As cyberthreats loom larger over healthcare, the industry stands at a critical crossroads—innovation or vulnerability. In the face of rising attacks on hospitals and medical devices, we spoke to Nitin Kumar, VP and Business Head of the Healthcare business unit at Tata Consultancy Services (TCS), about the pressing cybersecurity challenges. From AI risks to securing wearable tech, he shares strategies to safeguard patient data while embracing Digital Transformation.
With the rise in cyberattacks on healthcare institutions, including the recent incidents in London, what do you believe are the most pressing cybersecurity challenges facing the healthcare industry today?
A holistic approach is essential, including security awareness training to embrace Digital Transformation. While the healthcare industry is more prepared today to address emerging scenarios, these promising valuable advancements in patient care also come with its own cybersecurity risks if not managed correctly. It’s no longer just about protecting sensitive data from hackers seeking financial gain. We’re talking about safeguarding biometric information, ensuring the integrity of life-saving medical devices and navigating the ethical complexities of AI in healthcare.
The interconnected nature of modern healthcare, with data flowing between hospitals, clinics, insurance providers and even patients’ personal devices, creates a complex attack surface. Add to this the rise of telehealth and remote monitoring, the most pressing challenge in healthcare is the need for a multi-layered cybersecurity strategy. With the healthcare industry being one of the most regulated industries out there, we advise strict adherence to regulatory compliance as crucial for a secure and resilient healthcare industry.
As healthcare increasingly adopts wearable technology and remote monitoring systems, how can organisations address the unique vulnerabilities these devices introduce? What best practices should be followed?
To harness the full potential of wearable technology and remote monitoring systems in healthcare, organisations should adopt several best practices like data protection through advanced encryption, homomorphic computing and strict access controls.
A fundamental shift in mindset is required, one that embeds security into the very DNA of these devices from the outset. For instance, we use unique aliases and pseudonyms and ensure default settings are optimised for data security to protect personal information. We also leverage TinyML to analyse sensitive data directly on the device, minimising external transmission and advocating for continuous monitoring of ecosystems and data chains.
Imagine a pacemaker that can be remotely updated with life-saving software patches, but only by authorised medical professionals. Or a wearable health tracker that empowers patients with personalised insights, while ensuring their data remains confidential and secure. Achieving this delicate balance requires embedding intelligence at the device and edge and using trusted platforms for mobile healthcare applications. We also use new approaches like federated learning, as it extracts valuable insights from data without compromising patient privacy.
Critical medical devices like pacemakers need to remain accessible for updates and maintenance. How can healthcare providers balance the need for accessibility with the necessity of maintaining strong security measures?
The interconnected nature of modern medical devices presents a unique challenge: balancing the need for accessibility with the imperative for security. Considering the lifesaving capabilities of pacemakers, it’s crucial we prioritise robust security measures to ensure patient safety and maintain trust in modern healthcare solutions.
To do so, healthcare providers must adopt a multi-layered approach to security, starting with rigorous adherence to industry regulations and best practices of ‘Software as a Medical Device’. Data anonymisation techniques, robust encryption protocols and leveraging edge computing to minimise data transmission are all critical ways to minimise the exposure of sensitive information. This is further bolstered by implementing biometric authentication and incorporating separate security units to mitigate battery impact.
The use of AI in healthcare is growing rapidly. How does the integration of AI both benefit and potentially increase the risk of cyberthreats? What strategies can be employed to mitigate these risks?
AI is revolutionising healthcare by enhancing patient care and operational efficiency, presenting numerous opportunities to improve outcomes. However, AI also requires careful management to address biases, explainability and associated scenarios.
Mitigating these risks requires a multi-pronged approach. Secure data management practices, including encryption and stringent access controls, are crucial. Minimising data collection, ensuring data integrity and regularly updating AI models with accurate, diverse data points are essential. Adopting ethical AI development principles and fostering a culture of security awareness among stakeholders can aid this process too.
Protecting hyper-personalised health data, such as information related to emotional and mental states, presents unique challenges. How can healthcare organisations ensure this data is secure while still enabling its use in patient care?
Protecting hyper-personalised health data requires robust security measures. Granular access controls are a simple starting point, which will limit access to authorised personnel with legitimate needs. To take it further, technologies like digital lockers, which give patients greater control over their data, help further protect their data.
When the onus is on healthcare organisations to handle data, de-identifying and anonymising patient data for analysis is a simple way for firms to gain valuable insights while preserving patient privacy. By embracing a culture of data privacy through ongoing training and strict adherence to regulations, healthcare organisations can build unwavering trust with patients while harnessing the full potential of data for improved care.
Looking towards the future, with projections indicating over 750 million connected devices by 2026, what are some key areas where healthcare professionals should focus their cybersecurity efforts? How can they stay ahead of emerging threats?
The future of healthcare, from our point of view, is bright with the integration of connected devices, offering immense opportunities for innovation. With the proliferation of connected devices, healthcare professionals must focus on key areas like securing the entire ecosystem, not just individual devices.
By embracing a zero-trust model and implementing authentication protocols for every user, every device and utilising secure platforms with data protection measures, healthcare professionals can strengthen their edge security (particularly for wearable devices).
Also measures like integrating intelligence at the device level for secure data sharing and leveraging AI-driven threat intelligence for real-time threat mitigation are vital. Ultimately, the future of healthcare cybersecurity depends on a collective commitment to safeguarding patient safety and privacy in the digital age.
