Open Daily: 10am - 10pm | Alley door 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

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Network Classification for Traffic Management: Anomaly Detection, Feature Selection, Clustering and Classification

Network Classification for Traffic Management: Anomaly Detection, Feature Selection, Clustering and Classification

Tari, Zahir
Fahad, Adil
Almalawi, Abdulmohsen

Hardcover

Series: Computing and Networks

Networking

ISBN10: 1785619217
ISBN13: 9781785619212
Publisher: Institution Of Engineering & T
Published: Mar 23 2020
Pages: 288
Weight: 1.30
Height: 0.90 Width: 6.40 Depth: 9.20
Language: English

With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks.

Also in

Networking

View All