Artificial Intelligence Security Threats and Trends
Author(s):
Joshua Adiele
Artificial Intelligence (AI) has become a foundational technology shaping the modern digital era, influencing domains from healthcare and finance to national security and manufacturing. However, as AI systems become integral to daily operations and decision-making processes, their vulnerabilities expose new frontiers of cybersecurity risks. This paper explores the evolving landscape of AI security threats and emerging trends in mitigating such challenges. It highlights key vulnerabilities including data poisoning, adversarial attacks, model inversion, membership inference, and AI-powered cybercrime. It also examines the role of explainable AI (XAI), privacy-preserving learning techniques, adversarial defense mechanisms, and regulatory frameworks as emerging strategies to secure AI systems. The paper concludes by recommending a holistic approach that integrates ethical governance, technical safeguards, and global policy frameworks to ensure trustworthy and resilient AI development.