Modeling worms propagation on probability

There are the two common means for propagating worms: scanning vulnerable computers in the network and sending out malicious email attachments. Modeling the propagation of worms can help us understand how worms spread and devise effective defence strategies. Most traditional models simulate the overall scale of infected network in each time tick, making them invalid for examining deep inside the propagation procedure among individual nodes. For this reason, this paper proposes a novel probability matrix to model the propagation mechanism of the two main classes of worms (scanning and email worms) by concentrating on the propagation probability. The objective of this paper is to access the spreading and work out an effective scheme against the worms. In order to evaluate the effects of each major component in our probability model, we implement a series of experiments for both worms. From the results, the network administrators can make decision on how to reduce the number of vulnerable nodes to a certain threshold for scanning worms, and how to immunize the highly-connected node for preventing worm's propagation for email worms.

The probability model of peer-to-peer botnet propagation

Active Peer-to-Peer worms are great threat to the network security since they can propagate in automated ways and flood the Internet within a very short duration. Modeling a propagation process can help us to devise effective strategies against a worm's spread. This paper presents a study on modeling a worm's propagation probability in a P2P overlay network and proposes an optimized patch strategy for defenders. Firstly, we present a probability matrix model to construct the propagation of P2P worms. Our model involves three indispensible aspects for propagation: infected state, vulnerability distribution and patch strategy. Based on a fully connected graph, our comprehensive model is highly suited for real world cases like Code Red II. Finally, by inspecting the propagation procedure, we propose four basic tactics for defense of P2P botnets. The rationale is exposed by our simulated experiments and the results show these tactics are of effective and have considerable worth in being applied in real-world networks.

Metrics of the normal cornea : anterior segment imaging with the Visante OCT

Purpose:  The purpose of the study was to obtain anterior segment biometry for 40 normal eyes and to measure variables that may be useful to design large diameter gas permeable contact lenses that sit outside the region normally viewed by corneal topographers. Also, the distribution of these variables in the normal eye and how well they correlated to each other were determined.

Methods:  This is a cross-sectional study, in which data were collected at a single study visit. Corneal topography and imaging of the anterior segment of the eye were performed using the Orbscan II and Visante OCT. The variables that were collected were horizontal K reading, central corneal/scleral sagittal depth at 15 mm chord, and nasal and temporal angles at the 15 mm chord using the built-in software measurement tools.

Results:  The central horizontal K readings for the 40 eyes were 43 ± 1.73 D (7.85 ± 0.31 mm), with ± 95% confidence interval (CI) of 38.7 (8.7 mm) and 46.6 D (7.24 mm). The mean corneal/scleral sagittal depth at the 15 mm chord was 3.74 ± 0.19 mm and the range was 3.14 to 4.04 mm. The average nasal angle (which was not different from the temporal angle) at the 15 mm chord was 39.32 ± 3.07 degrees and the ± 95%CI was 33.7 and 45.5 degrees. The correlation coefficient comparing the K reading and the corneal/scleral sagittal depth showed the best correlation (0.58, p < 0.001). The corneal/scleral sagittal depth at 15 mm correlated less with the nasal angle (0.44, p = 0.004) and the weakest correlation was for the nasal angle at 15 mm with the horizontal readings (0.32, p = 0.046).

Conclusion:  The Visante OCT is a valuable tool for imaging the anterior segment of the eye. The Visante OCT is especially effective in providing the biometry of the peripheral cornea and sclera and may help in fitting GP lenses with a higher percentage of initial lens success, when the corneal sag and lens sag are better matched.

Contests with the probability of a draw : a stochastic foundation

This article proposes a stochastic foundation for the contest success function (CSF for short) with a richer structure on the set of possible outcomes of the contest. Specifically, the analysis allows for the possibility of a draw, so that no contestant can claim a victory over all other players. Under plausible conditions, this article not only discovers new functional forms of CSFs, but also shows the newly derived CSFs have very different properties in equilibrium to those of conventional CSFs. For example, in contrast to the CSFs discussed in the contest literature, which always generate a unique pure strategy Nash equilibrium, the newly discovered CSFs admit the possibility of multiple equilibria.

Probability distributions of number of children and maternal age at various order births using age-specific fertility rates by birth order

In this study, a simple analytical framework to find the probability distributions of number of children and maternal age at various order births by making use of data on age-specific fertility rates by birth order was proposed. The proposed framework is applicable to both the period and cohort fertility schedules. The most appealing point of the proposed framework is that it does not require stringent assumptions. The proposed framework has been applied to the cohort birth order-specific fertility schedules of India and its different regions and period birth order-specific fertility schedules, including the United States of America, Russia, and the Netherlands, to demonstrate its usefulness.

Image fusion metrics : evolution in a nutshell

Image fusion process merges two images into a single more informative image. Objective image fusion per- formance metrics rely primarily on measuring the amount of information transferred from each source image into the fused image. Objective image fusion metrics have evolved from image processing dissimilarity metrics. Additionally, researchers have developed many additions to image dissimilarity metrics in order to better value the local fusion worthy features in source images. This paper studies the evolution of objective image fusion performance metrics and their subjective and objective validation. It describes how a fusion performance metric evolves starting with image dissimilarity metrics, its realization into image fusion contexts, its localized weighting factors and the validation process.