Many real-world networks contain structurally-equivalent nodes. These are defined as vertices that share the same set of neighboring nodes, making them interchangeable with a traditional graph layout approach. However, many real-world graphs also have properties associated with nodes, adding additional meaning to them. We present an approach for swapping locations of structurally-equivalent nodes in graph layout so that those with more similar properties have closer proximity to each other. This improves the usefulness of the visualization from an attribute perspective without negatively impacting the visualization from a structural perspective. We include an algorithm for finding these sets of nodes in linear time, as well as methodologies for ordering nodes based on their attribute similarity, which works for scalar, ordinal, multidimensional, and categorical data.

Enterprise level cyber security requires the deployment, operation, and monitoring of many sensors across geographically dispersed sites. Communicating with the sensors to gather data and control behavior is a challenging task when the number of sensors is rapidly growing. This paper describes the system requirements, design, and implementation of T3, the third generation of our transport software that performs this task. T3 relies on open source software and open Internet standards. Data is encoded in MIME format messages and transported via NNTP, which provides scalability. OpenSSL and public key cryptography are used to secure the data. Robustness and ease of development are increased by defining an internal cryptographic API, implemented by modules in C, Perl, and Python. We are currently using T3 in a production environment. It is freely available to download and use for other projects.