Securely Outsourcing Large Scale Eigen Value Problem to Public Cloud

Cloud computing enables clients with limited computational power to economically outsource their large scale computations to a public cloud with huge computational power. Cloud has the massive storage, computational power and software which can be used by clients for reducing their computational overhead and storage limitation. But in case of outsourcing, privacy of client's confidential data must be maintained. We have designed a protocol for outsourcing large scale Eigen value problem to a malicious cloud which provides input/output data security, result verifiability and client's efficiency. As the direct computation method to find all eigenvectors is computationally expensive for large dimensionality, we have used power iterative method for finding the largest Eigen value and the corresponding Eigen vector of a matrix. For protecting the privacy, some transformations are applied to the input matrix to get encrypted matrix which is sent to the cloud and then decrypting the result that is returned from the cloud for getting the correct solution of Eigen value problem. We have also proposed result verification mechanism for detecting robust cheating and provided theoretical analysis and experimental result that describes high-efficiency, correctness, security and robust cheating resistance of the proposed protocol

A KINEMATICIS ANALYSES OF HIGH SCHOOL CHAMPIONSHIP LONG JUMPERS

INTRODUCTION: The purpose of this study was to analyze the long jump event during the Amman School Championship, and to investigate which of the kinematics variables contributed to the distance achieved in the long jump, and to compare the actual distance (AD) achieved by the jumper and the qualified legal distance (LED) judged. METHODS: Fifteen jumpers from Amman Secondary School were filmed at the saggital plane during the execution of three trials of long jumping. A video Camera (Sony) was set at (50) HZ/ second and was perpendicular to the plane of motion. Data from the image of the (TV) were analyzed and the following kinematics variables were calculated: flying angle (FA), take of angle (TOA), landing angle (LA), the vertical flying velocity (VFV), the horizontal flying velocity (HFV), flying velocity (FV). height of the body center of gravity at take off (HCGTO) and at landing (HCGL), take off distance (TOD), flying distance (FD). Landing distance (LD) direct distance of the last three strides from the approach (DDLSS). The data were statistically analyzed using (SAS) packages, whereby the T test and stepwise regression were used. RESULTS: It was found that there were significant differences between the (LED) and the (AD) jumped for the (AD). The (TOA) contributed by 0.39, the (TOA) and (FV) contributed by 0.47, the (TOA) and (FV) and (HCGTO) contributed by 0.61 to the total distance jumped. CONCLUSIONS: It was concluded that the three variables that contributed most to the total distance matched those factors in the Newtonian low of projectiles. It is suggested, therefore, to concentrate on making the approach run accurate and to achieve the maximal velocity for optimizing the three kinematics variables at takeoff

Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity