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Filtering by: Advisor Mazzuchi, Thomas A Advisor Sarkani, Shahram Keyword Cybersecurity Keyword Adaptive Boosting Keyword Machine Learning

Application of a Novel Multiple Kernel Learning Framework for Improving the Robustness of Network Intrusion Detection

Description:

Current day Network Intrusion Detection Systems have several shortcomings such as high rates of false positive alerts, low detection rates of rare but dangerous attacks and the need for constant human intervention and tuning. Daily reports of incidents appear in public media including major...

Author:

Fossaceca, John M.

Keyword:

Cybersecurity, Pattern Recognition, Multiple Kernel Learning, Adaptive Boosting, Systems Engineering, and Machine Learning

GW Unit:

School of Engineering and Applied Science

Degree:

Ph.D.

Advisor:

Mazzuchi, Thomas A and Sarkani, Shahram

Committee Member(s):

Murphree, E. Lile, Eveleigh, Timothy, and Holzer, Thomas

Resource Type:

Thesis or Dissertation