Abstract
With the continuously increasing number of data leakage security incidents caused by organization insiders, current security activities cannot predict a data leakage. Because such security incidents are extremely harmful and difficult to detect, predicting security incidents would be the most effective preventative method. However, current insider security controls and systems detect and identify unusual behaviors to prevent security incidents but produce many false-positives. To solve these problems, the present study collects and analyzes data leaks by insiders in advance, analyzes information leaks that can predict security incidents, and evaluates risk based on behavior. To this end, data leakage behaviors by insiders are analyzed through an analysis of previous studies and the implementation of an in-depth interview method. Statistical verification of the analyzed data leakage behavior is performed to determine the validity and derive the levels of leakage risk for each behavior. In addition, by applying the N-gram analysis method to derive a data leakage scenario, the levels of risk are clarified to reduce false-positives and over detection (i.e., the limitations of existing data leakage prevention systems) and make preemptive security activities possible.
Highlights
Security attacks that threaten the wellbeing of organizations are changing in various ways, including cyber-attacks
In the case of Google’s autonomous vehicle project Waymo, after the main employee who executed the project left the company, he founded a startup company and sold the trade secrets of his previous company to other companies. This exemplifies how mainstream security attacks have changed from being caused by outsiders to being caused by insiders, but the countermeasures implemented by organizations have not evolved from existing cyber-attack frameworks to adjust to this change
We focused on previous that used scenarios of security incidents involving insider threats
Summary
Security attacks that threaten the wellbeing of organizations are changing in various ways, including cyber-attacks. In the case of Google’s autonomous vehicle project Waymo, after the main employee who executed the project left the company, he founded a startup company and sold the trade secrets of his previous company to other companies This exemplifies how mainstream security attacks have changed from being caused by outsiders to being caused by insiders, but the countermeasures implemented by organizations have not evolved from existing cyber-attack frameworks to adjust to this change. Weaccording collect in to advance the signs of data leakage by insiders of the organization, analyze the signs of The introduction (above) explains research methodology, whichInwas intended overcome limits of existing leakage prevention and background. Through in-depth interviews and an analysis of earlier studies, we derive the data leakage limitations of existing data leakage prevention solutions.
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