My thesis for Master’s in Computer Sciences. As the proliferation and adoption of smart devices increase, there is an unprecedented amount of data being released into the network every second. Computer networks are the carriers for the movement of this ever generating amounts of data, but are dumb in a way that they do not distinguish between suspicious data traffic and valid data traffic.
However secure a computer network be, suspicious network traffic activities are bound to happen. These suspicious traffic activities have to be detected, analyzed and stopped before it compromises the entire network and leaves the information and data security of an organization in mayhem. There are several tools and visualizations for cybersecurity awareness at the disposal of security analysts and network operators. These helpful tools often lack in having the property of being intuitive and cognitive. Using the amalgamation of Mixed Reality, localization and mapping techniques, this thesis researches and implements a way of augmenting network traffic information right on the top of every computer system. The availability of network data rightly where it needs to be tagged and right when it is needed will help security analysts to better understand network activities and also locate the infected system and take quick actions if need be. In this thesis, we design and build a prototype that demonstrates how Mixed Reality provides better situation awareness to cyber operators managing a physical space.