IMAT5235 Artificial Neural Networks Assignment

Assignment Help Other Subject

Reference no: EM132608908

IMAT5235 Artificial Neural Networks - De Montfort University

Assignment - A neural network model for detecting intrusions or attacks on a computer network

Learning outcome 1: Experience creating an ANN to solve a intrusion attack problems

Learning outcome 2: Experience pre-processing large data sets

Learning outcome 3: Experience using Matlab

Learning outcome 4: Experience using different ANN algorithms implemented in Matlab using the ANN tool box.

Tasks to be undertaken:
The aim of this project is to develop and test a neural network model to be able to detect network intrusions. The neural network model should be capable of distinguishing between ``bad'' connections, called intrusions or attacks, and ``good'' normal connections.

In order to develop this neural network model, you will use the KDD Cup 1999 Data set which was used for The Third International Knowledge Discovery and Data Mining Tools Competition.

The database contains several intrusions simulated in a military network environment.

In order to simplify things, the construction of the neural network model will be based entirely (training and testing) on kddcup.data_10_percent.gz data subset which contains a dataset sample of only 10 % of the entire dataset.
The web-link above contains all the dataset descriptions and details in terms of inputs an outputs.

Task
You have a number of tasks:

• Grab the data set kddcup.data_10_percent.gz from the web site to produce a data set for training and testing your neural network.

• Split the available data sets for training and testing the neural network. It is up to you to decide how many of the inputs are needed as well as how much data is needed to construct the neural network (training and testing data sets). You might wish to use cross validation.

• Train and test a neural network that can identify good and bad connections (intrusion or attack).

We will be looking for:

• Sensible manipulation of the data.
• Sensible choice of training and test data.
• Appropriate choice of network topology.
• Careful thought about the various design parameters for a neural network.

Attachment:- Artificial Neural Networks.rar

Reference no: EM132608908

Questions Cloud

What effect did the one-time charge have on the company : What would Starbucks' ROE have been if it had accrued a $3,700 million litigation liability (and expense)? What effect did this one-time charge

Differentiate between broker and dealer : Differentiate between broker and dealer. Write briefly note on services provided by them.

Prepare discount amortization table : Is the accountant of Jose Orozco Inc. will prepare discount amortization table? If yes, then prepare discount amortization table for coming five years.

Explain the difference between fast-tracking and crashing : Explain the difference between Fast-Tracking and Crashing. How would your choice of technique (Fast-Tracking and Crashing) impact project quality?

IMAT5235 Artificial Neural Networks Assignment : IMAT5235 Artificial Neural Networks Assignment Help and Solution, De Montfort University - Assessment Writing Service - Experience creating an ANN to solve

Decreasing pattern in annual interest payment : After amortizing a loan , we may observe a specific increasing or decreasing pattern in annual interest payment

Project plan for new internal support system : Your company has assigned you to work on a project plan for a new internal support system.

Providing conflicting results : When the two projects are mutually exclusive, the acceptance of one project precludes the acceptance of other project or projects

Why do loan sharks worry less about moral hazard : Why do loan sharks worry less about moral hazard in connection to borrowers than some other lenders do?

User Account

All Pages