Chakrabarty, Dr. AmitabhaBinte istiaq, FaizaE Mohammad, RubaiyatTasnia, MoriomHassan, Kazi MoinulTabassum, Tanjim2024-06-062024-06-0620222022-09ID: 18301227ID: 18301103ID: 18301058ID: 18301290ID: 20101629http://hdl.handle.net/10361/23221Cataloged from PDF version of thesis.Includes bibliographical references (pages 46-50).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022."Botnet” refers to a network of compromised machines that the bot master remotely controls to prosecute innumerable malicious activities through a CC server and mis cellaneous slave machines. It is possible to categorize botnets as centralized (CC) or decentralized (P2P). According to their distributed functionality,recently P2P botnets is the most significant risks to network security . In this paper, we sys tematically analyze and compare some very recent peer-to-peer botnet algorithms and methods such as Honeypots, AutoBotCatcher, SDN, and PeerGrep to ascertain the most appropriate one for real-world applications. To perform this comparison, we examine AutuBotCatcher, an algorithm that utilizes the community detection method, Honeypot system, where we focus on the Nepethesis honeypot method. Additionally, the PeerGrep system integrates the PeerGrep algorithm, CART algo rithm, and P2P traffic in SDN to automate and flexibly manage flow entries through machine learning.50 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.BotnetPeer to peerHoneypotsAutoBotCatcherSDNPeerGrepComputer security.Computer networks--Security measures.Thesis