Survey of Machine Learning Methods for Database Security
msra(2009)
摘要
Application of machine learning techniques to database security is an emerging area of research. In this chapter, we present
a survey of various approaches that use machine learning/data mining techniques to enhance the traditional security mechanisms
of databases. There are two key database security areas in which these techniques have found applications, namely, detection
of SQL Injection attacks and anomaly detection for defending against insider threats. Apart from the research prototypes and tools, various third-party commercial products
are also available that provide database activity monitoring solutions by profiling database users and applications. We present
a survey of such products. We end the chapter with a primer on mechanisms for responding to database anomalies.
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关键词
machine learning,data mining,sql injection attack,anomaly detection
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