Discovering opportunities for adaptive human-machine interfaces for cyber-security

近年来，针对网络系统的网络攻击日益突出。网络图和攻击图是用于识别和纠正可能导致这些攻击的系统弱点的可视化工具。目前，这些可视化太复杂了，无法支持用户对网络战场环境的适当感知、理解和投影。为了在这些情况下提高态势感知能力，我们将与Uncharted Software Inc.一起开发一种自适应系统，用于确定网络系统和攻击图的适当详细程度视图。这种自适应系统将包括测量用户和系统的当前状态，以便以实时、特定于上下文的方式确定适当的信息聚合级别。虽然这一研究项目将直接应用于网络领域，但所开发的技术途径和方法也将广泛适用于其他形式的自适应可视化。

In recent years, cyber attacks against network systems have become increasingly prominent. Network maps and attack graphs are visualizations used to identify and correct system weaknesses that may lead to these attacks. Currently, these visualizations are too complex to support appropriate user perception, comprehension, and projection of the cyber battlespace situation. To improve situation awareness under these conditions, we will join Uncharted Software Inc. in developing an adaptive system for determining appropriate level of detail views for network systems and attack graphs. This adaptive system will involve measurement of both the user's and the system's current state in order to determine appropriate levels of information aggregation in a real-time, context-specific manner. While this research project will have direct applications in the cyber domain, the technical approach and methods developed will also be broadly applicable to other forms of adaptive visualizations.