Artificial Intelligence and Data Mining Approaches in Security Frameworks. Группа авторов

Чтение книги онлайн.

СКАЧАТЬ Framework of Multi-Tenancy 7.3 Privacy and Security in Multi-Tenant Base System Using AI 7.4 Related Work 7.5 Conclusion References

      12  8 Biometric Facial Detection and Recognition Based on ILPB and SVM 8.1 Introduction 8.2 The Proposed Methodolgy 8.3 Experimental Results 8.4 Conclusion References

      13  9 Intelligent Robot for Automatic Detection of Defects in Pre-Stressed Multi-Strand Wires and Medical Gas Pipe Line System Using ANN and IoT 9.1 Introduction 9.2 Inspection System for Defect Detection 9.3 Defect Recognition Methodology 9.4 Health Care MGPS Inspection 9.5 Conclusion References

      14  10 Fuzzy Approach for Designing Security Framework 10.1 Introduction 10.2 Fuzzy Set 10.3 Planning for a Rule-Based Expert System for Cyber Security 10.4 Digital Security 10.5 Improvement of Cyber Security System (Advance) 10.6 Conclusions References

      15  11 Threat Analysis Using Data Mining Technique 11.1 Introduction 11.2 Related Work 11.3 Data Mining Methods in Favor of Cyber-Attack Detection 11.4 Process of Cyber-Attack Detection Based on Data Mining 11.5 Conclusion References

      16  12 Intrusion Detection Using Data Mining 12.1 Introduction 12.2 Essential Concept 12.3 Detection Program 12.4 Decision Tree 12.5 Data Mining Model for Detecting the Attacks 12.6 Conclusion References

      17  13 A Maize Crop Yield Optimization and Healthcare Monitoring Framework Using Firefly Algorithm through IoT 13.1 Introduction 13.2 Literature Survey 13.3 Experimental Framework 13.4 Healthcare Monitoring 13.5 Results and Discussion 13.6 Conclusion References

      18  14 Vision-Based Gesture Recognition: A Critical Review 14.1 Introduction 14.2 Issues in Vision-Based Gesture Recognition 14.3 Step-by-Step Process in Vision-Based 14.4 Classification 14.5 Literature Review 14.6 Conclusion References

      19  15 SPAM Filtering Using Artificial Intelligence 15.1 Introduction 15.2 Architecture of Email Servers and Email Processing Stages 15.3 Execution Evaluation Measures 15.4 Classification - Machine Learning Technique for Email Spam 15.5 Conclusion References

      20  About the Editors

      21  Index

      22  End User License Agreement

      List of Illustrations

      1 Chapter 1Figure 1.1 Network infrastructure [4].Figure 1.2 System architecture [11].

      2 Chapter СКАЧАТЬ