A worth reading presentation on Data Mining

1. AN IMPROVED NETWORK INTRUSION DETECTION
TECHNIQUE BASED ON K-MEANS CLUSTERING VIA
NAIVE BAYES CLASSIFICATION
YOUSEF EMAMI
Yousef.emami@ieee.org
03/30/16 Data Mining's Presentation,CE&IT Faculty,Shiraz University of Technology 1

2. AGENDA
Intrusion Detection
Dataset Description
THE PROPOSED MODEL FOR NIDS
EXPERIMENT AND RESULTS
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3. INTRUSION DETECTION
An Intrusion Detection System (IDS) inspects the activities in a
system for suspicious behaviour or patterns that may indicate
system attack or misuse.
There are two main categories of intrusion detection techniques;
 Anomaly detection
Misuse detection
Here ,the performance of K-means clustering and naïve classifier
when trained to identify signature of specific attacks is reviewed.
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4. DATASET DESCRIPTION
The utilized data set is KDD Cup which contained a wide variety of
intrusions simulated in a military network environment
It consisted of approximately 4,900,000 data instances
The simulated attacks fell in one of the following four categories:
DOS-Denial of Service (e.g. a syn flood),
R2L- Unauthorized access from a remote machine (e.g. password
guessing),
 U2R-Unauthorized access to super user or root functions (e.g. a buffer
overflow attack)
 Probing-surveillance and other probing for vulnerabilities (e.g. port
scanning).
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5. K-MEANS CLUSTERING VIA NAIVE BAYES CLASSIFICATION MODEL
FOR NIDS
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6. Metrics
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Data Mining's Presentation,CE&IT Faculty,Shiraz University of
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Data Mining's Presentation,CE&IT Faculty,Shiraz University of
Technology
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11. Thank you for your kind attention
03/30/16
Data Mining's Presentation,CE&IT Faculty,Shiraz University of
Technology
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12. REFERENCE
• Sanjay Kumar Sharmai, Pankaj Pande, Susheel Kumar Tiwari and Mahendra Singh Sisodiai,”An Improved Network Intrusion
Detection Technique based on k-Means Clustering via NaIve Bayes Classification”, IEEE-International Conference On
Advances In Engineering, Science And Management (ICAESM -2012) March 30, 31, 2012
03/30/16
Data Mining's Presentation,CE&IT Faculty,Shiraz University of
Technology
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