A survey of android malware detection with deep neural models
Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …
security research. Deep learning models have many advantages over traditional Machine …
A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
Dos and don'ts of machine learning in computer security
With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …
massive datasets, machine learning algorithms have led to major breakthroughs in many …
graph2vec: Learning distributed representations of graphs
A Narayanan, M Chandramohan, R Venkatesan… - ar** a systematic approach to generate benchmark android malware datasets and classification
Malware detection is one of the most important factors in the security of smartphones.
Academic researchers have extensively studied Android malware detection problems …
Academic researchers have extensively studied Android malware detection problems …
Amandroid: A precise and general inter-component data flow analysis framework for security vetting of android apps
We present a new approach to static analysis for security vetting of Android apps and a
general framework called Amandroid. Amandroid determines points-to information for all …
general framework called Amandroid. Amandroid determines points-to information for all …