4 Ways to Protect Your Business from Zero-Day Attacks
Zero-day attacks cost businesses millions of dollars in lost revenue and recovery costs and can cripple a company that is not prepared to respond decisively and effectively.
Zero-day attacks cost businesses millions of dollars in lost revenue and recovery costs and can cripple a company that is not prepared to respond decisively and effectively.
Not all Artificial Intelligence is created equal. As we move towards a future where we lean on cybersecurity much more in our daily lives, it’s important to be aware of the differences in the types of AI being used for network security.
Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably when discussing developments in deep learning. However, there is an important difference between the two that network security professionals will need to understand in order to serve their clientele effectively.
In the face of intelligent cyber threats, the best defense is to supplement traditional methods with anomaly detection through unsupervised artificial intelligence (AI).
Mixmode’s platform utilizes third-wave, context-aware AI to inform the user of threats (including Zero-Day, and encrypted traffic) on their network, and reduces the rate of false positives in intel and alerts consistently by 90% or more.
Unsupervised artificial intelligence, also known as context-aware or third-wave AI, is notoriously difficult to explain because there lacks an appropriate test to understand just how powerful the intelligence is. The widely known Turing Test for AI testing is no longer the right framework for modern-day AI testing.
MSSPs are helping their customers deal with a fast-paced and ever-evolving threat landscape. It is critical, now more than ever, to evaluate new monitoring tools that produce more actionable data and alerts to help unearth and combat these modern threats more efficiently. I recently read an article titled “4 Technologies SMBs Can Use to Modernize …
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