Next-generation systems and secure computing

Next-Generation Systems and Secure Computing is essential for anyone looking to stay ahead in the rapidly evolving landscape of technology. It offers crucial insights into advanced computing models and their security implications, equipping readers with the knowledge needed to navigate the complex c...

Full description

Saved in:
Bibliographic Details
Other Authors Barman, Subhabrata (Editor), Koley, Santanu (Editor), Joardar, Subhankar (Editor)
Format Electronic eBook
LanguageEnglish
Published Hoboken, NJ : Beverly, MA : John Wiley & Sons, Inc. ; Scrivener Publishing LLC, 2025.
Subjects
Computer security.
Cloud computing > Security measures.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781394228522
9781394228546
9781394228478
9781394228263
Physical Description1 online zdroj

Cover

Table of Contents:
  • Cover
  • Series Page
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • Chapter 1 Yet Another Move Towards Securing Video Using Sudoku-Fernet
  • 1.1 Introduction
  • 1.2 Literature Survey
  • 1.3 Proposed Methodology
  • 1.3.1 Proposed Algorithm for Generating Sudoku-Fernet Cipher Key
  • 1.3.2 Encryption Process
  • 1.4 Result Analysis
  • 1.5 Computational Complexity
  • 1.6 Conclusions
  • References
  • Chapter 2 Watermarking: Characteristics, Methods, and Evaluation
  • 2.1 Introduction
  • 2.1.1 Chapter Organization
  • 2.2 Watermark Definition
  • 2.2.1 Digital Watermarking Applications
  • 2.2.1.1 Copyright Protection
  • 2.2.1.2 Fingerprinting
  • 2.2.1.3 Broadcast Monitoring
  • 2.2.1.4 Tamper Proofing
  • 2.3 Properties of Watermarking
  • 2.4 Categorization of Watermarking
  • 2.4.1 Related Works on Watermarking
  • 2.5 Attacks on Watermarking
  • 2.5.1 Enhancement Technique Attacks
  • 2.5.2 Noise Addition Attacks
  • 2.5.3 Geometric Transformation Attacks
  • 2.5.4 Compression Attack
  • 2.5.5 Combinational Attacks
  • 2.6 Chapter Summary
  • References
  • Chapter 3 A Comprehensive Study on Deep Learning and Artificial Intelligence for Malware Analysis
  • 3.1 Introduction
  • 3.2 The Evolving Landscape of Malware Threats
  • 3.2.1 Polymorphic and Metamorphic Malware
  • 3.2.2 Advanced Persistent Threats (APTs)
  • 3.2.3 Fileless and Memory-Based Attacks
  • 3.2.4 Ransomware and Cryptojacking
  • 3.2.5 Supply Chain Attacks
  • 3.2.6 IoT and Mobile Malware
  • 3.2.7 Zero-Day Exploits
  • 3.3 The Role of Deep Learning and AI in Enhancing Cybersecurity
  • 3.3.1 Advanced Threat Detection
  • 3.3.2 Real-Time Response and Mitigation
  • 3.3.3 Behavioral Analysis
  • 3.3.4 Anomaly Detection
  • 3.3.5 Predictive Security
  • 3.3.6 Reducing False Positives
  • 3.3.7 Continuous Learning and Improvement
  • 3.4 Deep Learning Models for Malware Analysis
  • 3.4.1 Convolutional Neural Networks (CNNs)
  • 3.4.2 Recurrent Neural Networks (RNNs) for Malware Analysis
  • 3.4.3 Long Short-Term Memory Networks (LSTMs)
  • 3.4.4 Generative Adversarial Networks (GANs)
  • 3.4.5 Radial Basis Function Networks (RBFNs)
  • 3.4.6 Deep Belief Networks (DBNs)
  • 3.5 AI Techniques in Malware Analysis
  • 3.5.1 Unsupervised Learning
  • 3.5.2 Supervised Learning
  • 3.5.3 Deep Learning
  • 3.6 Challenges and Limitations in Malware Family Classification
  • 3.6.1 Lack of Labeled Data
  • 3.6.2 Imbalanced Data
  • 3.6.3 Feature Engineering
  • 3.6.4 Adversarial Attacks
  • 3.6.5 Generalization to New Variants
  • 3.6.6 Real-Time Analysis
  • 3.6.7 Interpretability
  • 3.6.8 False Positives and False Negatives
  • 3.6.9 Overfitting
  • 3.7 Future Directions
  • 3.7.1 Conclusion
  • References
  • Chapter 4 Transmit Texts Covertly Using Trigonometric Functions and Pythagorean Theorem
  • 4.1 Introduction
  • 4.2 Mainstream Definition
  • 4.2.1 Plain Text
  • 4.2.2 Cipher Text
  • 4.2.3 Cipher
  • 4.2.4 Encryption
  • 4.2.5 Decryption
  • 4.2.6 Trigonometric Functions
  • 4.2.7 Pythagorean Theorem

Similar Items