On February 22, California-based cybersecurity firm Palo Alto Networks announced the most comprehensive Internet of Things (IoT) security solution for healthcare on the market.
The new solution would help the internet of medical things (IoMT) sector will be better protected against cyberthreats with better visibility thanks to insights on devices and will discover vulnerabilities early thanks to machine learning algorithms.
Over 2,000 healthcare institutions, organizations, and hospitals around the world rely on Palo Alto Networks to protect them from cyberattacks, patient data breaches, and other security operations.
Gartner predicts that there will be 25 billion connected devices (IoT) by 2021, a good part of them employed in the healthcare sector. With a record-breaking wave of ransomware attacks targeting American hospitals since the COVID-19 pandemic started, this announcement comes at the right time.
In their March 2020 report, Unit 42 cybersecurity researchers of Palo Alto showed that 83% of medical imaging devices run on unsupported operating systems, which made them potential targets for attackers. Attackers could breach such systems and disrupt vital healthcare services and leak patient data.
Palo Alto’s new platform for healthcare will feature crowd-sourced telemetry for profiling devices over the network, providing automated policy recommendations, and intrusion prevention. While sandboxing will be used for detecting and preventing IoT malware. The platform will have inproved URL and DNS security, the company says.
“IoMT has the potential to improve healthcare, save lives, and bring massive savings. But if not properly secured, these same devices can pose huge risks,” Anand Oswal, Palo Alto’s senior vice president, said.
Besides the above, Palo Alto’s IoMT healthcare system will feature MDS2 Document Ingestion feature which will allow medical device manufacturers to disclose security-related details about their devices. This will allow for specific recommended policies and deeper vulnerability analysis.
While using the platform, biomedical and clinical engineering teams will get insights on how the network is being used and how how they can optimize patient care, resource allocation, and capital planning.
