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Machine learning for malware detection and classification: benefits, limitations and future directions

21 October 2019
11:00 am
San Francesco Complex - Piazza San Francesco 19 (Sacrestia)

To detect and classify malware is a very hard task rich of pitfalls and obstacles: for this reason, researchers have been looking for effective solutions that support these two processes. Machine learning is considered one of the main means for this aim and it has been widely investigated. Unfortunately, machine learning shows limitations that do not allow to consider it the definitive solution; however, machine learning can produce benefits if it’s employed properly. This seminar will provide an analysis of the most prominent findings offered by the literature about machine and deep learning, aiming at shedding light on when and how machine learning can be applied for detecting and recognizing malware.

relatore: 
Corrado Aaron Visaggio - Università degli Studi del Sannio, Benevento
Units: 
SYSMA