The number of malware is constantly on the rise. Though most new malware are
modifications of existing ones, their sheer number is quite overwhelming. In
this paper, we present a novel system to visualize and map millions of malware
to points in a 2-dimensional (2D) spatial grid. This enables visualizing
relationships within large malware datasets that can be used to develop triage
solutions to screen different malware rapidly and provide situational
awareness. Our approach links two visualizations within an interactive display.
Our first view is a spatial point-based visualization of similarity among the
samples based on a reduced dimensional projection of binary feature
representations of malware. Our second spatial grid-based view provides a
better insight into similarities and differences between selected malware
samples in terms of the binary-based visual representations they share. We also
provide a case study where the effect of packing on the malware data is
correlated with the complexity of the packing algorithm.

本文提出了一种可视化和映射数百万恶意软件到二维空间网格点的新系统，以提高大规模恶意软件数据集的快速筛选效率，并通过二维空间网格点的可视化视图来分析和比较不同恶意软件样本间的共性和差异。同时也针对 Packing 算法的复杂性和影响性进行了相关案例分析。