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فهرست محتوای دیجیتالی
فهرست مطالب
فهرست نقدها
3 مرتبه مشاهده شده
Machine Intelligence and Big Data Analytics for Cybersecurity Applications
Maleh, Yassine
- ISBN:9783030570231
- Main Entry: Maleh, Yassine
- Title:Machine Intelligence and Big Data Analytics for Cybersecurity Applications/ Yassine Maleh • Mohammad Shojafar • Mamoun Alazab • Youssef Baddi.-
- Publisher:Cham, Switzerland: Springer Nature Switzerland AG, 2021.
- Added Entry:Shojafar, Mohammad
- Added Entry:Alazab, Mamoun
- Added Entry:Baddi, Youssef
فهرست محتوای دیجیتالی-
محتواي کتاب - مشاهده
فهرست مطالب- Preface
- Contents
- About the Editors
- Machine Intelligence and Big Data Analytics for Cybersecurity: Fundamentals and Challenges
- Network Intrusion Detection: Taxonomy and Machine Learning Applications
- Machine Learning and Deep Learning Models for Big Data Issues
- 1 Introduction
- 2 Importance of Predictive Analytics for Big Data Security
- 3 Predictive Models for Malware Detection
- 4 Predictive Models for Anomaly Detection
- 5 Predictive Models for Intrusion Detection
- 6 Predictive Models for Access Control
- 7 Predictive Models for Reliable Ingestion and Normalization
- 8 Conclusion
- References
- The Fundamentals and Potential for Cybersecurity of Big Data in the Modern World
- Toward a Knowledge-Based Model to Fight Against Cybercrime Within Big Data Environments: A Set of Key Questions to Introduce the Topic
- Machine Intelligence and Big Data Analytics for Cyber-Threat Detection and Analysis
- Improving Cyber-Threat Detection by Moving the Boundary Around the Normal Samples
- Bayesian Networks for Online Cybersecurity Threat Detection
- 1 Introduction
- 2 Related Works
- 3 Integrating Bayesian Networks in the DETECT Framework
- 3.1 Introduction to DETECT
- 3.2 The Architecture of the DETECT Framework
- 3.3 Bayesian Networks for Online Threat Detection in DETECT
- 3.4 Attack Trees
- 3.5 Bayesian Networks
- 3.6 Model-to-Model (M2M) Transformation Proposal: From Attack Trees to Bayesian Networks
- 3.7 Data Population of the Probability Tables
- 3.8 Transformation of Bayesian Networks to Machine-Readable XML Code
- 4 Case Study: Authentication Violation Scenario
- 5 Analysis
- 6 Discussion
- 7 Conclusion
- Appendix 1
- Appendix 2
- References
- Spam Emails Detection Based on Distributed Word Embedding with Deep Learning
- AndroShow: A Large Scale Investigation to Identify the Pattern of Obfuscated Android Malware
- IntAnti-Phish: An Intelligent Anti-Phishing Framework Using Backpropagation Neural Network
- Network Intrusion Detection for TCP/IP Packets with Machine Learning Techniques
- Developing a Blockchain-Based and Distributed Database-Oriented Multi-malware Detection Engine
- Ameliorated Face and Iris Recognition Using Deep Convolutional Networks
- Presentation Attack Detection Framework
- Classifying Common Vulnerabilities and Exposures Database Using Text Mining and Graph Theoretical Analysis
- Machine Intelligence and Big Data Analytics for Cybersecurity Applications
- A Novel Deep Learning Model to Secure Internet of Things in Healthcare
- Secure Data Sharing Framework Based on Supervised Machine Learning Detection System for Future SDN-Based Networks
- MSDN-GKM: Software Defined Networks Based Solution for Multicast Transmission with Group Key Management
- Machine Learning for CPS Security: Applications, Challenges and Recommendations
- 1 Introduction
- 2 Machine Learning Preliminaries
- 3 ML Phases: Modeling, Training and Deployment
- 4 Design of Learning-Based Anomaly Detectors: Practical Challenges
- 5 Experimental Evaluation on SWAT Testbed
- 6 Threat Model
- 7 Case Study-1: Invariant Generation Using Data-Centric Approach
- 8 Case Study-2: System Model Based Attack Detection and Isolation
- 9 Related Studies
- 10 Conclusions and Recommendations for Future Work
- References
- Applied Machine Learning to Vehicle Security
- Mobile Application Security Using Static and Dynamic Analysis
- Mobile and Cloud Computing Security
- Robust Cryptographical Applications for a Secure Wireless Network Protocol
- A Machine Learning Based Secure Change Management
- Intermediary Technical Interoperability Component TIC Connecting Heterogeneous Federation Systems