000			02208cam a2200361Ii 4500
001			9780429166877
008			180331t20142014fluad ob 001 0 eng d
020			_a9780429166877 _q(e-book : PDF)
020			_z9781466582088 _q(hardback)
024	7		_a10.1201/b15088 _2doi
035			_a(OCoLC)852899271
040			_aFlBoTFG _cFlBoTFG _erda
050		4	_aTK5105.59 _b.B474 2014
082	0	4	_a005.8 _bB575
100	1		_aBhattacharyya, Dhruba K., _eauthor. _915586
245	1	0	_aNetwork anomaly detection : _ba machine learning perspective / _cDhruba Kumar Bhattacharyya, Jugal Kumar Kalita.
264		1	_aBoca Raton : _bCRC Press, _c[2014]
264		4	_c©2014
300			_a1 online resource
336			_atext _2rdacontent
337			_acomputer _2rdamedia
338			_aonline resource _2rdacarrier
504			_aIncludes bibliographical references (pages 295-336) and index.
505	0		_a1. Introduction -- 2. Networks and anomalies -- 3. An overview of machine learning methods -- 4. Detecting anomalies in network data -- 5. Feature selection -- 6. Approaches to network anomaly detection -- 7. Evaluation methods -- 8. Tools and systems -- 9. Open issues, challenges and concluding remarks.
520			_aThis book discusses detection of anomalies in computer networks from a machine learning perspective. It introduces readers to how computer networks work and how they can be attacked by intruders in search of fame, fortune, or challenge. The reader will learn how one can look for patterns in captured network traffic data to look for anomalous patterns that may correspond to attempts at unauthorized intrusion. The reader will be given a technical and sophisticated description of such algorithms and their applications in the context of intrusion detection in networks-- _cProvided by publisher.
650		0	_aComputer networks _xSecurity measures. _93969
650		0	_aIntrusion detection systems (Computer security) _99445
650		0	_aMachine learning. _91831
700	1		_aKalita, Jugal Kumar, _eauthor. _915587
776	0	8	_iPrint version: _z9781466582088 _w(DLC) 2013014913
856	4	0	_uhttps://www.taylorfrancis.com/books/9781466582095 _zClick here to view.
942			_cEBK
999			_c71033 _d71033