DDoS attack detection mechanism in the application layer using user features

Silvia Bravo, David Mauricio

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

8 Scopus citations

Abstract

DDoS attacks are one of the most damaging computer aggressions of recent times. Attackers send large number of requests to saturate a victim machine and it stops providing its services to legitimate users. In general attacks are directed to the network layer and the application layer, the latter has been increasing due mainly to its easy execution and difficult detection. The present work proposes a low cost detection approach that uses the characteristics of the Web User for the detection of attacks. To do this, the features are extracted in real time using functions designed in PHP and JavaScript. They are evaluated by an order 1 classifier to differentiate a real user from a DDoS attack. A real user is identified by making requests interacting with the computer system, while DDoS attacks are requests sent by robots to overload the system with indiscriminate requests. The tests were executed on a computer system using requests from real users and attacks using the LOIC, OWASP and GoldenEye tools. The results show that the proposed method has a detection efficiency of 100%, and that the characteristics of the web user allow to differentiate between a real user and a robot.

Original languageEnglish
Title of host publication2018 International Conference on Information and Computer Technologies, ICICT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages97-100
Number of pages4
ISBN (Electronic)9781538653845
DOIs
StatePublished - 9 May 2018
Event2018 International Conference on Information and Computer Technologies, ICICT 2018 - DeKalb, United States
Duration: 23 Mar 201825 Mar 2018

Publication series

Name2018 International Conference on Information and Computer Technologies, ICICT 2018

Conference

Conference2018 International Conference on Information and Computer Technologies, ICICT 2018
CountryUnited States
CityDeKalb
Period23/03/1825/03/18

Bibliographical note

Funding Information:
ACKNOWLEDGMENT The authors thank the National Council of Science, Technology and Technological Innovation (CONCYTEC) - Peru and Technical University of Cotopaxi for the partial funding of this work and Professor Angel H. Moreno for their contributions to this work.

Publisher Copyright:
© 2018 IEEE.

Keywords

  • DDoS
  • denial of service
  • dynamism user
  • features user

Fingerprint Dive into the research topics of 'DDoS attack detection mechanism in the application layer using user features'. Together they form a unique fingerprint.

Cite this