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Healthcare Faces Rising Cyber Threats: Generative AI Deep Fakes Target Vulnerable Systems

Healthcare organizations face a critical threat as generative AI deep fakes contribute to rising cyberattacks, exacerbated by a projected shortage of 18 million workers by 2030.

The holidays are fast approaching, and for healthcare professionals that means increased patient volumes and staffing shortages, compounded by the emotional toll that comes with working in healthcare during the holidays. It’s an infamous time during which healthcare organizations become even more vulnerable to cyber attacks. As a new and increasingly common cyber threat emerges, healthcare organizations need to educate and prepare themselves, their teams, and their networks to prevent costly breaches and maintain patient safety.

Bad actors are increasingly using generative AI-powered deep fakes to launch phishing and social engineering attacks on organizations across industries. From audio calls impersonating senior U.S. officials in an attempt to secure sensitive government information to live video interviews with deep fake candidates, these sophisticated attacks have made national headlines over the last several months. Organizations are increasingly likely to encounter them moving forward. These emerging deep fake campaigns pose yet another threat to the already uniquely susceptible healthcare industry.

The global healthcare workforce was estimated by the World Health Organization (WHO) to have reached 65.1 million in 2020, and that number is expected to hit 84 million by 2030. The size and interconnectedness of the world’s healthcare systems—including numerous departments within every hospital, pharmacies, and third-party vendors—alone make it vulnerable to cybercrime. But bad actors are drawn to healthcare organizations for a litany of reasons. Many hospitals and related facilities operate using outdated communications tools and data-storage technologies, and are hampered by tight budgets that complicate tech upgrades and sufficient staffing.

Indeed, healthcare systems and workers are already stretched thin—and are getting thinner: The WHO also estimates a shortage of 18 million healthcare workers by 2030. The sensitive information flowing through these systems, combined with the inherent importance of maintaining public trust, have made healthcare organizations a prime target for AI-driven cyberattacks.

As cyberattacks grow increasingly varied and complex, everyone from physicians to patients to administrators must remain hyper-aware and maintain a robust level of skepticism in nearly every healthcare interaction that isn’t face-to-face. Comparatively analog threats such as intercepted and doctored emails are still in use because they are effective, requiring only a brief moment of impatience or forgetfulness on the part of the receiver to do their work. Manipulated phone messages and video interactions, however, are growing increasingly convincing by the day.

With the holiday season approaching, the urgency for healthcare organizations to bolster their cybersecurity measures has never been more critical. The intersection of heightened patient demand, staffing shortages, and sophisticated cyber threats like generative AI deep fakes presents a formidable challenge. As healthcare providers face these mounting pressures, ensuring robust training and preparedness within their teams will be essential to safeguarding sensitive patient data and maintaining trust in the healthcare system.

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Rachel Torres
Written By

At AIPressa, my work focuses on exploring the paradox of AI in cybersecurity: it's both our best defense and our greatest threat. I've closely followed how AI systems detect vulnerabilities in milliseconds while attackers simultaneously use them to create increasingly sophisticated malware. My approach: explaining technical complexities in an accessible way without losing the urgency of the topic. When I'm not researching the latest AI-driven threats, I'm probably testing security tools or reading about the next attack vector keeping CISOs awake at night.

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