The early detection of malicious communication with DNS traffic through the use of simple features

Anupama Mishra, B. B. Gupta, Ching Hsien Hsu, Kwok Tai Chui

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Today, in the era of advanced technology, Almost every one is connected with the internet and the number is increasing day by day as the number of Internet products increases. Today, we put our almost data in the hands of technology without thinking about the latest versions of bots which has become a significant issue and does the damage in many ways. The disruption done by botnets, in particular, is highly escalating. Additionally, encrypt communications are used or a non-standard protocol to evade detection. In our paper, we present a method for detecting malicious communication based on machine learning and Domain Name System traffic features. The results are very promising and verifying the proposed approach.

Original languageEnglish
Title of host publication2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
Pages291-293
Number of pages3
ISBN (Electronic)9781665436762
DOIs
Publication statusPublished - 2021
Event10th IEEE Global Conference on Consumer Electronics, GCCE 2021 - Kyoto, Japan
Duration: 12 Oct 202115 Oct 2021

Publication series

Name2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021

Conference

Conference10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Country/TerritoryJapan
CityKyoto
Period12/10/2115/10/21

Keywords

  • Bot
  • DNS
  • Machine Learning
  • Malware Detection

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