The invention discloses a communication data leakage detection and protection method combined with
deep learning, and belongs to the technical field of communication security, and the method specifically comprises the following steps: collecting chat records, extracting keywords and emotional tendencies by using a
natural language processing technology, inputting a
deep learning model, and training based on
annotation data, dividing work and private chat records; after a
private communication encryption instruction is obtained, a private chat
record is segmented into data blocks, hash values are generated and stored in block chain nodes, a symmetric
encryption algorithm is used for
encryption, and a secret key is customized by an employee; calculating the proportion of the two types of chat records, and starting network flow
simulation if the proportion exceeds a threshold value; monitoring an access interface in real time, judging abnormal access according to identity permission, request frequency and the like, extracting a hash value when the access is abnormal, and generating a bait
record according to the identity and returning the bait
record; and finally, the access risk is assessed through the block chain
smart contract, and if continuous
abnormality occurs, a data self-destruction program is triggered to encrypt the associated data block and terminate the connection, so that the communication
data security is ensured.