Open AccessErdos – Renyi Random Graph and Machine Learning Based Botnet Detection
Author(s) -
K. Akilandeswari,
Mr. L. Baranivel*,
Mr. G. Anwar Basha
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.e1996.039520
Subject(s) - botnet , random graph , computer science , theoretical computer science , graph , graph theory , artificial intelligence , combinatorics , mathematics , world wide web , the internet
Basically large networks are prone to attacks by bots and lead to complexity. When the complexity occurs then it is difficult to overcome the vulnerability in the network connections. In such a case, the complex network could be dealt with the help of probability theory and graph theory concepts like Erdos – Renyi random graphs, Scale free graph, highly connected graph sequences and so on. In this paper, Botnet detection using Erdos – Renyi random graphs whose patterns are recognized as the number of connections that the vertices and edges made in the network is proposed. This paper also presents the botnet detection concepts based on machine learning.