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The F-Secure Approach to AI

Machine learning algorithms have rapidly become the key to advancing technologies far beyond their current capabilities. Their ability to analyze large amounts of data, autonomously evolve to meet dynamic challenges, and surpass the limitations of the human mind, present tremendous possibilities for the future.

But with those possibilities come dangers. While Hollywood paints a rather far-fetched picture of machines rising up and eradicating humanity, the current reality is that many machine learning powered systems are susceptible to attack. And they’re being attacked right now. At F-Secure, we’ve been reproducing and analyzing those attacks in order to implement better security for machine learning.

Machine learning is also an important tool in the cyber security domain. Machine learning techniques are already being used to protect nations, organizations, and individuals from cyber attacks, to predict future adversarial tactics, and to track cyber criminal activities. At F-Secure, we’re always looking for new ways to apply advances in the field of machine learning to tasks in our own domain. And with efforts such as Project Blackfin, we’re doing research that will reveal how machine learning for security will be implemented in the near and distant future.


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