Search Results for author: Miroslav Bures

Found 5 papers, 0 papers with code

Overview of Test Coverage Criteria for Test Case Generation from Finite State Machines Modelled as Directed Graphs

no code implementations17 Mar 2022 Vaclav Rechtberger, Miroslav Bures, Bestoun S. Ahmed

Test Coverage criteria are an essential concept for test engineers when generating the test cases from a System Under Test model.

Prioritized Variable-length Test Cases Generation for Finite State Machines

no code implementations17 Mar 2022 Vaclav Rechtberger, Miroslav Bures, Bestoun S. Ahmed, Youcef Belkhier, Jiri Nema, Hynek Schvach

Depending on the application of the FSM, the strategy and evaluation presented in this paper are applicable both in testing functional and non-functional software requirements.

Utilising Flow Aggregation to Classify Benign Imitating Attacks

no code implementations6 Mar 2021 Hanan Hindy, Robert Atkinson, Christos Tachtatzis, Ethan Bayne, Miroslav Bures, Xavier Bellekens

The features used in these studies are broadly similar and have demonstrated their effectiveness in situations where cyber-attacks do not imitate benign behaviour.

Leveraging Siamese Networks for One-Shot Intrusion Detection Model

no code implementations27 Jun 2020 Hanan Hindy, Christos Tachtatzis, Robert Atkinson, David Brosset, Miroslav Bures, Ivan Andonovic, Craig Michie, Xavier Bellekens

Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class.

Anomaly Detection Intrusion Detection +1

A Hybrid Q-Learning Sine-Cosine-based Strategy for Addressing the Combinatorial Test Suite Minimization Problem

no code implementations27 Apr 2018 Kamal Z. Zamli, Fakhrud Din, Bestoun S. Ahmed, Miroslav Bures

Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level.

Q-Learning

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