Share
Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams (in English)
Michael J. Henson
(Author)
·
Biblioscholar
· Paperback
Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams (in English) - Henson, Michael J.
$ 48.80
$ 57.95
You save: $ 9.15
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My WishlistsIt will be shipped from our warehouse between
Friday, July 05 and
Monday, July 08.
You will receive it anywhere in United States between 1 and 3 business days after shipment.
Synopsis "Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams (in English)"
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.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
