IoCs were missed during a recent security incident due to the reliance on a signature-based detection platform. A security engineer must recommend a solution that can be implemented to address this shortcoming. Which of the following would be the most appropriate recommendation?
A signature-based detection platform relies on predefined patterns to identify potential threats, which can lead to missed indicators of compromise (IoCs) for new or unknown threats. User and Entity Behavior Analytics (UEBA) utilizes machine learning and advanced analytics to monitor and analyze the behaviors of users and entities within the network. By focusing on deviations from normal behavior rather than just known patterns, UEBA can identify and respond to anomalies that may indicate security threats, thus addressing the shortcomings of purely signature-based detection systems.
UEBA focuses on analyzing the behaviors of users and entities within the network to identify anomalies that may indicate security threats. Unlike signature-based detection, which relies on known patterns of malicious activity, UEBA uses machine learning and advanced analytics to detect deviations from normal behavior. This approach can identify new and unknown threats that do not match existing signatures, thus addressing the limitation of missing IoCs that signature-based systems might overlook