Description
Malware analysis increasingly relies on machine learning classification. In this mission-critical domain, analysts require deeper insights that justify the classification results and help them understand how the results were reached. In the project EMA (NextGenerationEU/Recovery and Resilience Plan project No. 09I05-03-V02-00064), we focus on applications of eXplainable (XAI) methods that enable such insights. We develop suitable datasets, select the most promising XAI methods, and also focus on the presentation of the justifications/explanations to the user.
| Pracovisko fakulty (katedra)/ Department of Faculty | KAI |
|---|---|
| Tlač postru/ Print poster | Budem požadovať tlač /I hereby required to print the poster in faculty |
Authors
Martin Homola
Štefan Balogh
(FEI STU)
Ján Kľuka
(FMFI UK)
Daniela Chudá
(KInIT)
Iveta Bečková
Jaroslav Kopčan
(KInIT)
