Applying Deep Learning Techniques to the Analysis of Android APKs

Malware targeting mobile devices is a pervasive problem in modern life and as such tools to detect and classify malware are of great value. This paper seeks to demonstrate the effectiveness of Deep Learning Techniques, specifically Convolutional Neural Networks, in detecting and classifying malware targeting the Android operating system. Unlike many current detection techniques, which require the use of relatively rigid features to aid in detection, deep neural networks are capable of automatically learning flexible features which may be more resilient to obfuscation. We present a parsing for extracting sequences of API calls which can be used to describe a hypothetical execution of a given application. We then show how to use this sequence of API calls to successfully classify Android malware using a Convolutional Neural Network

MOONS: The New Multi-Object Spectrograph for the VLT

International audienceMOONS is the new Multi-Object Optical and Near-infrared Spectrograph currently under construction for the Very Large Telescope (VLT) at ESO. This remarkable instrument combines, for the first time, the collecting power of an 8-m telescope, 1000 fibres with individual robotic positioners, and both low- and high-resolution simultaneous spectral coverage across the 0.64–1.8 μm wavelength range. This facility will provide the astronomical community with a powerful, world-leading instrument able to serve a wide range of Galactic, extragalactic and cosmological studies. Construction is now proceeding full steam ahead and this overview article presents some of the science goals and the technical description of the MOONS instrument. More detailed information on the MOONS surveys is provided in the other dedicated articles in this Messenger issue