Abstract: In order to avoid more duplicate data in the encryption process of IoT privacy data, which leads to higher computational complexity and reduces computational efficiency and security, an encryption method of IoT privacy data that combines DES(Data Encryption Standard) and ECC(Ellipse Curve Ctyptography) algorithms is proposed. Firstly, the TF-IDF(Tem Frequency-Inverse Document Frequency) algorithm is used to extract feature vectors from the privacy data of the Internet of Things. They are input into the BP(Back Proragation) neural network and are trained. The IQPSO( Improved Quantum Particle Swarm Optimization) algorithm is used to optimize the neural network and complete the removal of duplicate data from the privacy data of the Internet of Things. Secondly, the Data Encryption Standard and ECC algorithm are used to implement the primary and secondary encryption of the privacy data of the Internet of Things. Finally, a fusion of DES and ECC algorithms is adopted for digital signature encryption to achieve complete encryption of IoT privacy data. The experimental results show that the proposed algorithm has high computational efficiency, security, and reliability.

Key words: data encryption standard, ellipse curve cryptography(ECC), internet of things data encryption, term frequency-inverse document frequency ( TF-IDF ), improved quantum particle swarm optimizationI(QPSO), digital signature