Addressing Bias in Insider Risk Monitoring

Enterprises often take similar steps to protect data from internal and outside threats, where teams analyze activities to identify potential risks.
Security operations centers defending against these threats must look at employees, partners, and threat actors through a similar lens to pinpoint potential data leaks.
When surveilling for insider threats, there is the added concern of potential bias.
Monitoring bias is the unfounded, often discriminatory observation of specific employees or departments irrespective of their conduct.
This can generate unsupported, negative conclusions about the credibility and trust an organization should have about an employee or department, resulting in intrusive monitoring.
Conversely, it can lead to data leaks if biases prevent other employees from being adequately monitored.
Monitoring bias affects how businesses analyze insider risks, resulting in errors that can prevent identifying potential threats.
Unequal Monitoring: Monitoring specific members of your organization without holding others to the same standard can result in low visibility of vulnerabilities that, when spotted, can prevent insider threats.
Selective Attention: Concentrating on specific actions or behaviors instead of considering other risk indicators.
Attribution Bias: Judging specific employees or departments as presenting a heightened or lowered risk for an organization without considering their behaviors is attribution bias.
This leads to inaccuracies when developing risk profiles.
Group Identity Bias: Stereotyping employees and assuming they present a higher risk based on their backgrounds can generate inaccurate assessments of their level of risk.
Confirmation Bias: Monitoring bias can cause organizations to believe data that supports preconceived assumptions is far more trustworthy than it is, resulting in a lack of focus on contradictory information.
These biases can inadvertently make security teams fail to see risky activities from other employees, partners, or threat actors.
Older, legacy Data Loss Prevention and Insider Risk Management solutions use dated blueprints to run locally within organizational firewalls.
It is best practice to reduce bias when monitoring employees by pinpointing activities involving sensitive data that can jeopardize sensitive information.
Using technology that anonymizes employees while monitoring activities to maintain organizational security is crucial for eliminating bias.
This monitoring technology still allows teams to unveil users displaying suspicious activity by providing 'scoped investigations,' giving audited data access to investigators with limited access to maintain privacy regulations.
Protecting and identifying employee information helps security teams detect risks without the interference of bias.
This form of anonymity in monitoring provides teams with a holistic view of organizational activities that help detect threats and reduce monitoring bias, supporting an impartial management program that employees can trust.


This Cyber News was published on www.cyberdefensemagazine.com. Publication date: Fri, 09 Feb 2024 14:13:03 +0000


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