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Faced with the packet data under unknown protocol, it brought problems in the process of packet extraction and protocol identification for the traditional pattern matching method, for the reason that it couldn’t obtain the relevant characteristics through protocol specification. A method for the extraction of datagram fingerprint characteristics was proposed based on data mining theory. In the process of characteristic sequence mining, it introduced the self-adaptive weights to get the verdict after the weighted statistics of sequence model from the original data. And it used Up-rate to verify the association rules between the characteristic sequence. Then fingerprint characteristics was exported. Finally, ARP broadcast frames and ICMP packets were used as raw data, and the fingerprint characteristics were extracted. Experiment results show that, the self-adaptive weights could reduce the interference of redundant data segments, improve the accuracy of the extraction of fingerprint characteristics, and have some robustness to the packet length change.