Intrusion Alerts Analysis Using Attack Graphs and Clustering

Network and information security is very crucial in keeping large information infrastructures safe and secure. Many researchers have been working on different issues to strengthen and measure security of a network. An important problem is to model security in order to apply analysis schemes efficiently to that model. An attack graph is a tool to model security of a network which considers individual vulnerabilities in a global view where individual hosts are interconnected. The analysis of intrusion alert information is very important for security evaluation of the system. Because of the huge number of alerts raised by intrusion detection systems, it becomes difficult for security experts to analyze individual alerts. Researchers have worked to address this problem by clustering individual alerts based on similarity in their features such as source IP address, destination IP address, port numbers and others. In this paper, a different method for clustering intrusion alerts is proposed. Sequences of intrusion alerts are prepared by dividing all alerts according to specified time interval. The alert sequences are considered as temporal attack graphs. The sequences are clustered using graph clustering technique, which considers similarity in sequences as a factor to determine closeness of sequences. The suggested approach combines the concept of attack graphs and clustering on sequences of alerts using graph clustering technique

Investigating the sensitivity of juvenile social exploration at detecting the affective consequences accompanying chronic neuropathic pain

Chronic neuropathic pain debilitates millions of lives globally and exerts substantial emotional hardship, particularly in the form of major depressive disorder, on its sufferers. Despite extensive research, the biological basis of interaction between pain and its affective consequences remains largely elusive. A growing body of literature suggests chronic neuropathic pain and major depressive disorder may have similar underlying causes rooted in neuroinflammation. Establishing a paradigm to study the comorbidity of pain and its affective implications would be invaluable in the process of developing holistic treatment options. Here, we investigate the sensitivity of an anxiety-based behavioral test, juvenile social exploration (JSE), at detecting the affective repercussions of chronic neuropathic pain, simulated by chronic constriction injury, in male Sprague Dawley rats over the course of 28 days. Although statistically significant differences in interaction times were observed between the experimental groups on day 7 post-surgery, these differences were not observed on the following days post-surgery. A morphine time course was employed to exacerbate the effects of inflammation with the hope of creating greater separation between the groups but this manipulation produced contradicting behavioral data. A ceiling effect was suspected so a 3-minute pre-exposure trial was conducted; but again, this modification resulted in unremarkable data. Despite the negative results of JSE in this exploratory study, other behavioral assays might prove to be more sensitive at detecting the affective implications of chronic neuropathic pain. Further research into developing a reliable model of chronic neuropathic pain and its affective complications is desperately warranted

Review on PAR Reduction Techniques for MIMO-OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier communication scheme Plays a prominent role in wireless communication technology as multicarrier transmission scheme. The combination of multiple-input multiple-output (MIMO) technology with orthogonal frequency division multiplexing is an attractive solution for next generation of wireless network. However, practical implementation of OFDM introduced a major drawback known as high Peak-to-Average Power ratio (PAR). This paper inclusion detail of peak-to-Average Power ratio and its reduction techniques

Prevalence of non-alcoholic fatty liver disease in type-2 diabetes mellitus patients

Background: Non-alcoholic fatty liver disease (NAFLD) is a common chronic condition of which diabetic fatty liver accounts for a large proportion, with 50 to 75% of the subjects demonstrating fat in the liver on ultrasound. As a result of epidemic increase in diabetes mellitus, hypertension, obesity and hyperlipidemia, the prevalence of NAFLD is increasing worldwide.Methods: A study was conducted on a total 100 type-2 diabetes mellitus patients attending Geetanjali Medical College and Hospital, Udaipur, Rajasthan. Patients with known chronic liver disease and history of alcohol intake were excluded. These patients were evaluated by abdominal ultrasonography to determine the presence of fatty liver. They were divided into fatty liver group and non-fatty liver group; and were further evaluated by measurement of body mass index, Central obesity, HbA1c and lipid profile. The data obtained was analyzed using SPSS version 20.0.Results: Of the 100 diabetic patients enrolled in this study, 64 (64%) presented with NAFLD. The highest prevalence of NAFLD was recorded in the age group of 50-59 years at 37.5%. The prevalence rate among males (65.62%) was higher than for females (34.38%). A comprised NAFLD patients (64%) and Non-NAFLD patients (34%).Conclusions: This study revealed that the NAFLD is a vital part of cluster of abnormalities such as dysglycemia, dyslipidemia, hypertension and obesity. Age and duration of diabetes are also important contributing factors in occurrence of NAFLD

