Network anomaly detection using big data analytics

By: Material type: TextTextPublication details: Lahore (unpublished) 2020Description: xiii, 91 p. ; 30 cm. +CD : illSubject(s): DDC classification:
  • SHA 006.7
Dissertation note: Thesis (MS)--Riphah International University, 2020
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Item type Current library Call number Copy number Status Date due Barcode
Thesis Thesis Lahore Raiwind Campus 006.7 SHA (Browse shelf(Opens below)) 1 NOT for LOAN 80095

Submitted in the partial fulfillment of the requirements for the degree of Master of Science in Computer Science

Includes bibliographical references.

Thesis supervisor: Mr. Imran Ahmad

Thesis (MS)--Riphah International University, 2020

English

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