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It depends on what properties the compression function has, which in turn depends on how the hash function was constructed. In hash functions based on the Merkle–Damgård construction, the compression function is required to be collision, preimage and second preimage resistant, just like the hash function itself. The only difference is input length: the ...


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In a Merkle Tree, data is eventually and inevitably lost, because it is compressed away. If a Merkle Tree used a non-padded compression function, the size of the resulting hashes would go down level by level, resulting in a top hash that is very short. The shorter that top hash is, the less it CAN say about the contents of its tree. The longer the resulting ...



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