The most effective way to identify exfiltration of sensitive data by a malicious insider is to establish behavioral analytics monitoring. Behavioral analytics is the process of analyzing the patterns and anomalies in user behavior to detect and prevent insider threats. Behavioral analytics can help identify unusual or suspicious activities, such as accessing sensitive data at odd hours, transferring large amounts of data to external devices or locations, or using unauthorized applications or protocols. Behavioral analytics can also help correlate data from multiple sources, such as network logs, user profiles, and access rights, to provide a holistic view of user activity and risk.

Data loss prevention (DLP) software is a tool that can help prevent exfiltration of sensitive data by a malicious insider, but it is not the most effective way to identify it. DLP software can block or alert on unauthorized data transfers based on predefined rules and policies, but it may not be able to detect sophisticated or stealthy exfiltration techniques, such as encryption, steganography, or data obfuscation.

Reviewing perimeter firewall logs is a way to identify exfiltration of sensitive data by a malicious insider, but it is not the most effective way. Perimeter firewall logs can show the traffic volume and destination of data transfers, but they may not be able to show the content or context of the data. Perimeter firewall logs may also be overwhelmed by the amount of normal traffic and miss the signals of malicious exfiltration.

Providing ongoing information security awareness training is a way to reduce the risk of exfiltration of sensitive data by a malicious insider, but it is not a way to identify it. Information security awareness training can help educate users on the importance of protecting sensitive data and the consequences of violating policies and regulations, but it may not deter or detect those who are intentionally or maliciously exfiltrating data.