@techreport{TD:7NZS8K,
	att_abstract={{We formulate and address the problem of discovering dynamic malicious  regions on the Internet. We model this problem as one of adaptively  pruning a known decision tree, but with  additional challenges: (1) severe  space requirements, since the underlying decision tree has over 4 billion  leaves, and (2) a changing target function, since malicious activity on  the Internet is dynamic. We present a novel algorithm that addresses this  problem, by putting together a number of different "experts" algorithms  and online paging algorithms. We prove guarantees on our algorithm?s  performance as a function of the best possible pruning of a similar size,  and our experiments show that our algorithmachieves high accuracy on large  real-world data sets, with significant improvements over existing  approaches. }},
	att_authors={sv1623, ss2864, os1872},
	att_categories={},
	att_copyright={{NIPS Foundation}},
	att_copyright_notice={{}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:7NZS8K},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:7NZS8K_DS1_2010-08-18T16:03:18.101Z.pdf},
	author={Shobha Venkataraman and Subhabrata Sen and Oliver Spatscheck and Avrim Blum and Dawn Song},
	institution={{Neural Information Processing Systems (NIPS) 2009}},
	month={December},
	title={{Tracking Dynamic Sources of Malicious Activity at  Internet-Scale}},
	year=2009,
}