Medical deepfakes: A severe attack on healthcare

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  Quantumrun Foresight
• June 14, 2023

Insight highlights

Medical deepfakes can lead to unnecessary or wrong treatments, causing financial losses and potential fatalities. They erode patient trust in the medical sector, leading to hesitancy in seeking care and using telemedicine. Medical deepfakes also pose a cyber warfare threat, disrupting healthcare systems and destabilizing governments or economies.

Medical deepfakes context

Deepfakes are digital alterations designed to trick someone into thinking they're authentic. In healthcare, medical deepfakes involve manipulating diagnostic images to falsely insert or delete tumors or other medical conditions. Cybercriminals are constantly innovating new methods of launching medical deepfake attacks, aiming to disrupt the operations of hospitals and diagnostic facilities.

Manipulated imaging attacks, such as inserting false tumors, can lead to patients undergoing unnecessary treatments and exhaust millions of dollars in hospital resources. Conversely, eliminating an actual tumor from an image can withhold necessary treatment from a patient, exacerbating their condition and potentially resulting in fatalities. Given that 80 million CT scans are conducted annually in the US, according to a 2022 study on medical deepfake detection, such deceitful tactics can serve politically or financially motivated agendas, such as insurance fraud. As such, developing robust and dependable strategies for detecting and identifying image alterations is critically important.

Two frequent methods of image tampering include copy-move and image-splicing. Copy-move involves overlaying a non-target area on top of a target region, effectively hiding the part of interest. Additionally, this method can multiply the target region, exaggerating the prevalence of places of interest. Meanwhile, image-splicing follows a procedure similar to copy-move, except the duplicate area of interest comes from a separate image. With the rise of machine and deep learning techniques, attackers can now learn from vast image databases using tools like generative adversarial networks (GANs) commonly used in fabricated videos.

Disruptive impact

These digital manipulations could significantly undermine the reliability and integrity of diagnostic processes. This trend could ultimately increase healthcare costs substantially due to the potential legal fees associated with malpractice suits. Furthermore, the misuse of medical deepfakes for insurance fraud could contribute to the economic burden on healthcare systems, insurers, and, ultimately, patients.

In addition to financial implications, medical deepfakes also seriously threaten patient trust in the medical sector. Trust is a cornerstone of effective healthcare delivery, and any harm to this trust could lead to patients hesitating or avoiding necessary medical care due to fear of being misled. In global health crises like pandemics, this mistrust can result in millions of deaths, including rejecting treatments and vaccines. The fear of deepfakes could also discourage patients from participating in telemedicine and digital health services, which have become increasingly important in modern healthcare.

Moreover, the potential use of medical deepfakes as a tool of sabotage in cyber warfare cannot be underestimated. By targeting and disrupting hospital systems and diagnostic centers, adversaries could create chaos, cause physical harm to many people, and instill fear and distrust in the populace. Such cyber-attacks could be part of wider strategies to destabilize governments or economies. Therefore, national security and public health infrastructure need to proactively develop strategies to detect and prevent these potential threats. 

Implications of medical deepfakes

Wider implications of medical deepfakes may include: 

• Increased medical misinformation and potentially harmful self-diagnosis leading to worsening epidemics and pandemics.


• Significant financial losses for pharmaceutical companies and medical device manufacturers as misinformation and hesitancy cause their products to expire or be misused, leading to lawsuits.


• The potential to be weaponized in political campaigns. Deepfakes could be used to create false narratives about the health conditions of political candidates or about non-existent health crises to induce panic, leading to instability and disinformation.


• Vulnerable populations, such as the elderly or those with limited access to healthcare, becoming the primary target of medical deepfakes to encourage them to purchase unnecessary medicines or self-diagnose.


• Significant advancements in artificial intelligence and machine learning algorithms to accurately identify and filter out deepfake medical content.


• Mistrust in scientific research and peer-reviewed studies. If manipulated research findings are presented through deepfake videos, it may be challenging to discern the authenticity of medical claims, hindering advancements in medical knowledge and potentially leading to the spread of false information.


• Doctors and other healthcare professionals being misled by deepfakes, ruining their reputations and careers.

Questions to consider

• If you’re a healthcare professional, how is your organization protecting itself from medical deepfakes?


• What are the other potential dangers of medical deepfakes?