Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams

Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams

Henson, Michael J.

Hardcover

General ComputersNetworking

ISBN10: 1025112121
ISBN13: 9781025112121
Publisher: Hutson Street Press
Published: May 22 2025
Pages: 94
Weight: 0.69
Height: 0.25 Width: 6.14 Depth: 9.21
Language: 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.

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