Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams

Henson, Michael J.

ISBN 10: 1288286082 / ISBN 13: 9781288286089

Published by BiblioScholar 2012-11, 2012

About this Item

Seller Inventory # 6666-IUK-9781288286089

Bibliographic Details

• Title: Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams
• Publisher: BiblioScholar 2012-11
• Publication Date: 2012
• Language: English
• ISBN 10: 1288286082
• ISBN 13: 9781288286089
• Binding: PF
• Condition: New

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.