10 research outputs found
Android Malware Clustering through Malicious Payload Mining
Clustering has been well studied for desktop malware analysis as an effective
triage method. Conventional similarity-based clustering techniques, however,
cannot be immediately applied to Android malware analysis due to the excessive
use of third-party libraries in Android application development and the
widespread use of repackaging in malware development. We design and implement
an Android malware clustering system through iterative mining of malicious
payload and checking whether malware samples share the same version of
malicious payload. Our system utilizes a hierarchical clustering technique and
an efficient bit-vector format to represent Android apps. Experimental results
demonstrate that our clustering approach achieves precision of 0.90 and recall
of 0.75 for Android Genome malware dataset, and average precision of 0.98 and
recall of 0.96 with respect to manually verified ground-truth.Comment: Proceedings of the 20th International Symposium on Research in
Attacks, Intrusions and Defenses (RAID 2017
Stroke 1: definition, burden, risk factors and diagnosis
The field of stroke has benefitted from many advances in recent decades, in particular, improved imaging techniques. This, coupled with better knowledge of brain function among professionals and greater awareness of stroke signs and symptoms among the general public, leads to the earlier identification, diagnosis, and treatment – which are key as stroke is a medical emergency. However, more needs to be done to reduce the personal and societal burden of stroke. This article – the first of a five-part series on stroke – discusses definitions, epidemiology, risk factors and diagnosis to help nurses gain an in-depth understanding of this complex condition