000			04221nam a22006015i 4500
001			978-3-031-34969-0
003			DE-He213
005			20251030110839.0
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020			_a9783031349690 _9978-3-031-34969-0
024	7		_a10.1007/978-3-031-34969-0 _2doi
050		4	_aTK5101-5105.9
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
072		7	_aTJK _2thema
245	1	0	_aCyber Malware _h[electronic resource] : _bOffensive and Defensive Systems / _cedited by Iman Almomani, Leandros A. Maglaras, Mohamed Amine Ferrag, Nick Ayres.
250			_a1st ed. 2024.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2024.
300			_aXXXVI, 280 p. 1 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSecurity Informatics and Law Enforcement, _x2523-8515
505	0		_aPart 1. Android Malware Analysis -- Chapter 1. A Deep Vision-based Multi-Class Classification System of Android Malware Apps -- Chapter 2. Android Malware detection based on network analysis and federated learning -- Chapter 3. ASParseV3: Auto Static Parser & Customizable Visualizer -- Part 2. Network Malware Analysis -- Chapter 4. Fast Flux Service Networks: Architecture, Characteristics and Detection Mechanisms -- Chapter 5. Efficient Graph-based Malware Detection using Minimized Kernel and SVM -- Chapter. 6 Deep Learning for Windows Malware Analysis -- Part 3. IoT Malware Analysis -- Chapter 7. Malware analysis for IoT and Smart AI-based Applications -- Chapter 8. A Multi-Class Classification Approach for IoT Intrusion Detection Based on Feature Selection and Oversampling -- Chapter 9. Malware Mitigation in Cloud Computing Architecture.
520			_aThis book provides the foundational aspects of malware attack vectors and appropriate defense mechanisms against malware. The book equips readers with the necessary knowledge and techniques to successfully lower the risk against emergent malware attacks. Topics cover protections against malware using machine learning algorithms, Blockchain and AI technologies, smart AI-based applications, automated detection-based AI tools, forensics tools, and much more. The authors discuss theoretical, technical, and practical issues related to cyber malware attacks and defense, making it ideal reading material for students, researchers, and developers. Presents theoretical, technical, and practical knowledge on defending against malware attacks; Covers malware applications using machine learning algorithms, Blockchain and AI, forensics tools, and much more; Includes perspectives from experts in cybersecurity at different institutions, including academia, research centers, and companies.
650		0	_aTelecommunication.
650		0	_aComputer crimes. _967515
650		0	_aData protection.
650		0	_aSecurity systems. _966821
650	1	4	_aCommunications Engineering, Networks.
650	2	4	_aCybercrime. _967516
650	2	4	_aData and Information Security. _966492
650	2	4	_aSecurity Science and Technology. _966822
700	1		_aAlmomani, Iman. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _967517
700	1		_aMaglaras, Leandros A. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _967518
700	1		_aFerrag, Mohamed Amine. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _967519
700	1		_aAyres, Nick. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _967520
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783031349683
776	0	8	_iPrinted edition: _z9783031349706
776	0	8	_iPrinted edition: _z9783031349713
830		0	_aSecurity Informatics and Law Enforcement, _x2523-8515 _967521
856	4	0	_uhttps://doi.org/10.1007/978-3-031-34969-0
912			_aZDB-2-ENG
912			_aZDB-2-SXE
999			_c56626 _d56626