ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Monitor and increase security in a private cloud using artificial intelligence

Dewit, Maxime
(2021)

Files

DEWIT_99031700_2021.pdf
  • Closed access
  • Adobe PDF
  • 1.56 MB
Download not available

Details

Supervisors
Legay, Axel ; Detienne, Nicolas
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] en cybersécurité, à finalité spécialisée: conception et analyse de systèmes
Abstract
Firewalls are used to regulate network traffic by allowing or rejecting incoming and outgoing packets. They are nowadays the core of network security. However, these firewalls can quickly expand into a long list of rules that becomes difficult to manage. As it will be shown in this thesis, there are several types of anomaly that can appear within the list of rules. These anomalies lead to complex rules with hard-to-notice errors that may result in ineffective firewalls. The use of artificial intelligence such as clustering can provide assistance for network administrators to detect and reduce the number of anomalies. In addition to classic anomalies such as shadow anomalies and generalization anomalies, the use of artificial intelligence can also detect decaying rules which may lead to security risks. The purpose is to provide evidence to network administrators in order to detect and mitigate those security risks.

Citations

  • APA

Dewit, M. (2021). Monitor and increase security in a private cloud using artificial intelligence. https://dial-mem.test.bib.ucl.ac.be/handle/2078.2/24034