It’s scary to image that the new generation of combat might reach the very hospital beds of our wounded veterans.
As interactive devices and the internet of things become more entrenched in military health, the health information of our military can easily become compromised. More importantly, it is absolutely possible that bad actors can take control of unsecured medical devices.
There is a wealth of data within the military health system. Health IT professionals need to harness that data to create business and medical intelligence – not so much collection and querying, but exploiting big data for information on how systems need to be securely positioned. We need systems to predict how to best use and position our medical resources to cater to service members and their families.
By marrying data analytics with security, this mass of information should be able to provide possible lines of defense in the fight against cybersecurity intrusion. That’s the next generation of security. Monitoring and other security tools will become predictive rather than static – sharing insights that might otherwise have been missed, or to react faster to potential threats than a human may have been able to react previously.
Where does security fit in?
Data analytics is an important tool for looking at the overall IT ecosystem and across devices. IT professionals can see which devices are up to date, which may not have been patched in a while and the ones that may be at the end of their useful life.
Questions that the Military Health System is already undertaking to answer include: Which IV pumps already meet security and interoperability standards? How can the 10 or so networked devices in an ICU communicate with each other and externally in a secure manner? These cybersecurity efforts are essential, not an added burden, and analytics can offer real help.
I’ve already touched on traditional network monitoring, but this is another area where data analytics and security come together. Central monitoring for threats to the network happens through the Defense Health Agency Network Operations Center (DNOC) in San Antonio. This is the front line for monitoring cyber threats for defense health. When the network is secure, analytics is still helpful to identify trends to learn from.
Protection from ransomware
Along these same lines, the Department of Defense health community needs to leverage predictive analytics to protect against cyber threats such as ransomware. There is a rapidly growing list of examples of ransomware targeting the health industry. Predictive analytics can look for deviations from how the network should behave, rather than relying on known signatures (which is not wholly effective when threats are continually evolving).
Again, the prevalence of connected devices and ever-evolving threats require traditional cybersecurity be tied to analytics. Data and analytics must be used not to describe what already happened but to augment current practices to map out the way ahead.
It is critical to secure medical devices, especially as they communicate and function with other devices and IT networks. Because medical devices are increasingly becoming IT devices, they are the best way to underscore the importance of securing IoT devices in a network. It’s not just information, but the very loss of life and limb that’s at stake.
Want to take your big data practice to the next level? Find out how Arrow can help.
This article originally appeared in the Government InfoSec blog.
By Lloyd McCoy
Manager, Market Intelligence
Arrow ECS and immixGroup, an Arrow company
Last modified: May 2, 2019