000			02883nam a22003615i 4500
001			394028
003			ES-MaUEC
005			20230102123048.0
007			cr nn 008mamaa
008			220924s2022 sz | s |||| 0|eng d
020			_a9783031158933
024	7		_a10.1007/978-3-031-15893-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aOmar, Marwan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aMachine Learning for Cybersecurity _bInnovative Deep Learning Solutions _cby Marwan Omar
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (VIII, 48 páginas) _b32 ilustraciones, 22 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSpringerBriefs in Computer Science _x2191-5776
505	0		_a1. Application of Machine Learning (ML) to Address Cyber Security Threats -- 2. New Approach to Malware Detection Using Optimized Convolutional Neural Network -- 3. Malware Anomaly Detection Using Local Outlier Factor Technique. .
520			_aThis SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry. By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior. The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effective Advanced-level students in computer science studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the application of machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.
776	0	8	_iPrinted edition: _z9783031158926
776	0	8	_iPrinted edition: _z9783031158940
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-15893-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394028 _d394028