Observable artifacts or forensic evidence that indicate a potential intrusion or malicious activity has occurred on a system or network.
For insider threats, IOCs include unusual file access patterns, off-hours system activity, large data downloads, access to unauthorized systems, or behavioral changes. Advanced insider threat programs use machine learning to identify subtle IOCs that may indicate malicious or compromised insider activity. These indicators are often more behavioral than technical compared to external threat IOCs.
A proactive security approach where analysts actively search for hidden threats and malicious activities within an organization's environment using various tools and techniques.
The practice of collecting, preserving, analyzing, and presenting digital evidence in a legally admissible manner for investigations and legal proceedings.
The use of statistical analysis and machine learning to identify patterns in user behavior and detect anomalies that may indicate security threats or policy violations.