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Bc. Glenn Fischer

Bachelor's thesis

Reinforcement Learning for Efficient Attack Agents Training

Reinforcement Learning for Efficient Attack Agents Training
Abstract:
Umelá inteligencia otvára nové možnosti skúmania a odhaľovania nových útočných stratégií bez skutočného ohrozenia siete. Jedným z najperspektívnejších prístupov k tvorbe útočných entít prostredníctvom strojového učenia je reinforcement learning, tj. spätnoväzobné učenie. Tento prístup umožňuje vytvárať obranné postupy proti útokom, ktoré sa v realite neodohrali, ale ich realizácia je možná. Spätnoväzobné …more
Abstract:
By using AI within a simulation, we create a means of discovering new attack strategies without the dangers of actual network attacks. One of the most promising machine learning approaches to creating attack agents is reinforcement learning. Using this approach, it is possible to create defences against attacks that have not taken place in real systems. While reinforcement learning agents may be able …more
 

Keywords

reinforcement learning cyber-attack simulator topology generation Q-learning SARSA
 
Language used: English
Date on which the thesis was submitted / produced: 19. 5. 2022
Identifier: https://is.muni.cz/th/ma5ux/

Thesis defence

  • Date of defence: 28. 6. 2022
  • Supervisor: RNDr. Tomáš Jirsík, Ph.D.
  • Reader: RNDr. Martin Drašar, Ph.D.

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Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatiky
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Masaryk University

Faculty of Informatics

Bachelor programme / field:
Informatics / Informatics

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