04221nam a22006015i 4500 978-3-031-34969-0 DE-He213 20251030110839.0 cr nn 008mamaa 231108s2024 sz | s |||| 0|eng d 9783031349690 978-3-031-34969-0 10.1007/978-3-031-34969-0 doi TK5101-5105.9 TJK bicssc TEC041000 bisacsh TJK thema Cyber Malware [electronic resource] : Offensive and Defensive Systems / edited by Iman Almomani, Leandros A. Maglaras, Mohamed Amine Ferrag, Nick Ayres. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XXXVI, 280 p. 1 illus. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Security Informatics and Law Enforcement, 2523-8515 Part 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. This 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. Telecommunication. Computer crimes. 67515 Data protection. Security systems. 66821 Communications Engineering, Networks. Cybercrime. 67516 Data and Information Security. 66492 Security Science and Technology. 66822 Almomani, Iman. editor. edt http://id.loc.gov/vocabulary/relators/edt 67517 Maglaras, Leandros A. editor. edt http://id.loc.gov/vocabulary/relators/edt 67518 Ferrag, Mohamed Amine. editor. edt http://id.loc.gov/vocabulary/relators/edt 67519 Ayres, Nick. editor. edt http://id.loc.gov/vocabulary/relators/edt 67520 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031349683 Printed edition: 9783031349706 Printed edition: 9783031349713 Security Informatics and Law Enforcement, 2523-8515 67521 https://doi.org/10.1007/978-3-031-34969-0 ZDB-2-ENG ZDB-2-SXE 56626 56626