Informatics Publishing Limited

V. Kalpana ¹, V. Meena ¹

Affiliations
1 Computer Science and Engineering, School of Computing, SASTRA University, Tirumalaisamudram, Thanjavur – 613401, Tamilnadu, IN

Abstract

Data Storage Correctness plays a major role in Mobile Cloud Computing. This deals with checking the integrity of data at remote cloud storage server. In auditing the data blindness should be incorporated regarding Third party auditing. Message Authentication Code, Digital Signatures, and Hash methods are employed for verification of message in the existing methods. In this current study data dynamic and public auditing is taken with confidentiality. This work isolates the method that is suitable for mobile cloud environment and gives the overall view of the auditing methods in the recent study. Design of an efficient auditing architecture to minimize computation and storage cost of the mobile devices are proposed to enhance the mobile users auditing is discussed. This work analysed on numerous existing cloud storage correctness methods pros and cons based on their technique, framework and also discusses the challenges that are required to implement data storage correctness method in Mobile Cloud Computing. This study gives a new framework to improve the integrity verification for remote data stored in cloud.

Keywords

Auditing, Data Dynamics, Data Storage Correctness, Mobile Cloud, Provable Data Possession, Trusted Third Party.

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V. Placida ¹, V. Meena ¹

Affiliations
1 St. Theresas College, Eluru, IN

Abstract

Sauropus plant belongs to the family Euphorbiaceae of series unisexuals, sub class monoclemidae, class dicotyledons. This plant is a shrub nearly grows upto 9 feet, the basal growth is not strong enough to support the maximum growth. Sauropus plant is profusely branched at the top, leaves on the main branch are scaly and in the axil of scale leaves dwarf branches are seen.

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Rajammal P. Devadas ¹, S. Prema Kumari ¹, V. Meena ¹

Affiliations
1 Sri Avinashilingam Home Science College for Women, Coimbatore-641 043, IN

Abstract

Alcohol related problems are an obstacle to the socio economic development in the developing countries. Not only the health of the younger generations is affected due to alcoholism but also their moral standards disappear.

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G. Vinodhini ¹, V. Meena ¹

Affiliations
1 School of Computing, SASTRA University, Tirumalaisamudram, Thanjavur – 613401, Tamilnadu, IN

Abstract

Objectives: Cloud computing refers to an internet based computing that allows sharing data and resources, which provides create, configure and customize the applications online. Methods: To overcome this issue, we proposed an analyzing behavior of user’s traffic. First, construct a whole feature set by collecting features from users and feature selection is helps to choose set of accurate features where necessary features are selected and predicted for an abnormal user is done by Naive Bayes classification. Findings: Support Vector Machine (SVM) produces high accuracy and over fitting of data is applicable. This new method improves the efficiency and detection rate of the system in the analysis of traffic behavior of abnormal users. Applications: Email communication, banking, e-commerce and social networks.

Keywords

Data Mining Techniques, Feature Set, Feature Selection, Network Traffic Analysis, Network Traffic Prediction, SVM.

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