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Martin Macák
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- affiliation: Masaryk University, Brno, Czech Republic
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2020 – today
- 2023
- [j5]Lukas Daubner
, Martin Macák, Raimundas Matulevicius, Barbora Buhnova, Sofija Maksovic
Addressing insider attacks via forensic-ready risk management. J. Inf. Secur. Appl. 73: 103433 (2023) - [j4]Pavla Sabacká, Jirí Maxa
Comparative Analysis of Supersonic Flow in Atmospheric and Low Pressure in the Region of Shock Waves Creation for Electron Microscopy. Sensors 23(24): 9765 (2023) - [c18]Martin Macák, Tomás Rebok, Matus Stovcik, Mouzhi Ge, Bruno Rossi, Barbora Buhnova:
CopAS: A Big Data Forensic Analytics System. IoTBDS 2023: 150-161 - [c17]Martin Macák, Radek Oslejsek, Barbora Buhnova:
Detecting Masquerading Traitors from Process Visualization of Computer Usage. TrustCom 2023: 1935-1940 - 2022
- [j3]Martin Macák
Process mining usage in cybersecurity and software reliability analysis: A systematic literature review. Array 13: 100120 (2022) - [c16]Martin Macák, Radek Vaclavek, Dasa Kusniráková, Raimundas Matulevicius, Barbora Buhnova:
Scenarios for Process-Aware Insider Attack Detection in Manufacturing. ARES 2022: 89:1-89:10 - [c15]Stanislav Chren
Evaluating Code Improvements in Software Quality Course Projects. EASE 2022: 160-169 - [c14]Martin Macák, Radek Oslejsek, Barbora Buhnova:
Applying Process Discovery to Cybersecurity Training: An Experience Report. EuroS&P Workshops 2022: 394-402 - [c13]Martin Macák, Radek Oslejsek, Barbora Buhnova:
Process Mining Analysis of Puzzle-Based Cybersecurity Training. ITiCSE (1) 2022: 449-455 - [i3]Martin Macák, Radek Oslejsek, Barbora Buhnova:
Process Mining Analysis of Puzzle-Based Cybersecurity Training. CoRR abs/2203.15425 (2022) - [i2]Lukas Daubner
Forensic-Ready Risk Management Concepts. CoRR abs/2210.06840 (2022) - [i1]Martin Macák, Matus Stovcik, Tomás Rebok, Mouzhi Ge, Bruno Rossi, Barbora Buhnova:
CopAS: A Big Data Forensic Analytics System. CoRR abs/2212.04843 (2022) - 2021
- [j2]Martin Macák
Using process mining for Git log analysis of projects in a software development course. Educ. Inf. Technol. 26(5): 5939-5969 (2021) - [c12]Martin Macák
Game Achievement Analysis: Process Mining Approach. ADMA 2021: 68-82 - [c11]Martin Macák
Cybersecurity Analysis via Process Mining: A Systematic Literature Review. ADMA 2021: 393-407 - [c10]Martin Macák, Stefan Bojnak, Barbora Buhnova:
Identification of Unintentional Perpetrator Attack Vectors using Simulation Game: A Case Study. FedCSIS 2021: 349-356 - 2020
- [j1]Martin Macák
A Cross-Domain Comparative Study of Big Data Architectures. Int. J. Cooperative Inf. Syst. 29(4): 2030001:1-2030001:27 (2020) - [c9]Lukas Daubner
Towards verifiable evidence generation in forensic-ready systems. IEEE BigData 2020: 2264-2269 - [c8]Martin Macák, Matus Stovcik, Barbora Buhnova, Michal Merjavy:
How well a multi-model database performs against its single-model variants: Benchmarking OrientDB with Neo4j and MongoDB. FedCSIS 2020: 463-470 - [c7]Martin Macák, Agata Kruzikova, Lukas Daubner
Simulation Games Platform for Unintentional Perpetrator Attack Vector Identification. ICSE (Workshops) 2020: 222-229 - [c6]Martin Macák, Matus Stovcik, Barbora Buhnova:
The Suitability of Graph Databases for Big Data Analysis: A Benchmark. IoTBDS 2020: 213-220 - [c5]Martin Macák, Hind Bangui, Barbora Buhnova, András J. Molnár, Csaba István Sidló:
Big Data Processing Tools Navigation Diagram. IoTBDS 2020: 304-312 - [c4]Lukas Daubner
Verification of forensic readiness in software development: a roadmap. SAC 2020: 1658-1661 - [c3]Martin Macák, Ivan Vanat, Michal Merjavy, Tomás Jevocin, Barbora Buhnova:
Towards Process Mining Utilization in Insider Threat Detection from Audit Logs. SNAMS 2020: 1-6
2010 – 2019
- 2019
- [c2]Jakub Lipcak, Martin Macák, Bruno Rossi
Big Data Platform for Smart Grids Power Consumption Anomaly Detection. FedCSIS 2019: 771-780 - [c1]Stanislav Chren
Mistakes in UML diagrams: analysis of student projects in a software engineering course. ICSE (SEET) 2019: 100-109
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last updated on 2024-08-05 20:18 CEST by the dblp team
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