
New Perspective

Cloud computing has offered a brand-new perspective to scalable, distributed computing, which allows significant reduction in IT costs and increase in capabilities. At the same time, however, due to the openness of accessible information relying on trust between cloud providers and customers, the problem of data security has been amplified under the cloud model. This paper investigates the security problem and some of the key challenges of implementing security solutions.

scholarly journals Enhancing the Authentication Scheme to Auditing the Cloud Storage and Security

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
K. Deepa, Et. al.
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Security ◽  
Cloud Storage ◽  
Data Access ◽  
It Infrastructure ◽  
Data Confidentiality ◽  
Basic Concepts ◽  
Publicly Supported ◽  
The Many

Cloud computing has become a reality with new IT infrastructure based on several techniques such as distributed computing, virtualization, etc. Besides the many benefits that they can offer, cloud computing also comes with the difficulty of protecting data security. This paper first explores the basic concepts and analyzes the main aspects of data security about cloud computing. We then look at each problem, discussing its nature and existing solutions, if any. In particular, we will pay special attention to protecting data confidentiality/integrity/availability, data access, and monitoring, and complying with rules and obligations to ensure data security and confidentiality. With the fast advancement of organizing and portable gadgets, we are confronting a dangerous incensement of swarm sourced information. Existing frameworks as a rule depend on a confided in server to total the spatio fleeting publicly supported information and after that apply differential security component to bother the total insights previously distributing to give solid protection ensure. We propose a Modified appropriated specialist based protection saving structure, called MDADP that presents another dimension of various operators between the clients and the untrusted server.  

Classification of File Data Based on Confidentiality in Cloud Computing using K-NN Classifier

2016 ◽  
Vol 3 (2) ◽  
pp. 61-78 ◽  
Author(s):  
Munwar Ali Zardari ◽  
Low Tang Jung
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Virtual Machine ◽  
Data Security ◽  
Virtual Machines ◽  
Data Classification ◽  
Data Encryption ◽  
Cloud Services ◽  
Security Level ◽  
Public Data

Cloud computing is a new paradigm model that offers different services to its customers. The increasing number of users for cloud services i.e. software, platform or infrastructure is one of the major reasons for security threats for customers' data. Some major security issues are highlighted in data storage service in the literature. Data of thousands of users are stored on a single centralized place where the possibility of data threat is high. There are many techniques discussed in the literature to keep data secure in the cloud, such as data encryption, private cloud and multiple clouds concepts. Data encryption is used to encrypt the data or change the format of the data into the unreadable format that unauthorized users could not understand even if they succeed to get access of the data. Data encryption is very expensive technique, it takes time to encrypt and decrypt the data. Deciding the security approach for data security without understanding the security needs of the data is a technically not a valid approach. It is a basic requirement that one should understand the security level of data before applying data encryption security approach. To discover the data security level of the data, the authors used machine learning approach in the cloud. In this paper, a data classification approach is proposed for the cloud and is implemented in a virtual machine named as Master Virtual Machine (Vmm). Other Vms are the slave virtual machines which will receive from Vmm the classified information for further processing in cloud. In this study the authors used three (3) virtual machines, one master Vmm and two slaves Vms. The master Vmm is responsible for finding the classes of the data based on its confidentiality level. The data is classified into two classes, confidential (sensitive) and non-confidential (non-sensitive/public) data using K-NN algorithm. After classification phase, the security phase (encryption phase) shall encrypt only the confidential (sensitive) data. The confidentiality based data classification is using K-NN in cloud virtual environment as the method to encrypt efficiently the only confidential data. The proposed approach is efficient and memory space friendly and these are the major findings of this work.

Classification of File Data Based on Confidentiality in Cloud Computing Using K-NN Classifier

2019 ◽  
pp. 678-697
Author(s):  
Munwar Ali Zardari ◽  
Low Tang Jung
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Security ◽  
Virtual Machines ◽  
Data Classification ◽  
Data Encryption ◽  
Security Level ◽  
New Paradigm ◽  
Memory Space ◽  
Multiple Clouds

Cloud computing is a new paradigm model that offers different services to its customers. The increasing number of users for cloud services i.e. software, platform or infrastructure is one of the major reasons for security threats for customers' data. Some major security issues are highlighted in data storage service in the literature. Data of thousands of users are stored on a single centralized place where the possibility of data threat is high. There are many techniques discussed in the literature to keep data secure in the cloud, such as data encryption, private cloud and multiple clouds concepts. Data encryption is used to encrypt the data or change the format of the data into the unreadable format that unauthorized users could not understand even if they succeed to get access of the data. Data encryption is very expensive technique, it takes time to encrypt and decrypt the data. Deciding the security approach for data security without understanding the security needs of the data is a technically not a valid approach. It is a basic requirement that one should understand the security level of data before applying data encryption security approach. To discover the data security level of the data, the authors used machine learning approach in the cloud. In this paper, a data classification approach is proposed for the cloud and is implemented in a virtual machine named as Master Virtual Machine (Vmm). Other Vms are the slave virtual machines which will receive from Vmm the classified information for further processing in cloud. In this study the authors used three (3) virtual machines, one master Vmm and two slaves Vms. The master Vmm is responsible for finding the classes of the data based on its confidentiality level. The data is classified into two classes, confidential (sensitive) and non-confidential (non-sensitive/public) data using K-NN algorithm. After classification phase, the security phase (encryption phase) shall encrypt only the confidential (sensitive) data. The confidentiality based data classification is using K-NN in cloud virtual environment as the method to encrypt efficiently the only confidential data. The proposed approach is efficient and memory space friendly and these are the major findings of this work.

