Data Classification for Achieving Security in Cloud Computing

Shaikh, Rizwana; Sasikumar, M.

doi:10.1016/j.procs.2015.03.087

Cited by 69 publications

(27 citation statements)

References 11 publications

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“…measure in cloud computing [21] As mentioned earlier throughout the paper, data is a significant factor in cloud computing. Since data in a cloud computing technique possess various attributes, the security measures required for them also varies.…”

Section: Data Classification As a Securitymentioning

confidence: 95%

Cloud Computing: Characteristics, Issues and Possible Security Solutions - A Review

Jiju¹,

Arun²

2015

DJ JAECE

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Cloud computing is one of the research areas where a large amount of studies and investigations are going on. With the advent of technology the security concerns and issues related to cloud computing are on the rise and thus they require a serious attention. In this article we have attempted a review of the cloud computing scenario; their characteristics, issues and possible solutions. The types of cloud computing can be classified as public, private and hybrid cloud computing. The services and characteristics of cloud computing are presented with a special mention to resource pooling, flexibility, accessibility, measurability and on demand cell service. The issues in cloud computing are provided with emphasis on storage security and distributed denial of service. Three methods viz data classification, layered frame work and Attribute Based Encryption (ABE) have been presented as the viable methods for improved security in cloud computing. Next the usage of cloud computing in malware detection is outlined. Finally general measures for improving security in cloud computing is discussed.

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Section: Data Classification As a Securitymentioning

confidence: 95%

Cloud Computing: Characteristics, Issues and Possible Security Solutions - A Review

Jiju¹,

Arun²

2015

DJ JAECE

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“…Rizwana Shaikh and Dr. M. Sasikumar developed a technique for the classification in the cloud by identifying a set of parameters that could provide security based on the type of content and accessibility. The strength of the security offered was improved, but it failed to describe the classification procedure mathematically, rather than defining.…”

Section: Motivationmentioning

confidence: 99%

“…From the classification and privacy protection approaches studied in the literature, some of the challenges that the existing systems face are as follows: One of the major challenges in the methods used for privacy protection in the cloud is the number of attributes considered to offer privacy Implementing a classifier in the cloud environment is the second challenge, as the classifier must ensure security for the sensitive data. In cloud computing, data classification is crucial and is challenging, as it depends on the risk related to disclosure or the user information, such as user ID and usage patterns Another challenge that deals with the techniques providing security is the mixed attribute nature of the cloud data.…”

Section: Motivationmentioning

confidence: 99%

OW‐SVM: Ontology and whale optimization‐based support vector machine for privacy‐preserved medical data classification in cloud

Karlekar

Gomathi

2018

Int J Communication

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Summary Cloud is a multitenant architecture that allows the cloud users to share the resources via servers and is used in various applications, including data classification. Data classification is a widely used data mining technique for big data analysis. It helps the learners to discover hidden data patterns by training massive data collected from the real world. Because this trained model is the private asset of an entity, it should be protected from all other noncollaborative entities. Therefore, it is essential to take effective measures to preserve the confidential data. The objective of this paper is to preserve the privacy of the confidential data in the cloud environment by introducing the medical data classification method. In view of that, this paper presents a method for medical data classification using a novel ontology and whale optimization‐based support vector machine (OW‐SVM) approach. Initially, privacy‐preserved data are developed adopting Kronecker product bat approach, and then, ontology is built for the feature selection process. Ontology and whale optimization‐based support vector machine is then proposed by integrating ontology and whale optimization algorithm into SVM, in which ontology and whale optimization algorithm is used for the feasible selection of kernel parameters. The experiment is done using 3 heart disease datasets, such as Cleveland, Switzerland, and Hungarian. In a comparative analysis, the performance of the OW‐SVM approach is compared with that of K‐nearest neighbor, Naive Bayes, decision tree, SVM, and OW‐SVM, using accuracy, sensitivity, specificity, and fitness, as the evaluation metrics. The OW‐SVM approach could achieve maximum performance with accuracy of 83.21%, the sensitivity of 91.49%, specificity of 73%, and fitness of 81.955, outperforming existing comparative techniques.

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“…Zardari MA et.al [10] In this paper they had used the K-NN approach for in order to do classification of data inorder to provide the confidentiality of data.The main aim to classify data is to provide security.In this approach they classify the data into labels sensitive and non-sensitive data using K-NN algorithm.On the sensitive data the encryption is done inorder to provide the security.Classification is mainly performed because it become easy to select an appropriate security for data according to need of data.So this way it will enhance the security. Shaikh, Rizwana et.al [11] This paper had contributed another important technique inorder to enhance the security of data in cloud by considering the classification technique.In this different parameters are been taken into consideration to provide the classification of data and then on the classified data the encryption is performed.Different classification properties considered are access control, content and storage.On these properties the data classification is done and then the encryption is performed to enhance more security and better efficiency.Tawalbeh L et al [12] In this paper they had contributed the secure cloud computing model based on the classification which basically minimizes the overhead and processing time needed to secure the data through using different security mechanism with variable keysizes to provide the confidentiality level required for data.Classification is done by user manually and the encryption is been performed in three different level with different cryptographic algorithm.The levels are based on the sensitivity of data which includes Basic, Confidential and highly confidential level.The different cryptographic algorithm are been used at different levels to provide the security of data upto a great extent.…”

Section: Related Workmentioning

confidence: 99%

Secure Cloud Model using Classification and Cryptography

Tamanna¹,

Kumar²

2017

IJCA

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Cloud computing offers numerous benefits including scalability, availability and many services. But with its wide acceptance all over the globe, new risks and vulnerabilities have appeared too. Cloud computing supplies facility of storing and accessing understanding and programs over the web without bothering the storage space on procedure. Storing the data on cloud eliminates one's worries about space considerations, buying new storage equipment or managing their data, rather they are able to access their data any time from any place provided they have internet access. However, the rising security issues have resisted the companies from connecting with cloud computing fully. Hence security risks have appeared as the main disadvantage of cloud computing. This paper involves the efforts to research the security risk and then proposes a framework to address these risks on the authentication and storage level in cloud computing. While addressing the security issues the first and the foremost thing is to classify what data needs security and what data needn't bother with security and hence data gets classified into classes. To achieve data classification, a data classification approach based on the confidentiality of data is proposed in this paper. Following that an efficient security mechanism must be deployed by means of encryption, authentication, and authorization or by means of every other method to ensure the privacy of s data on cloud storage

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Data Classification for Achieving Security in Cloud Computing

Cited by 69 publications

References 11 publications

Cloud Computing: Characteristics, Issues and Possible Security Solutions - A Review

Cloud Computing: Characteristics, Issues and Possible Security Solutions - A Review

OW‐SVM: Ontology and whale optimization‐based support vector machine for privacy‐preserved medical data classification in cloud

Secure Cloud Model using Classification and Cryptography

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