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A New model to Detect Worm Attacks in Cloud Computing Environment

A New model to Detect Worm Attacks in Cloud Computing Environment”
It is required that the (Chapter 3 methodology) and (Chapter 4 Results) related to my research which should cover the most important subject in my Dissertation, and you have the authority to organize the chapters.
Important Note: Kindly refer to Chapter1+Chapter2 when you draft the both chapters.
Very Very Important Note: kindly there are some Parts in this order I have to give
you approval before you draft them as the following
Part1: the data set
Part2: classification
Part3: New format for data set (nominal data)

Chapter 3: methodology
The methodology chapter may cover the following:
1-Research process (Diagram)
2-Research Design:
2.1 Data Sets
2.2-Lab architecture
2.3-Table Software Installed in Testing Lab Computers
2.4- Loading specimen and (Table for Template for Worm analysis)
2.5- Knowledge Discovery Techniques+ KDD process (KDD Processes for this researsh)
2.6-Data pre-processing
2.7-Worm Analysis process (Dynamic Analysis)
2.8-Data cleaning and transformation + (WEKA Software it is must used).
2-9- Statistical Analysis in spss like Chi-square and Symmetric Measures or any
Statistical Analysis that as you seen suitable to test classification to determine relationship between worm characteristics and quantify relationship strength in cloud
Computing.

2.10-Data Mining (Clustering+ Classification)
2.11-Genetic Algorithm +GA Pseudo code you will use these code for the program it as a new classifier to increase accuracy for detection worm in cloud computing

2.12-Data Post-processing
2.13- Summary
Note: kindly refer to my original methodology chapter that I had drafted when you
draft this chapter.
Chapter 4 Results: Results for Efficient Worm Detection Model in Cloud Computing
Environment ( EWCCDM)

The Results may cover the following and you have the authority to organize the chapter but before you start drafting it please show me on content table the area that you will cover:

– Introduction

– Model for Worm Detection in Cloud Computing Environment (Diagram)

– Related Existing Works.

– EWCCDM worm classification in cloud computing environment (Diagram) + explain all in the diagram as points and add references between paragraphs with these points when you explain.

–  Requested to collect free samples in worm data set that attack cloud server up to data (Need 800 samples or more ) and provide me.
Kindly analyze this data set using dynamic analyze and free tools like process monitoring, process Explorer, portmon, Newt pro, promiscdetect.exe, Wireshark, winzip… and so on , I need to do worm data sets classification in cloud server. -I will upload file that contain free samples of worm data set but for computer network as an example for you but to do it the same but in cloud server

– Do classifications in Excel sheet about these worm samples that attack cloud sever and transformed worm code into nominal data with numeric values (these numeric
Values are will input into machine learning algorithms weak software .–
Kindly find the excel sheet file I will upload it under name (Worm Classification)for example to do it similar but please make sure to be different to the classification in
computer network) (Request two excel sheet).

– Worm characteristic in MS Excel.

– Worm cloud in .csv format

– Worm dataset cloud in .arff formats.

-Experimental Results (WEKA evaluation result) train and test data  sets

-Frequency Analysis+ Figures.

– Statistical Analysis Results.

– EWCCDM Model for worm detection in cloud computing environment Results
– EWCCDM worm clustering +Results

– Do to programming Genetic algorithm code (Write Genetic algorithm Pseudo code and program it as a new classifier to give increase accuracy rate (be sure it must have high accuracy rate comparing with others algorithms using below.

– EWCCDM worm classification Results(Result of SMO classifier+2 Results of IBk classifier+ Results of Multilayer Perception classifier+ Results of Naive Bayes classifier+ Result of J48 classifier + Results of GA classifier.
– Summarisation of the result +Tables

– Comparison with Existing Works(Previous Studies comparing to this research )+Tables
– Summary
Important over all Notes:
-P.S: Be sure the methodology and results it must solve the problem statement and achieve all my objectives and significance and contribution of my dissertation
P.S: I will upload file under name (Worm Classification.jpg) I need the same structure but in cloud computing and the contents are must different.

P.S: The worm dataset that attack cloud server (it must different classification of computer network) it is meaning the contents of classification in cloud server it must different the contents in computer network.

Kindly refer to the word file under name (genetic algorithm (GA) Pasudo Code.doc) may be help you when you programming (GA code) as a new classifier if you can see as suitable code or you have authority to do.

– References should follow APA format and up to date and a lot of references.
– Kindly refer to the uploaded files when you draft these chapters.

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