1. Intrusion Detection with Neural Networks my awesome graphic ↑
Mary Krajnak

2. Problem Definition Computers an essential part of our lives
Security has become an essential issue
Methods of hand-coded rules for detecting misuse are not reliable and are labor intensive
Need an intrusion detection system which works by modeling “normal behavior” to detect anomalies.

3. Data & ANN Structure DARPA Intrusion Detection Evaluation Session:
Collection of controlled TCP/IP connections which model normal network behavior
Session:
<Session ID, Start date, Start time, Duration, Service, Src port, Dest port, Src IP, Dest IP, Attack score, Attack name>
Backpropagation Neural Network
Data most likely not linearly seperable

4. Initial Work and Results
Extracted features from TCP/IP dump
Created program to extract & convert
Created a Backpropagation neural network in F90
Speed important in network security
Initial results

5. Work To Be Done Pre-process data to obtain better results
Currently using four features
<duration, service, source port, destination port>
Feature reduction/addition may improve
Implement C++ Backpropagation algorithm
Speed comparable, may make up for authors penchant for mistakes in Fortran 90