How New Approaches Can Help Us Prepare for Unforeseen Viral Attacks
Relying on our knowledge of the known is not enough when it comes to managing risk and maintaining health and security.
From smallpox to SARS to Ebola, we humans have been fighting viral outbreaks for centuries. Even as we recover from one outbreak, we begin to look ahead to try and understand what might come next. We attempt to learn from the past as we work to build new defenses, and we do our best to ensure we can stop the spread of damaging new attacks.
Still, despite ongoing medical and technological advancements that continue to improve our ability to identify, track, and battle fast-spreading diseases, we continue to be caught unawares by viruses that emerge and evolve faster than we can adapt. Reliance on the known continues to leave us vulnerable in the face of the unknown.
We are witnessing this right now with COVID-19.
To be fair, it’s impossible to predict a global pandemic. However, we do now have the ability to combine our knowledge of the past with advanced technologies that can enable proactive detection of new and unknown attack types.
From our work in the field of fraud prevention — where rapidly-spreading viruses are also an ongoing problem — we know that technologies such as unsupervised machine learning offer unprecedented capabilities for addressing emerging threats in real time, and at scale.
I write about this in detail on DataVisor’s blog, in a new article you can find here. Among the topics I cover are valuable lessons we can apply to future threat scenarios:
- Reactivity is no longer a viable approach.
- Everything today is interconnected.
- Knowing the unknown is critical for safety and security.
- Centralized intelligence is the difference between success and failure.
From all of us at DataVisor, please stay safe, stay healthy, and continue to follow the latest recommendations for preventing the spread of COVID-19!
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