Time filter

Source Type

Sharma M.G.,Mahakal Institute of Technology
IFIP International Conference on Wireless and Optical Communications Networks, WOCN | Year: 2012

The effect of channel bit error rate on the distortion of the image transmitted on an AWGN channel has been considered and a statistical relationship between the two has been presented and verified by simulation. © 2012 IEEE.

Tripathi A.,Mahakal Institute of Technology | Singh U.K.,Vikram University
ICCTD 2010 - 2010 2nd International Conference on Computer Technology and Development, Proceedings | Year: 2010

One of the major problem in information system security assessment is lack of standard vulnerability categorization scheme or taxonomy. Various analyses indicated that majority of software vulnerabilities tend to focus in few areas and associated with small set of services. An effective vulnerability taxonomy that can relate vulnerability causes, effects and countermeasures can aid in security assessment. Researchers and security analysts also widely recognized the need of standard vulnerability taxonomy for security assessment and measurement of software tools, services and systems. Keeping in view high rising need of such standard taxonomy of vulnerability, prominent efforts in this direction are critically reviewed. Status of efforts towards categorization of CVE dictionary is also examined. This paper aims to help researchers in developing standard vulnerability taxonomy by highlighting common pitfalls associated with previous efforts and provide guidelines for future work. © 2010 IEEE.

Tripathi A.,Mahakal Institute of Technology | Singh U.K.,Vikram University
Proceedings - 6th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2011 | Year: 2011

In view of increasing population of vulnerabilities, quantitative evaluation of vulnerabilities is necessary for efficient mitigation. Evaluation on classified vulnerability datasets can further improve the mitigation process. Objective of this paper is to develop security metrics to prioritize vulnerability categories based on CVSS scores to step ahead in this regard. In this context, security metrics are developed to reevaluate and unify vulnerability severity scores depending on availability of patches and age of vulnerability. Proposed metrics are applied on 5177 vulnerabilities extracted from NVD published in recent one year and vulnerability categories are prioritized and ranked based on cumulative severity scores. © 2011 AICIT.

Tripathi A.,Mahakal Institute of Technology | Singh U.K.,Vikram University
Proceedings - 6th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2011 | Year: 2011

Quantitative risk assessment of system security is emerging as an important research area in view of increasing population of vulnerabilities. Assessment on classified vulnerability datasets leads to effective vulnerability mitigation and risk analysis. An effective vulnerability classification scheme under rich taxonomic features that relates cause, impact and risk level can serve the purpose. However there is no common classification scheme in this regard. The focus of our research is taxonomic analysis of classification schemes in pertinent vulnerability databases, so as to identify issues involved and form a basis for development of a common classification scheme. Our objective is to shape and mature a classification scheme to accelerate research in the quantitative evaluation of risk levels as a measure of system security. © 2011 AICIT.

Pandey S.,Mahakal Institute of Technology | Hindoliya D.A.,Ujjain Engineering College | Mod R.,Mahakal Institute of Technology
Applied Soft Computing Journal | Year: 2012

Three passive cooling methods (e.g. roof pond, reflective roof cooling and using insulation over the roof) have been experimentally evaluated using an experimental test structure. The objective of this work is to train an artificial neural network (ANN) to learn and predict the indoor temperature of room with the different experimental data. Different training algorithms (traingd, traingdm, traingdx, trainrp, traincgp, traincgf, traincgb, trainscg, trainbfg, trainoss, trainlm, and trainbr) were used to create an ANN model. This study is helpful in finding the thermal comfort of building by applying different passive cooling techniques. The data presented as input were outside temperature, relative humidity, solar intensity and wind speed. The network output was indoor temperature. The advantages of this approach are (i) the speed of calculation, (ii) the simplicity, (iii) adaptive learning from examples and thus gradually improve its performance, (iv) self-organization and (vi) real time operation. Results proved highly satisfactory and provided enough confidence for the process to be extended to a larger solution space for which there is uneconomical and time consuming way of calculating the solution. © 2011 Elsevier B.V. All rights reserved.

Discover hidden collaborations