![](bg8.png)
NSL-KDD dataset and SEAL homomorphic library,
are promising in terms of accuracy.
In the future, we plan to ameliorate the execu-
tion times of the prediction over encrypted data. We
will investigate the use of the plaintext space of BFV
scheme to compute the prediction results of many in-
puts simultaneously. Second, we will use other homo-
morphic encryption schemes, namely TFHE (Chillotti
et al., 2016) or CKKS (Cheon et al., 2016) for our
classification. TFHE and CKKS are interesting as
they use floating point numbers. Second, we intend
to implement and test other classification algorithms
(e.g. neural networks) for the analysis of the en-
crypted logs.
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