Coulomb Drag in Graphene

We study the Coulomb drag between two single graphene sheets in intrinsic and extrinsic graphene systems with no interlayer tunneling. The general expression for the nonlinear susceptibility appropriate for single-layer graphene systems is derived using the diagrammatic perturbation theory, and the corresponding exact zero-temperature expression is obtained analytically. We find that, despite the existence of a non-zero conductivity in an intrinsic graphene layer, the Coulomb drag between intrinsic graphene layers vanishes at all temperatures. In extrinsic systems, we obtain numerical results and an approximate analytical result for the drag resistivity $\rho_{\textrm{D}}$, and find that $\rho_{\textrm{D}}$ goes as $T^2$ at low temperature $T$, as $1/d^4$ for large bilayer separation $d$ and $1/n^3$ for high carrier density $n$. We also discuss qualitatively the effect of plasmon-induced enhancement on the Coulomb drag, which should occur at a temperature of the order of or higher than the Fermi temperature

An Empirical Study of Switching Behavior toward Cloud Storage Services

With the rapid development of cloud storage, it is necessary to determine the mechanism of cloud storage adoption. Based on social exchange theory, technology acceptance model and perceived risk theory, this study attempts to explore the switching factors and to empirically examine the relationship between those and users’ intention to switch to cloud storage services. This study quantitatively analyzes the data to obtain the significance level of each variable and a model of the influence mechanism of cloud storage switching intention is obtained. Our main results suggest that perceived ease of use and perceived usefulness have a significantly positive impact on related benefits. Information loss risk and time risk have a significantly positive impact on related costs while information leakage risk does not influence significantly. Related benefits have a significant positive impact on switching intention while related costs have a significantly negative impact on it

Anonymous web browsing through predicted pages

Anonymous web browsing is an emerging hot topic with many potential applications for privacy and security. However, research on low latency anonymous communication, such as web browsing, is quite limited; one reason is the intolerable delay caused by the current dominant dummy packet padding strategy, as a result, it is hard to satisfy perfect anonymity and limited delay at the same time for web browsing. In this paper, we extend our previous proposal on using prefetched web pages as cover traffic to obtain perfect anonymity for anonymous web browsing, we further explore different aspects in this direction. Based on Shannon&rsquo;s perfect secrecy theory, we formally established a mathematical model for the problem, and defined a metric to measure the cost of achieving perfect anonymity. The experiments on a real world data set demonstrated that the proposed strategy can reduce delay more than ten times compared to the dummy packet padding methods, which confirmed the vast potentials of the proposed strategy.<br /