FiFTy uses a compact 1-D convolutional network with a trainable byte embedding to classify raw memory blocks into 75 file types, reaching 77.5% average accuracy at 38 seconds per GB.
Sceadan: Using Concate- nated N-Gram Vectors for Improved File and Data Type Classification,
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FiFTy: Large-scale File Fragment Type Identification using Neural Networks
FiFTy uses a compact 1-D convolutional network with a trainable byte embedding to classify raw memory blocks into 75 file types, reaching 77.5% average accuracy at 38 seconds per GB.