Information Segmentation and Investing in Cybersecurity

This paper provides an analysis of how the benefits of information segmentation can assist an organization to derive the appropriate amount to invest in cybersecurity from a cost-benefit perspective. An analytical model based on the framework of the Gordon-Loeb Model ([1]) is presented that provides a set of sufficient conditions for information segmentation to lower the total investments in cybersecurity and the expected loss from cybersecurity breaches. A numerical example illustrating the insights gained from the model is also presented.

Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Steganography technology has been widely used in data transmission with secret information.However,the existing steganography has the disadvantages of low hidden information capacity,poor visual effect of cover images,and is hard to guarantee security.To solve these problems,steganography using reversible texture synthesis based on seeded region growing and LSB is proposed.Secret information is embedded in the process of synthesizing texture image from the existing natural texture.Firstly,we refine the visual effect.Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.We use seeded region growing algorithm to ensure texture’s similar local appearance.Secondly,the size and capacity of image can be decreased by introducing the information segmentation,because the capacity of the secret information is proportional to the size of the synthetic texture.Thirdly,enhanced security is also a contribution in this research,because our method does not need to transmit parameters for secret information extraction.LSB is used to embed these parameters in the synthetic texture.

INFLUENCE OF ANTIDROM IC ELECTRIC STIM ULATI ON ONPREPROTACHYKININ m RNA EXPRESSION IN ADJACENT DORSAL ROOT GANGLIA OF RATS

By in situ hybridization histochemistry, the changes of preprotachykinin (PPT) mRNA expression were examined in the neurons of adjacent thoracal dorsal root ganglion (DRG) after a strong electric stimulation to an intact dorsal cutaneous branch and the cut distal part of left T 9 thoracal spinal nerve of rat. There was a significant increase of the number of neurons expressing PPT mRNA in the ipsilateral T 8, T 9 and T 10 DRG of the animals given electric stimulation to intact spinal nerve branch 24 h after the electric stimulation. The same increase was found in the ipsilateral T 8 and T 10 DRG of the animals given electric stimulation to the distal part of spinal nerve branch. While no change was found in the DRG of the contralateral side of these animals. The present results showed that the antidromic electric stimulation strengthened the biosynthesis of PPT mRNA in adjacent DRG. These findings suggested that there was information transmission across segments between two sensory nerve endings and some bioactive substances such as SP might play important roles in the information transmission across segments of spinal cord.

Novel Model Using Kernel Function and Local Intensity Information for Noise Image Segmentation

It remains a challenging task to segment images that are distorted by noise and intensity inhomogeneity.To overcome these problems, in this paper, we present a novel region-based active contour model based on local intensity information and a kernel metric. By introducing intensity information about the local region, the proposed model can accurately segment images with intensity inhomogeneity. To enhance the model＇s robustness to noise and outliers, we introduce a kernel metric as its objective functional. To more accurately detect boundaries, we apply convex optimization to this new model, which uses a weighted total-variation norm given by an edge indicator function. Lastly, we use the split Bregman iteration method to obtain the numerical solution. We conducted an extensive series of experiments on both synthetic and real images to evaluate our proposed method, and the results demonstrate significant improvements in terms of efficiency and accuracy, compared with the performance of currently popular methods.