Bilal Hikmat Rasheed

M.S.

Computer Science & (IT)

B.S

Computer Science

Assistant Lecturer

Academic & Researchers Platform

University E- Learning

Peshmarga Hall

Editi staff accounts and modified

Teaching method for higher education

Certificate

Managing Interconnected device

Managing Interconnected device

Diploma in .NET technology

.NET

English Language Programme

English Language

Calibration Techniques for Securing Web Application in Dual Delegation Interoperability Network Model with Green Communication

With the increase in the growth of the Internet, web applications such as net banking, online shopping, social networking and email communications have become central and essential part of our everyday life. Web pages are no longer static; they contain dynamic content from diverse sources that may be trusted or untrusted. Providing a good security for the web application and its user becomes hard, expensive, time consuming and quite confusing. However, mitigating the attacks to secure the web application has become very essential and one of the primary liability of the web developers and researchers. Securing the web applications becomes paramount and it is an intricate process with the current technologies since they are very complex to understand, implement and maintain. Thus, the main goal of this research is to reduce the attack by minimizing the amount of time needed to create and maintain the approach. A model named “Dual Delegation Model” to protect the web applications from session attacks has been implemented on client-side and on the server-side. This DDM could be added to the client and server as delegates, does the security checks, and manage the sessions by monitoring the communications between client and the server. Keywords: Web Application, Security, Dual Delegation Model, Accuracy

An Improved Novel ANN Model for Detection of DDoS Attacks On Networks

Attacks over the internet have become an increasing menace in recent time which tries to hack or illegally tamper with the data available over the networks. On the other hand, there has been an increase in volume in research contributions to effectively counter attack these attacks and implement a strong defence mechanism. There have been numerous algorithms and frameworks implemented in recent times which are intelligent and soft computing based. These evolution based algorithms play a vital role in self adapting the system under attack towards increasing and new types of attacks which are increasing day by day. One such area of soft computing algorithms investigated in this chapter is the artificial neural network or popularly known as ANNs. They work analogous to the biological neurons in the human body. The chapter is organized in a systematic manner to give an insight in to ANN based network models to counter attack DDoS attacks which has been the primary focus of this thesis, architecture and implementation of ANNs, the experimental investigations and findings which help in drawing an inference of ANN based defence models. Key words: Network attacks, distributed denial of service attacks, ANN, training and confusion matrix.