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Security is becoming one of the most urgent challenges in database research and industry, and there has also been increasing interest in the problem of building accurate data mining models over aggregate data, while protecting privacy at the level of individual records. Instead of building walls around servers or hard drives, a protective layer of encryption is provided around specific sensitive data items or objects. This prevents outside attacks as well as infiltration from within the server itself. This also allows the security administrator to define which data stored in databases are sensitive and thereby focusing the protection only on the sensitive data, which in turn minimizes the delays or burdens on the system that may occur from other bulk encryption methods. Encryption can provide strong security for data at rest, but developing a database encryption strategy must take many factors into consideration. We present column-level database encryption as the only solution that is capable of protecting against external and internal threats, and at the same time meeting all regulatory requirements. We use the key concepts of security dictionary, type transparent cryptography and propose solutions on how to transparently store and search encrypted database fields. Different stored data encryption strategies are outlined, so you can decide the best practice for each situation, and each individual field in your database, to handle different security and operating requirements. Application code and database schemas are sensitive to changes in the data type and data length, the paper presents a policy driven solution that allows transparent data level encryption that does not change the data field type or length.