
Statistical Analysis of Network Traffic
Basic statistical tool
LAP Lambert Academic Publishing
Published on 14. November 2022
Book
Paperback/Softback
64 pages
978-620-5-51651-5 (ISBN)
Description
Network forensics helps in tracking down cyber fraudsters by assessing and tracing back network data. The use of various network traffic gathering tools is required. Network forensics is analyzing network traffic to detect intrusions and studying how the crime occurred, i.e., establishing a crime scene for investigation and replays. This study proposes a general network forensic process model and architecture. A secondary data set, KDD CUP of normal and anomalous traffic is used for analysis to simulate the entire process. The dataset is largely processed for feature selection and redundancy removal. The dataset was cleaned before being analyzed using the Support Vector Machine learning model to classify the traffic. The multiclass classification has been used to categorize various types of network attacks. The accuracy of the model is then evaluated using the obtained results.
More details
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 5 mm
Weight
113 gr
ISBN-13
978-620-5-51651-5 (9786205516515)
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Schweitzer Classification
Persons
Prabhjot Kaur is working at Uttaranchal University. She has keen interest in data analysis using ML.Dr. Amit Awasthi is working at University of Petroleum & Energy Studies having more than 15 years of professional experience. He has published 40 research papers in SCI Journals with a total Impact factor ~75, i10-index ~18 and citations ~1000.