By incorporating UEBA into their cybersecurity tools, organizations not only improve their defense against insider threats but also promote an ethical and unbiased monitoring approach, resulting in organisations protecting their assets while maintaining the dignity and trust of their employees.
From 2019 to 2024, insider threats surged, with 76% of organizations reporting incidents, often accidental rather than malicious. To address this, User and Entity Behavior Analytics (UEBA) offers an ethical, data-driven solution that reduces biases in threat detection. Here is a perspective of Ajay Biyani, VP – APAC, India and MEA at Securonix
In the constantly changing world of cybersecurity, insider threats are a major concern for organizations. In a recent report by Securonix, from 2019 to 2024, the number of organizations reporting insider attacks increased from 66% to 76%, indicating a substantial increase in detected insider threats. While all these attacks are not orchestrated with malicious intent, some are just the result of accidental mistakes made by employees. Organizations are becoming more aware of the potential harm that can come from this which is why many of them are now shifting to next-gen technologies such as User and Entity Behavior Analytics (UEBA) rather than traditional cybersecurity tools. When protecting sensitive information from insider threats, there is also a need to address biases based on factors like race, gender, and nationality in the monitoring process. It is crucial to balance technical expertise with ethical considerations to monitor insider threats effectively.
Biases within insider threat monitoring programs can significantly compromise an organization’s security and adversely affect its culture, morale and reputation. This can lead to unjust targeting of individuals based on factors like race, nationality, gender, or job role, which not only raises ethical concerns but also practical ones. Biases can shift the focus of security efforts and leave vulnerabilities unaddressed.
“Witnessing a substantial increase in insider attacks, organizations must shift from traditional cybersecurity tools to next-generation solutions like User and Entity Behavior Analytics (UEBA).”Ajay Biyani, VP – APAC, India and MEA at Securonix
UEBA technology provides a sophisticated solution to this challenge by emphasizing data-driven objectivity and automated anomaly detection to reduce the risk of biased outcomes. UEBA tools address these concerns in the following ways:
- Data-Driven Insights: UEBA solutions rely on objective, data-driven analysis to detect anomalies based on individual user behavior and avoiding any subjective biases that may target individuals based on job roles, nationality, or working hours. This approach ensures that monitoring efforts are based on factual observations, reducing the potential for biased outcomes.
- Automated Anomaly Detection: By removing the human element from the initial detection phase, UEBA minimizes the potential for human biases to influence threat assessments. Anomalies are flagged based on deviations from established behavioral patterns, rather than assumptions or stereotypes about the individual involved.
- Adaptability and Customization: UEBA technology offers customizable parameters to define normal behavior, accommodating variations in work patterns such as remote work, flexible hours, and international travel. This prevents normal activities from being mistakenly classified as suspicious.
- Transparency and Accountability: UEBA solutions ensure that the logic behind alerts and anomaly detection is clear and understandable, fostering a culture of accountability and helping stakeholders understand and justify security measures.
- Prioritising Behavior over Personal Identity: UEBA focuses on user behavior rather than personal identity, reducing bias in threat detection efforts and aligning with principles of fairness and non-discrimination.
In order to maintain a healthy workplace culture, security professionals often find it challenging internally to convince HR of the importance of accessing certain data logs. However, it is important to note that obtaining this sensitive information is not just a security measure but also a way to protect individuals and the organization at large. For instance, UEBA technology can protect high-risk individuals who may unintentionally become security risks due to their role or access to sensitive information. Additionally, UEBA technology includes a data masking feature to ensure that security investigations are conducted with respect for privacy and without any bias. By anonymizing personal data, UEBA systems prioritize analyzing behavioral patterns, ensuring that security measures are equal for all employees, and ultimately promoting a culture of trust and security within the company.
To conclude, one can rightly say that by incorporating UEBA into their cybersecurity tools, organizations not only improve their defense against insider threats but also promote an ethical and unbiased monitoring approach. When security practices align with values of transparency and inclusivity, organizations can protect their assets while maintaining the dignity and trust of their employees.
