Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. Perhaps the most cited...
What is Snort?
Snort® is an open source network intrusion prevention and detection system utilizing a rule-driven language, which combines the benefits of signature, protocol and anomaly based inspection methods. With millions of downloads to date, Snort is the most widely deployed intrusion detection and prevention technology worldwide and has become the de facto standard for the industry.
E. Raad, R. Chbeir, and A. Dipanda. Proceedings of the 2010 13th International Conference on Network-Based Information Systems, page 297--304. Washington, DC, USA, IEEE Computer Society, (2010)
A. Mislove, B. Viswanath, K. Gummadi, and P. Druschel. Proceedings of the Third ACM International Conference on Web Search and Data Mining, page 251--260. New York, NY, USA, ACM, (2010)
J. Yang, and J. Leskovec. Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, page 587--596. New York, NY, USA, ACM, (2013)
M. Somaiya, C. Jermaine, and S. Ranka. Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, page 909--918. ACM, (2010)
A. McCallum, A. Corrada-Emmanuel, and X. Wang. Proceedings of the 19th international joint conference on Artificial intelligence, page 786--791. Citeseer, (2005)
F. Mitzlaff, D. Benz, G. Stumme, and A. Hotho. HT '10: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia, page 265--270. New York, NY, USA, ACM, (2010)