Table of Contents:
  • Chapter 1. Can pruning make large language models more efficient?
  • Chapter 2. Comprehensive review and analysis of network firewall rule analyzers: enhancing security posture and efficiency
  • Chapter 3. Do generative large language models need billions of parameters?
  • Chapter 4. Enhancing IoT security: leveraging advanced deep learning architectures for proactive botnet detection and network resilience
  • Chapter 5. Ethical considerations in implementing artificial intelligence in cybersecurity: balancing security and privacy concerns
  • Chapter 6. Exploring blockchain-based timestamping tools: a comprehensive review
  • Chapter 7. Exploring the landscape of website vulnerability scanners: a comprehensive review and comparative analysis
  • Chapter 8. Investigating the limitations of adversarial training for language models in realistic spam filter deployment scenarios
  • Chapter 9. Source code vulnerability analysis using GPT-2
  • Chapter 10. Hybrid machine learning model for an intrusion detection system for smart grids using artificial neural network and random forest
  • Chapter 11. Illuminating evidence: explainable AI in cyber crime investigations
  • Chapter 12. The progressive approach of linear substitution cipher for a singular matrices key using AI tools.