Rama Sushil

Cloud Auditing: Privacy Preserving using Fully Homomorphic Encryption in TPA

Cloud computing is the future of the next generation architecture of IT solutions. Cloud provides computing resources on subscription basis over the internet. The Cloud data storage network includes a Third Party Auditor which has the power and capabilities that a client does not have. It is a trusted entity that has the access to, other than cloud and check on the exposed risk involved in cloud storage data on behalf of the client. In this paper, the problem of data security and integrity has been presented. Also, a scheme to provide maximum data integrity. In proposed scheme, existing fully homomorphic encryption is integrated with TPA auditing system is proposed. This scheme can audit data integrity without decrypting it.

Mobile Agent Communication Protocols: A Comparative Study

Mobile Agent is considered as a striking technology for distributed applications. Its mobility feature makes it difficult to track and consequently performing communication between them becomes difficult. In multi mobile agent environment, a reliable communication is still a big challenge. In this paper, we have addressed the pros and cons of the existing different Mobile Agent communication protocols with their limitations. This paper also presents their parametric comparative study in tabular form.

An Integral Image Based Text Extraction Technique from Document Images by Multilevel Thresholding Using Differential Evolution

This paper presents a multilevel image segmentation technique for extraction of texts from document images at a faster rate. Rectangular sum-table based concept (known as integral image) has been used here to find the local threshold value of images. An integral image obtained for a fixed window size is used to calculate threshold value by the proposed probability-based objective function. Threshold value calculations over small window size generate the result quickly compared to standard algorithms like Sauvola, Niblack, and Vu approaches. The achieved local threshold value is further optimized globally by the Differential Evolution (DE) algorithm to get multiple thresholds. DE provides fast and accurate convergence towards the optimal solution as compared to other well-known optimized algorithms like Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The proposed technique is applied to different types of degraded document images. The outcomes of the proposed approach are compared both quantitatively and qualitatively with state-of-the-art methods.

Deployment of Cloud Using Open-Source Virtualization: Study of VM Migration Methods and Benefits

Cloud computing has become a buzz word in the field of Information Technology today. It increases the machine potential in terms of computing using virtualization as a core technology. Virtualization is a core of cloud computing in which creation of virtual machines provides the scalability and portability by hosting the components of different applications. Requirements in the cloud environment are dynamic; therefore, there is always a need to move virtual machines within the same cloud or in different clouds. The goal of this paper is to conduct the experiment for deployment of cloud using open source and show the virtual machine (VM) migration between different hosts within a cloud in different scenarios. For secure migration of VM, we have used secure shell method and compared open-source virtualization with other technologies available in the market. The experiment for this study was conducted in the computer service center of IIT Delhi on their private cloud “Baadal.”

A New Objective Function Based Multi-Level Image Segmentation Using Differential Evolution

This Paper represents a multi-level image thresholding approach based on the normalized index value of image and probability of pixel intensities. One new objective function proposed, which is the multiplication of normalized index value and probability, to obtain the scenario. This multiplication measure is then optimized to obtain the thresholds of the image. In order to solve an optimization problem, Differential Evolution (DE) as a meta-heuristic approach is used, which results a fast and accurate convergence towards the optimal solution. The performance of DE is compared to other well-known optimized algorithms like Particle swarm optimization (PSO), Genetic Algorithms (GA). The outcomes of images are compared with Kapur entropy, Tsalli entropy and Otsu method, both visually and statistically for establishing the perceptible difference in image.