Abstract: Since GANs(Generative Adversarial Networks) has been put forward,it has been widely used in various fields,and its application in the field of information security is getting more and more deeply.However,using GANs to realize secure communication under public key cryptosystem has not been reported publicly.Therefore,in view of the adversarial nature of both communication sides and their adversary,this paper proposes an adversarial learning mechanism of GANs.In the public key cryptosystems scenarios,the key generator,encryption and decryption of both communication sides,and the decipher process of adversary are regarded as neural networks,then we use the certification confidentiality to strengthen public-private key linkage.Afterwards,by using the adversarial learning mechanism to train both communication sides and their adversary,we realize the authenticable encrypted secure communication (AEC-AN) between both communication sides on the open channel.In the experiment,4 keys with lengths of 16 bit,32 bit,64 bit and 128 bit have been used for training.The experiment result shows that Bob's accuracy rate is between 91%~94%,and Eve's error rate is between 43%~57%,which is close to the probability of Eve's random guess,thus proving that the proposed mechanism of GANs achieves the secure communication between both communication sides under the environment of adversary eavesdropping.

Key words: Adversarial network, Authenticable encrypted, Public key cryptosystem, Secure communication