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As per the definition of Deep Packet Inspection (DPI), it uses signatures for packet filtering. Supervised Machine Learning can help put a label on a packet which does not get identified by Deep Packet Inspection if it does not have a signature that the DPI recognizes. However, apart from this advantage, is there any other advantage/functionality supervised ML has over Deep Packet Inspection?

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Traditionally, signatures are defined by a human having analyzed the various data streams.

ML learns the patterns by inference, making it (potentially) cheaper to use. Also, ML can be used to keep learning while it's running. Generally, it's more flexible and likely quicker to adapt.

Both may obtain similar results. However, the human-created signature is a formulated, comprehensible rule while ML filters might produce results that are less understandable.

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