Feature Selection Technique Impact for Internet Traffic Classification Using Naïve Bayesian
Satish Chadokar
, Ashish Kumbhare
Internet traffic defines as the density of data or information presented on the Internet or in another language we can say it’s a flow of data on the internet. Internet traffic classification has power to solve many network difficulties and manage different type of network problems. There are some basic functions provided to government, Internet service providers (ISPs) and network administrator through Internet traffic classification. It can be used for intrusion detection system by finding patterns of denial of service (Dos) and other attacks. It can be used for intrusion detection system by finding patterns of denial of service (Dos) and other attacks. It can help to ISPs to monitor network traffic flow and troubleshoot the faults and other problems, it can also be used in “lawful inspection” of the payload of a packet by government to obtain users information.
"Feature Selection Technique Impact for Internet Traffic Classification Using Naïve Bayesian", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 7, page no.196 - 204, July-2017, Available :https://ijsdr.org/papers/IJSDR1707029.pdf
Volume 2
Issue 7,
July-2017
Pages : 196 - 204
Paper Reg. ID: IJSDR_170629
Published Paper Id: IJSDR1707029
Downloads: 000347210
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
