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Proceedings Paper

Synchronization properties of cyber behaviors
Author(s): David C. Twardowski; George V. Cybenko
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Paper Abstract

In recent years the internet has facilitated an explosion of growth in social networks, allowing individuals to interact with one another in a variety of different contexts. Interactions between individuals in networks such as twitter and NASDAQ produce events which co-occur in time. If we make the assumption that events in networks are anonymized such that there is no mapping from the event back to the individual who produced it, we are left with a data stream consisting of spatially and temporally interleaved events with no attribution. We model this property of event co-occurrence in order to recreate this mapping by assuming a strong coupling between temporal co-occurrence and spatial variance an arbitrary individual's behavior. We present a few algorithms based on this model, which produce partitions of tracks, where each track is indicative of the behaviors from a single individual in the network. Results using the algorithms indicate that the models are valid showing a high degree of spatio-temporal consistency among behaviors in networks. This suggests the need for further exploration of new behavior models and algorithms centered around this property.

Paper Details

Date Published: 28 April 2010
PDF: 12 pages
Proc. SPIE 7709, Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 77090C (28 April 2010); doi: 10.1117/12.850220
Show Author Affiliations
David C. Twardowski, Dartmouth College (United States)
George V. Cybenko, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 7709:
Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II
William J. Tolone; John F. Buford; William Ribarsky; Gabriel Jakobson; John Erickson, Editor(s)

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