We are studying functional encryption for application in privacy preserving data mining(PPDM). Are there any development or deployment for the same?. Is there any formal or practical aspects available for the exact understanding of performance measure and complexity calculations for various functional encryption policies viz. key policy attribute based encryption, Ciphertext policy attribute based encryption, Inner product encryption for PPDM. Also we want to know about simulation tools suitable for this task.
Maybe a look at Privacy Preservation with Homomorphic Encryption? http://en.wikipedia.org/wiki/Homomorphic_encryption
I think you should go through works on k-anonymity, l-diversity, statistical disclosure control and multiparty computation. I should read carefully this paper:
http://www.sigmod.org/publications/sigmod-record/0403/B1.bertion-sigmod-record2.pdf
To me functional encryption is not the correct tool you want to use. Functional encryption let you to decrypt a ciphertext if your secret key satisfies a function specified when encrypting the ciphertext, but it does not allow you to compute a function on the ciphertext. As Kato and Dadid suggested, homomorphic encryption, anonymization or multiparty computation protocols are more appropriate.
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