Abstract: A mutual authentication protocol based on radio frequency (RF) fingerprint and fuzzy extractor is provided. Two kinds of nodes in the protocol are denoted by authenticator and verifier respectively. In the registration phase, the verifier sends a registration request to the verifier, the verifier receives its RF fingerprint and uses the fuzzy extractor to process it. After storing the help string P related to the verifier, the key generated by R is returned to the verifier, and the verifier stores the key after receiving it. In the authentication phase, the verifier sends an encrypted message containing the challenge value to the verifier. After receiving it, the verifier recovers the key needed for decryption through the fuzzy extractor using the extracted RF fingerprint and the previously stored P value, and returns a reply message to the verifier to achieve the final two-way authentication effect.

Abstract: The present disclosure provides a large-scale malware classification system, comprising a client for unloading malware and a server for receiving and classifying the malware, wherein the server comprises a deep learning module for classifying the malware.

Abstract: Embodiments of the present invention provide a communication method and a communications device. The method includes: obtaining, by a first access network device, a first data block; performing network coding on the first data block to generate a plurality of first encoded data blocks; and performing, by the first access network device, offload processing on at least one first encoded data block in the plurality of first encoded data blocks. The offload processing includes: sending a part of the at least one first encoded data block to a second access network device, and directly sending, by using an air interface, another part of the at least one first encoded data block to the terminal device.

Abstract: The present disclosure provides a large-scale malware classification system, comprising a client for unloading malware and a server for receiving and classifying the malware, wherein the server comprises a deep learning module for classifying the malware.

Abstract: Embodiments of the present invention provide a communication method and a communications device. The method includes: obtaining, by a first access network device, a first data block; performing network coding on the first data block to generate a plurality of first encoded data blocks; and performing, by the first access network device, offload processing on at least one first encoded data block in the plurality of first encoded data blocks. The offload processing includes: sending a part of the at least one first encoded data block to a second access network device, and directly sending, by using an air interface, another part of the at least one first encoded data block to the terminal device.