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The authors apply MDLcompress, a grammar inference engine, to Network Intrusion Detection (NID). They specifically target HTTP payload analysis of Deep Packet Inspection (DPI) utilizing the DARPA 1999 data sets for their normal network traffic base and create modern attack traffic using Nessus. Their approach accurately detected over 98% of the attacks compared with literature reports of approximately 95% accuracy rate on HTTP attacks. As the digital universe becomes more and more connected, information assurance, providing legitimate users access to data and services while blocking unauthorized use, is an ever-increasing challenge.
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