Botnet Detection Using Graph Based Feature Clustering

Detecting botnets in a network is crucial because bot-activities impact numerous areas such as security, finance, health care, and law enforcement. Most existing rule and flow-based detection methods may not be capable of detecting bot-activities in an efficient manner. Hence, designing a robust botnet-detection method is of high significance. In this study, we propose a botnet-detection methodology based on graph-based features. Self-Organizing Map is applied to establish the clusters of nodes in the network based on these features. Our method is capable of isolating bots in small clusters while containing most normal nodes in the big-clusters. A filtering procedure is also developed to further enhance the algorithm efficiency by removing inactive nodes from bot detection. The methodology is verified using real-world CTU-13 and ISCX botnet datasets and benchmarked against classification-based detection methods. The results show that our proposed method can efficiently detect the bots despite their varying behaviors

A Study on Pulmonary Tuberculosis and Diabetes in Eluru- A Dual Burden

Background: The Tuberculosis-Diabetes mellitus(TB-DM) co-morbidity is one of the rising public health problem and the studies in this part of country on TB-DM co-morbidities are lesser. We need more evidence base for the management of the dual burden of TB and Diabetes Mellitus.Aim & Objective: To know the prevalence of diabetes mellitus among pulmonary tuberculosis patients.Methodology: This was a community based cross sectional study carried out in the tuberculosis unit (TU) area of Eluru, Andhra Pradesh. This study was conducted from 1st June 2018 to November 31 st, 2018.Results: In the present study, the overall prevalence of diabetes mellitus among pulmonary tuberculosis was found to be 31%. Highest (35.7%) prevalence of diabetes Mellitus was noticed in 18-30 years of age group. There was statistically significant association was found between male sex and diabetes mellitus among pulmonary tuberculosis patients (p <0.05). The association between marital status and diabetes mellitus among pulmonary tuberculosis was found to be statistically significant (p<0.05). There was statistically significant association was found between high socio economic status and diabetes mellitus among pulmonary tuberculosis patients (p <0.05). The association between residential status, tobacco intake, type of smoking and duration of smoking, housing condition and diabetes mellitus among pulmonary tuberculosis was found to be statistically significant (p<0.001, P<0.0001).Prevalence of diabetes mellitus among pulmonary tuberculosis was high among chewers who are chewing for more than 20 yrs (66.7%).The association between physical activity, duration of exercise and diabetes among pulmonary tuberculosis was found to be statistically significant (p<0.05, P< 0.02).The association between amount of BMI status and diabetes among pulmonary tuberculosis was found to be statistically significant (p<0.05). Increasing BMI increases the Diabetes among pulmonary TB patients.The association between hypertension status and diabetes among pulmonary tuberculosis was found to be statistically significant (p<0.01).Prevalence of diabetes mellitus among pulmonary tuberculosis was high among the patients who are smear positive 32.0 % and low among the smear negative patients 28.9%.Conclusion:Prevalence of Diabetes mellitus among pulmonary Tuberculosis patients was high and also observed high prevalence among bad life style modifications adopting individuals