Designing A Logical Security Framework for E-Commerce System Based on SOA

Ashish Kr. Luhach1, Dr. Sanjay K. Dwivedi2, Dr. C. K. Jha3

1Dronacharya College of Engineering, Gurgaon, Hr, India

2BBA University, Lucknow, U.P., India

3Banasthali University, Jaipur, Rajasthan, India.

Abstract

Rapid increases in information technology also changed the existing markets and transformed them into emarkets (e-commerce) from physical markets. Equally with the e-commerce evolution, enterprises have to recover a safer approach for implementing E-commerce and maintaining its logical security. SOA is one of the best techniques to fulfill these requirements. SOA holds the vantage of being easy to use, flexible, and recyclable. With the advantages, SOA is also endowed with ease for message tampering and unauthorized access. This causes the security technology implementation of E-commerce very difficult at other engineering sciences. This paper discusses the importance of using SOA in E-commerce and identifies the flaws in the existing security analysis of E-commerce platforms. On the foundation of identifying defects, this editorial also suggested an implementation design of the logical security framework for SOA supported E-commerce system.

Keywords

Service oriented Architecture, web services, system consolidation, logical security.

Original Source URL: https://airccse.org/journal/ijsc/papers/5214ijsc01.pdf

https://airccse.org/journal/ijsc/current2014.html

An Artificial Neural Network Model for Classification of Epileptic Seizures Using Huang-Hilbert Transform

Shaik.Jakeer Husain1 and Dr.K.S.Rao2

1Dept. of Electronics and Communication Engineering , Vidya Jyothi Institute of Technology, Hyderabad India

ABSTRACT

Epilepsy is one of the most common neurological disorders characterized by transient and unexpected electrical disturbance in the brain. In This paper the EEG signals are decomposed into a finite set of band limited signals termed as Intrinsic mode functions. The Hilbert transom is applied on these IMF’s to calculate instantaneous frequencies. The 2nd,3rd and 4th IMF's are used to extract features of epileptic signal. A neural network using back propagation algorithm is implemented for classification of epilepsy. An overall accuracy of 99.8% is achieved in classification.

KEYWORDS

Electroencephalogram(EEG),Hilbert-Huang transform(HHT), Instantaneous frequency (ifs), intrinsic mode function (IMF) 

Original Source URL: https://airccse.org/journal/ijsc/papers/5314ijsc03.pdf

https://airccse.org/journal/ijsc/current2014.html

Perfusion System Controller Strategies during an ECMO Support

M.Dhinakaran and S.Abraham Lincon, Annamalai University, India

ABSTRACT

In this work modelling and control of Perfusion system is presented. The Perfusion system simultaneously controls the partial pressures during Extra Corporeal Membrane Oxygenation (ECMO) support. The main Problem in ECMO system is exchange of Blood Gases in the Artificial Lung (Oxygenator).It is a highly Nonlinear Process comprising time-varying parameters, and varying time delays, it is currently being controlled manually by trained Perfusionist. The new control strategy implemented here has a feedback linearization routine with time-delay compensation for the Partial pressuresof Oxygen and Carbon dioxide. The controllers were tuned robustly and tested in simulations with a detailed artificial Lung (Oxygenator) model in Cardiopulmonary bypass conditions. This Automatic control strategy is proposed to improve the patient’s safety by fast control reference tracking and good disturbance rejection under varying conditions.

KEYWORDS

Cardio Pulmonary Bypass (CPB), Blood Gas Analyser (BGA), Extra Corporeal Membrane Oxygenator (ECMO)

Original Source URL: https://airccse.org/journal/ijsc/papers/5314ijsc02.pdf

https://airccse.org/journal/ijsc/current2014.html