scholarly journals Research on Achieving Data Security with the Cloud Computing Adoption Framework

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1566-1570
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Cloud Computing Adoption ◽  
The Way

offering perpetual statistics safety for petabytes of facts is important for handed on enrolling. A ordinary overview on cloud safety imparts that the safety of customers' records has the maximum lifted need and moreover challenge. We acquire this need in order to accomplish with a manner of thinking this is succesful, adoptable and all around made. consequently, this paper has constructed up a device known as Cloud Computing Adoption Framework (CCAF)which has been modified for verifying cloud information. This paper clears up the chart, device for deduction and regions within the CCAF to make certain statistics safety. CCAF is outlined through using the framework route of action depending on the fundamentals and the execution confirmed up thru the CCAF multi-layered protection. while you do not forget that our records center has 10 petabytes of data, there can be splendid challenge to provide nonstop safety and detach. We use business agency manner Modeling Notation (BPMN) to mirror how information is getting used. using BPMN redirection allows us to assess the picked protection introductions in advance than showed execution. outcomes show that an opportunity to assume duty for security break may have a few spot inside the extent of 50 and 100 twenty 5 hours. The server farms have skilled problems of brisk increase within the data. as an example, in a server broaden that the lead writer used to art work with, properly ordered option of 100 terabytes of statistics modified into elegant this proposes greater safety is needed to guarantee all statistics is particularly ensured inside the squeezing a hundred twenty five hours. This paper has correspondingly tested that CCAF multi-layered protection can ensure statistics coherently and it has 3 layers of safety: 1) firewall and get admission to govern; 2) personality affiliation and obstruction adjusting movement and 3) joined encryption. To avow CCAF, this paper has gotten a deal with on techniques of proper hacking assessments required with attack trying out with 10,000 Trojans and pollutions. The CCAF multi-layered security can rectangular 9,919 illnesses and Trojans which can be beaten like a burst and the staying ones may be disengaged or disconnected. The tests seem paying little admire to the way in which that the diploma of blockading can decrease for steady aggregate of ailments and Trojans, 90 seven.forty three percent of them can be restricted. Our CCAF multi-layered safety has a humdrum of 20 percentage ideal execution over the singlelayered manner of thinking which can simply block7, 438 defilements and Trojans

scholarly journals Proficient Recovery Over Records using Encryption in Cloud Computing

2019 ◽  
Vol 8 (9S3) ◽  
pp. 670-673
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Access Structure ◽  
The Way

Secure record stockpiling and recovery is one among the most blazing examination bearings in distributed computing. Notwithstanding the way that various available cryptography plans are orchestrated, few of them bolster conservative recovery over the archives that are encoded upheld their traits. Amid this paper, a positioned characteristic based cryptography topic is at first intended for a report grouping. A gathering of reports will be encoded together in the event that they share partner coordinated access structure. Contrasted and the figure content arrangement trait based cryptography (CP-ABE)plans, each the figure content cabinet reality costs of encryption/unscrambling are spared. At that point, partner record structure named trait based recovery alternatives (ARF) tree is made for the report variety upheld the TF-IDF demonstrate and in this manner the archives' characteristics. The ARF tree depends on the various levelled processing encryption plot(HABE).A significance first look algorithmic program for the ARF tree is proposed to enable the chase to control that can be additional improved by parallel handling. Beside the archive accumulations, our subject will be conjointly connected to various datasets by changing the ARF tree marginally. The modification plot is called as HABE. An extreme examination and a movement of preliminaries are executed for example the security and force of the masterminded subject.

scholarly journals OB-MECC: An Efficient Confidentiality and Security Enhancement for Cloud Storage System

2021 ◽  
Author(s):  
P. NagaRaju ◽  
N. Nagamalleswara Rao
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Cloud Storage ◽  
Storage System ◽  
Cloud Services ◽  
Security Level ◽  
Data Confidentiality ◽  
Security Enhancement ◽  
Reducing Costs ◽  
Main Barrier

Cloud computing (CC) is one amongst the developing technologies, which get more attention from academia as well as industries. It offers diverse benefits like sharing computing resources, service flexibility, reducing costs, etc. The Cloud Services Provider (CSP) is accountable for the data that are delivered to the cloud. The threat of seeing the stored data and using sensitive raw data by strangers is the main barrier in the utilization of cloud services. So, Data Security (DS) along with privacy is the chief issue, which is an obstacle while adopting the CC. Countless techniques are existent for ensuring data confidentiality, but they do not completely give protection to the data. To trounce these drawbacks, this paper introduces the Obfuscation (OB) based Modified Elliptical Curve Cryptography (MECC) algorithm for protecting data as of malicious attacks, which is termed as OB-MECC. Primarily, the proposed method obfuscates the data before they are uploaded to the cloud. For the OB of the data, the proposed work employs methods like substitution cipher (SC), position update, Ceaser cipher, binary conversion, 8-bit binary conversion, decimal(),  two complex(), and ASCII(). Then, encryption of the obfuscated data is done with the utilization of the MECC algorithm. After encryption, the data on the cloud is retrieved. The retrieved data is then decrypted by reversing the OB and encryption process to get the actual data. The outcomes corroborate that the confidentiality and security level are maximum for the proposed OB-MECC when contrasted to the existing approaches.

Data Security and Protection in Cloud Computing

2012 ◽  
Vol 1 (2) ◽  
pp. 31-34
Author(s):  
Shameena Begum ◽  
◽  
V.Ratna Vasuki ◽  
K.V.V.Srinivas K.V.V.Srinivas
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Protection
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