Predicting the Impact of Android Malicious Samples via Machine Learning
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2914311
Abstract: Recently, Android malicious samples threaten billions of mobile end users’ security or privacy. The community researchers have designed many methods to automatically and accurately identify Android malware samples. However, the rapid increase of Android malicious… read more here.
Keywords: android malware; malicious samples; android malicious; security ... See more keywords
Deep Generative Learning Models for Cloud Intrusion Detection Systems.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3163811
Abstract: Intrusion detection (ID) on the cloud environment has received paramount interest over the last few years. Among the latest approaches, machine learning-based ID methods allow us to discover unknown attacks. However, due to the lack… read more here.
Keywords: deep generative; malicious samples; cloud; intrusion detection ... See more keywords