All Research Sponsored By:Deep Instinct
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AI in Cybersecurity: Friend or Foe?
Cybersecurity experts battle AI threats like deepfakes. Many use outdated EDR tools, but prevention strategies are emerging. This report explores predictive prevention for pre-emptive defense. Discover how to preempt evolving cyber risks in the full report.
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The Evolution of AI in Cybersecurity: Breaking the Cycle of Reactionary Cybersecurity
While security teams strive to combat new threats as fast as they can, as long as their approach is reactionary, hackers will always have the upper hand. This white paper examines how the adoption of AI and ML presents an opportunity to overcome reactionary approaches and achieve proactive anti-malware security. Read on to learn more.
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File Upload Security: The Missing Category for a Comprehensive Security Posture
Organizations accept files through their web applications to run their business. But, files being uploaded by customers could contain malware or some other risk that could hurt your business. What is scarier is that 80% of successful breaches come from zero-day attacks. Read on to learn more and don’t let malicious files stay like uninvited guests.
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Deep Learning vs. Machine Learning in Cybersecurity
This eBook compares the differences between deep learning and machine learning tools for cybersecurity, helping you determine which makes the most sense for your business. Read the eBook here.
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Deep Learning Delivers Proactive Cyber Defense
Amidst the cybersecurity skills shortage, organizations are hard pressed to find new answers to evolving problems. Deep learning, a subset of machine learning, offers a highly accurate way to identify attack patterns and stop threats before they become attacks, without the need for highly skilled cybersecurity experts. Read on to learn more.