doctoral thesis
Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:651873

University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electronics, Microelectronics, Computer and Intelligent Systems

Cite this document

Knežević, K. (2023). Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:651873

Knežević, Karlo. "Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:651873

Knežević, Karlo. "Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:651873

Knežević, K. (2023). 'Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 19 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:651873

Knežević K. Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 19] Available at: https://urn.nsk.hr/urn:nbn:hr:168:651873

K. Knežević, "Machine learning and evolutionary computation in design and analysis of symmetric key cryptographic algorithms", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:651873

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