http://13.232.72.61:8080/jspui/handle/123456789/271 2026-04-03T18:21:11Z 2026-04-03T18:21:11Z Kurup, Dhanya V . http://13.232.72.61:8080/jspui/handle/123456789/3360 2020-02-28T14:27:19Z 2014-03-01T00:00:00Z

Title: Explore HASBE Scheme for Fine- Grained Access Control of Outsourced Data in Cloud Computing Authors: Kurup, Dhanya V . Abstract: Cloud storage enables users to remotely store their data and use the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users’ physical possession of their outsourced data, which inevitably poses new security risks towards the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this project a flexible distributed storage integrity auditing mechanism, utilizing the homomorphism token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

2014-03-01T00:00:00Z Narasimha Murthy, M. S. Suma, V. http://13.232.72.61:8080/jspui/handle/123456789/2235 2019-05-17T10:21:09Z 2016-01-01T00:00:00Z

Title: A Comparision of Effectiveness of Regression Testing in Conventional and Cloud based Environment Authors: Narasimha Murthy, M. S.; Suma, V. Abstract: In current scenario,software industries are moving towards cloud computing environment for many reasons, one such reason is, testing the applications in cloud environment such that, they can stay in a very competitive IT market by satisfying the customer need as for as testing is considered. In this paper a data analysis is made on the application by considering traditional regression testing environment and cloud environment. It is observed that, the cloud testing environment has many advantages over traditional environment with respect to various parameter such as response time, amount of effort invested, number of defects captured, number of defects escapes.

2016-01-01T00:00:00Z Radhakrishna, Vangipuram Kumar, P. V. Aljawarneh, Shadi A. Janaki, V. http://13.232.72.61:8080/jspui/handle/123456789/2234 2019-05-17T10:20:52Z 2017-05-01T00:00:00Z

Title: Design and Analysis of a Novel Temporal Dissimilarity Measure Using Gaussian Membership function Authors: Radhakrishna, Vangipuram; Kumar, P. V.; Aljawarneh, Shadi A.; Janaki, V. Abstract: Earlier research works addressing the problem of mining time profiled temporal association patterns did not address the possibility of using new similarity measures in the context of time stamped temporal databases except some of our previous works. This research throws focus on designing a new similarity measure for mining similarity profiled temporal association patterns. The objective is to design a fuzzy similarity measure which can be used to discover all valid similarity profiled temporal association patterns.

2017-05-01T00:00:00Z Radhakrishna, Vangipuram Veereswara Kumar, Puligadda Janaki, Vinjamuri http://13.232.72.61:8080/jspui/handle/123456789/2226 2019-05-17T10:16:01Z 2012-08-01T00:00:00Z

Title: SRIHASS - A Similarity Measure for Discovery of Hidden Time Profiled Temporal Associations Authors: Radhakrishna, Vangipuram; Veereswara Kumar, Puligadda; Janaki, Vinjamuri Abstract: Mining and visualization of time profiled temporal associations is an important research problem that is not addressed in a wider perspective and is understudied. Visual analysis of time profiled temporal associations helps to better understand hidden seasonal, emerging, and diminishing temporal trends. The pioneering work by Yoo and Shashi Sekhar termed as SPAMINE applied the Euclidean distance measure. Following their research, subsequent studies were only restricted to the use of Euclidean distance. However, with an increase in the number of time slots, the dimensionality of a prevalence time sequence of temporal association, also increases, and this high dimensionality makes the Euclidean distance not suitable for the higher dimensions. Some of our previous studies, proposed Gaussian based dissimilarity measures and prevalence estimation approaches to discover time profiled temporal associations. To the best of our knowledge, there is no research that has addressed a similarity measure which is based on the standard score and normal probability to find the similarity between temporal patterns in z-space and retains monotonicity. Our research is pioneering work in this direction. This research has three contributions. First, we introduce a novel similarity (or dissimilarity) measure, SRIHASS to find the similarity between temporal associations. The basic idea behind the design of dissimilarity measure is to transform support values of temporal associations onto z-space and then obtain probability sequences of temporal associations using a normal distribution chart. The dissimilarity measure uses these probability sequences to estimate the similarity between patterns in z-space. The second contribution is the prevalence bound estimation approach. Finally, we give the algorithm for time profiled associating mining called Z-SPAMINE that is primarily inspired from SPAMINE. Experiment results prove that our approach, Z-SPAMINE is computationally more efficient and scalable compared to existing approaches such as Naïve, Sequential and SPAMINE that applies the Euclidean distance

2012-08-01T00:00:00Z