AI-Driven Cybersecurity Solutions Enhancing Threat Detection in Healthcare and Airlines

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Abstract

The increasing sophistication and volume of cyber threats pose significant challenges to sectors such as healthcare and airlines, where data sensitivity and operational continuity are paramount. Artificial Intelligence (AI) offers transformative potential to address these challenges by enabling advanced threat detection, real-time response mechanisms, and proactive defense strategies. This abstract explores the role of AI-driven cybersecurity solutions in enhancing threat detection capabilities within these critical industries. AI techniques, such as machine learning (ML) and deep learning (DL), facilitate the identification of anomalous behaviors and patterns in complex data environments. In healthcare, these systems safeguard patient records, medical devices, and infrastructure from breaches, ensuring compliance with stringent regulatory standards like HIPAA. Similarly, in airlines, AI-driven models monitor operational systems and passenger data to detect cyber threats targeting reservation systems, flight operations, and critical avionics. By integrating AI with traditional security frameworks, these sectors can transition from reactive to predictive security postures. Key advantages include reduced response times, improved accuracy in identifying emerging threats, and the ability to adapt to evolving attack vectors. This abstract concludes by emphasizing the need for continued innovation, ethical considerations, and cross-industry collaboration to fully leverage AI’s capabilities in fortifying cybersecurity.

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