Attackers continue to update their tactics to remain ahead of enterprise defenses and use evasive techniques to avoid detection by traditional cybersecurity tools. Pre-built attack tools, stealthy communications and exfiltration avenues, and advanced phishing techniques are all used to compromise and exploit target organizations. While out-of-band and signature-based detection approaches remain critical in preventing known threats, a new approach is required to protect organizations from these attacks using evasive techniques. As a result, machine learning and advanced analytics have become a critical component of threat prevention tools. Yet, just as importantly, these mechanisms must be applied in line to prevent threats before they can impact even the first potential victim.
Read the white paper today to learn how your organization can leverage inline deep learning to stop today’s most sophisticated attacks as they happen.
