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WIREs Data Mining Knowl Discov
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Enterprise data breach: causes, challenges, prevention, and future directions

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A data breach is the intentional or inadvertent exposure of confidential information to unauthorized parties. In the digital era, data has become one of the most critical components of an enterprise. Data leakage poses serious threats to organizations, including significant reputational damage and financial losses. As the volume of data is growing exponentially and data breaches are happening more frequently than ever before, detecting and preventing data loss has become one of the most pressing security concerns for enterprises. Despite a plethora of research efforts on safeguarding sensitive information from being leaked, it remains an active research problem. This review helps interested readers to learn about enterprise data leak threats, recent data leak incidents, various state‐of‐the‐art prevention and detection techniques, new challenges, and promising solutions and exciting opportunities. WIREs Data Mining Knowl Discov 2017, 7:e1211. doi: 10.1002/widm.1211 This article is categorized under: Application Areas > Business and Industry Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Technologies > Prediction
Classification of enterprise data leak threats.
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MR‐DLD throughput on a local cluster and Amazon EC2.
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Workload distribution between the data owner and data leak prevention and detection (DLPD) provider.
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An example of calculating the intersection rate between two 3‐gram collections. Collection intersection counts duplicated items, whereas the set intersection does not.
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There exist multiple points for deploying complementary data leak prevention and detection (DLPD) techniques in an enterprise environment.
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Breakdown and analysis of the Target data breach.
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Statistics of data leak incidents in recent years (Reprinted with permission from Ref . Copyright 2017 Identity Theft Resource Center). (a) Breaches by industry sector and (b) Breaches by type of occurrence
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Application Areas > Business and Industry
Technologies > Prediction
Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining

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