Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams

Michael J Henson

ISBN 10: 1288286082 / ISBN 13: 9781288286089

Published by Biblioscholar, 2012

About this Item

This item is printed on demand. New copy - Usually dispatched within 5-9 working days 216.

Seller Inventory # C9781288286089

Bibliographic Details

• Title: Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams
• Publisher: Biblioscholar
• Publication Date: 2012
• Language: English
• ISBN 10: 1288286082
• ISBN 13: 9781288286089
• Binding: Paperback / softback
• Condition: New
• Weight: 216 grams

About this title

Synopsis

As wireless networks become an increasingly common part of the infrastructure in industrialized nations, the vulnerabilities of this technology need to be evaluated. Even though there have been major advancements in encryption technology, security protocols and packet header obfuscation techniques, other distinguishing characteristics do exist in wireless network traffic. These characteristics include packet size, signal strength, channel utilization and others. Using these characteristics, windows of size 11, 31, and 51 packets are collected and machine learning (ML) techniques are trained to classify applications accessing the 802.11b wireless channel. The four applications used for this study included E-Mail, FTP, HTTP, and Print.