A Review on Different Image De-noising Methods

Image de-noising is a classical yet fundamental problem in low level vision, as well as an ideal test bed to evaluate various statistical image modeling methods. The restoration of a blurry or noisy image is commonly performed with a MAP estimator, which maximizes a posterior probability to reconstruct a clean image from a degraded image. A MAP estimator, when us ed with a sparse gradient image prior, reconstructs piecewise smooth images and typically removes textures that are important for visual realism. One of the most challenging problems in image de - noising is how to preserve the fine scale texture structures while removing noise. Various natural image priors, such as gradient based prior, nonlocal self - similarity prior, and sparsity prior, have been extensively exploited for noise removal. The de - noising algorithms based on these priors, however, tend to smoo th the detailed image textures, degrading the image visual quality. To address this problem, we propose a texture enhanced image de - noising (TEID) method by enforcing the gradient distribution of the de - noised image to be close to the estimated gradient d istribution of the original image. Another method is an alternative de - convolution method called iterative distribution reweighting (IDR) which imposes a global constraint on gradients so that are constructed image should have a gradient distribution simil ar to a reference distribution

Experimental Evaluation and Performance of Window Air Conditioner by Using Pre-Cooled Air in Condenser

Reduction of energy consumption is a major concern in the vapor compression refrigeration cycle especially in the area with very hot weather conditions (about 50 ºC), where window-air conditioners are usually used to cool homes. Research programs in order to improve the performance of window-air-conditioners by enhancing heat transfer rate in the condenser. In this system air is cooled outside the window air conditioner, and this cold air is fed over the condenser tubes. After to this greater amount of heat rejected from refrigerant vapor and low condensation pressure is obtained, which in turn increase Coefficient of performance (COP) of air conditioner. Air is pre-cooled in a device, in which atmospheric air is directly contact with water which comes from top of the device in fine droplets. Due to contact between air-water, air is cooled and passes to air conditioner. Practical performance shows that, by this arrangement reduces power consumption and improving performance of air-conditioner

Experimental Investigation on Effective Copper Conduction Path Thickness for Multilayer Absorber Plate Type Solar Still

Solar still is a best alternative solution against most of the conventional water distillation system. The multilayer absorber plate type solar still is the more effective technique to enhance the passive solar still productivity. The experiment has been carried out to find out the best thickness of copper conduction path for the multilayer absorber plate type solar still. The results have concluded that the productivity of solar still is reduced with increasing the conduction path thickness and water depth. The maximum productivity of distilled water has been produced in the multilayer absorber type solar still with 0.5cm thick copper conduction path and 1cm water depth

DETERMINATION OF S-METHYL L-CYSTEINE BY HIGH-PERFORMANCE LIQUID CHROMATOGRAPHIC METHOD

Objective: A simple, reproducible and sensitive high-performance liquid chromatography method has been developed for determination of S-Methyl L-Cysteine. S-Methyl L-Cysteine is widely observed and most common amino acid in plants, including many edible vegetables, which is responsible for reducing blood cholesterol level in the body. Methods: S-Methyl L-Cysteine was chromatographed using Phosphate buffer of pH 6.5: Acetonitrile in the ratio of 97:3. The liquid chromatogram was equipped with a variable wavelength UV detector, an injector and a data processor. Inertsustain GL-Science Column C-18 (150 mm x 4.6 mm; 5μ) was used as a stationary phase. Results: The retention time of S-Methyl L-Cysteine was observed as 2.261±0.0016 min. The linearity value for S-Methyl L-Cysteine was found to be 100-2000 µg/ml with Correlation of Determination (R2) value as 0.9992. LOD and LOQ values obtained are 29.51μg/ml and 89.74 μg/ml, respectively. Conclusion: The method was developed and validated successfully as per ICH guidelines for analytical method validation

Lanthanum triflate triggered synthesis of tetrahydroquinazolinone derivatives of N-allyl quinolone and their biological assessment

A series of 24 derivatives of tetrahydroquinazolinone has been synthesized by one-pot cyclocondensation reaction of N-allyl quinolones, cyclic β-diketones and (thio)urea/N-phenylthiourea in presence of lanthanum triflate catalyst. This methodology allowed us to achieve the products in excellent yield by stirring at room temperature. All the synthesized compounds were investigated against a representative panel of pathogenic strains using broth microdilution MIC (minimum inhibitory concentration) method for their in vitro antimicrobial activity. Amongst these sets of heterocyclic compounds 5h, 6b, 6h, 5f, 5l, 5n and 6g found to have admirable activity

The Impact of the Big Data on the Healthcare Information Systems

This article explores the possible implications of the big data on Informatics of health. Possible research questions are: 1). What are the applications in health care information systems are the most affected? 2). What algorithm/program shall be used for big data? 3). What the privacy, security, and ethical issues are there for big data? In the field of biology, big data becomes the latest technology for genomics. Other possible areas: Parma co monitoring, the care of patients and the management of the chain of medical supplies