Open AccessThreat Prediction using Honeypot and Machine Learning
Author(s) -
Prof. Suvarna Aranjo,
Sachin Maurya,
Chandrakant Thakur,
Melvin Raju
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.41016
Subject(s) - honeypot , computer science , intrusion detection system , computer security , intrusion , network security , cloud computing , artificial intelligence , operating system , geochemistry , geology
Honeypot is the ultimate tool in the kit of a security analyst, it helps us figure out what kind of attacks and malicious intent the attackers carry out and different strategies they use to take control of the network. Machine learning on the other hand can be used to make quicker decisions and narrow down different types of attacks faster and therefore predict the same attack that can occur on the actual network. The paper is divided into two sections one where we talk about the setup of the Honeypot on a Cloud service and then analyzing it and the other is where we are using Machine Learning algorithms to predict the type of the threat detected in the honeypots Keywords: Intrusion detection System (IDS), Network Intrusion Detection System(NIDS), High Interaction Honeypots(HIH)