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001			288027
003			MX-SnUAN
005			20160429154610.0
007			cr nn 008mamaa
008			150903s2013 xxu| o |||| 0|eng d
020			_a9781461455233 _99781461455233
024	7		_a10.1007/9781461455233 _2doi
035			_avtls000341652
039		9	_a201509030333 _bVLOAD _c201405050232 _dVLOAD _y201402061104 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA76.9.A25
100	1		_aYin, Heng. _eautor _9317558
245	1	0	_aAutomatic Malware Analysis : _bAn Emulator Based Approach / _cby Heng Yin, Dawn Song.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aIx, 73 páginas 15 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSpringerBriefs in Computer Science, _x2191-5768
500			_aSpringer eBooks
505	0		_aIntroduction -- Dynamic Binary Analysis Platform -- Hidden Code Extraction -- Privacy-breaching Behavior Analysis -- Hooking Behavior Analysis -- Analysis of Trigger Conditions and Hidden Behaviors -- Concluding Remarks.
520			_aMalicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems.  Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aSong, Dawn. _eautor _9304796
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781461455226
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-5523-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c288027 _d288027