Recent research indicates that organizational insiders perpetrate 35 percent of data breaches, and malicious insider incidents cost organizations an average of $701,500 annually. The study and management of insider threat and risk remain areas of increasingly growing attention, prevalence, and concern, but capturing and sharing information about insider incidents in a standardized way has been a challenge for practitioners. A standard of incident classification and information sharing could allow practitioners to build, maintain, deidentify, and share insider threat case data with an eye toward building more robust data for analysis and insights that benefit their organizations and the whole community. In this blog post from the Carnegie Mellon University Software Engineering Institute, we introduce the Insider Incident Data Exchange Standard (IIDES) schema for insider incident data collection, provide an example use case, and invite you to collaborate with us on its development.
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