Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Tractable Group Detection on Large Link Data Sets
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Uncovering the dark Web: A case study of Jihad on the Web
Journal of the American Society for Information Science and Technology
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In this paper, we present preliminary results of analyzing data from the Dark Web collection using a dynamical systems approach for unsupervised anomaly detection. The goal is to provide a robust, focus-of-attention mechanism to identify emerging threats in time-dependent, unlabelled data sets. In our method, finite-time Lyapunov exponents are used to characterize the time evolution of both the directed network structure and the distribution of text attributes in the forum messages. We provide a description of the technique and a summary of the initial anomaly detection results. We conclude with a summary of results and a brief discussion of promising avenues for future research.