Innovative Strategies for Enhancing Cybersecurity in Information Systems: A Holistic Approach in Computer Engineering

The compounded nature of cyber threats, such as ransomware, phishing, and supply chain attacks, has revealed the inadequacy of conventional security controls. AI and machine learning-based solutions offer promising improvements in near-instant threat detection and neutralization, responding to the increasing demand for adaptive cybersecurity measures.This research assesses AI-based cybersecurity models, derives security insights from historical cyber-attacks, measures the effectiveness of regulatory compliance frameworks, and formulates a multi-layered AI-based security strategy. The research is centered on AI as a means of improving cybersecurity, vulnerabilities revealed by historical cyber-attacks, and blending AI-based threat detection with compliance.A mixed-methods research design is used, including case study analysis, expert interviews, surveys, and machine learning model assessments. Case studies of significant cyber-attacks identify vulnerabilities and mitigation measures. Machine learning models are tested on the UNSW-NB15 dataset to determine their performance in identifying cyber threats, and surveys offer information on AI adoption in cybersecurity. The research concludes that AI-based models are much more effective than conventional security measures, with Random Forest and XGBoost delivering more than 95% accuracy in detecting cyber threats. Expert interviews reveal that 90% of cybersecurity experts support AI-based intrusion detection, but only 31% of companies have deployed it. Compliance frameworks like NIST's Risk Management Framework and Zero Trust models offer systematic security solutions but lack real-time AI-based integration.This study illustrates how AI-powered models provide higher accuracy in detecting cyber threats, addressing significant cybersecurity loopholes. It points to the disparity between AI potential and organizational adoption while underlining the importance of integrating AI-powered security with compliance frameworks for a more responsive cybersecurity framework.The results highlight the need for AI-based cybersecurity tools that integrate real-time threat identification, automated protection, and compliance support. Companies need to step up AI implementation, cybersecurity awareness training, and regulation integration to build robust defenses against emerging threats.