How many more wake-up calls do we need before we recognize that the approaches most organizations take to defend against ransomware are not working? Sponsored by DeepInstinctSec
of cybersecurity and business leaders found that 90 percent believe that current technology simply isn’t capable of providing adequate protection from cyberattacks. Relying on these solutions only emboldens threat actors—cyber-criminals or state-sponsored hackers—who see rewards in disrupting essential elements of daily life.
As a result ML security tools have been found to only detect 60 percent of unknown attacks with a one to two percent false positive rate. The situation is even worse when it comes to legacy security solutions, which can produce 30-50 percent false positives, straining resources as high-salaried experts investigate each alert. Deep learning is the next evolution of machine learning.
To achieve these results, it’s essential to invest in a purpose-built solution. Systems adapted from facial recognition systems, for example, aren’t necessarily appropriate for the specialized needs of cybersecurity. Many existing behavioral ransomware protection features rely on mechanisms such as honey pots, mock target files, or volume shadow copies access. But, ransomware actors are well aware of these approaches. What’s needed is a tool that monitors every file-system operation on the machine . Speed is critical to cybersecurity. When battling ransomware, reactions must be measured in milliseconds.
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