Existing certificateless proxy signature schemes based on classical number theory problem assumptions cannot resist to quantum computer attacks， and when these schemes are applied to systems with a large number of users， there are limitations such as single point of failure and low scalability. Aiming at these problems， a lattice-based hierarchical certificateless proxy signature scheme was proposed. Firstly， the rejection sampling technology and trapdoor-free technology were used to improve the computational efficiency of key generation. Secondly， the mutual authentication was performed by the original signers and proxy signers at different levels by exchanging randomly selected matrices， and then the proxy authorization was realized. Finally， the security of this scheme was proved under the of the Small Integer Solution （SIS） hard problem assumption in the random oracle model. Compared with the existing proxy signature schemes， the proposed scheme allows signers coming from different levels and belonging to different Key Generation Centers （KGCs）. The performance evaluation experimental results show that in the proposed scheme， the public key size is a constant， the overhead of proxy signature and verification is independent of the level， and the proxy key size and the signature size are not hierarchical linear quantities， so that this scheme can better meet the needs of large-scale distributed heterogeneous networks for load balancing， and is efficient and feasible.

For the intelligent dialogue system of customer service robots in power supply business halls, a large-scale dataset of power business user intents was constructed. The dataset includes 9 577 user queries and their labeling categories. First, the real voice data collected from the power supply business halls were cleaned, processed and filtered. In order to enable the data to drive the study of deep learning models related to intent classification, the data were labeled and augmented with high quality by the professionals according to the background knowledge of power business. In the labeling process, 35 types of service category labels were defined according to power business. In order to test the practicability and effectiveness of the proposed dataset, several classical models of intent classification were used for experiments, and the obtained intent classification models were put in the dialogue system. The classical Text classification model-Recurrent Convolutional Neural Network (Text-RCNN) was able to achieve 87.1% accuracy on this dataset. Experimental results show that the proposed dataset can effectively drive the research on power business related dialogue systems and improve user satisfaction.

As the civil aviation develops, organization rebuilding and task reassigning will be repeating in a long period. Workflow technology provides separation of the business procedure logic and its IT operational support, enabling subsequent changes to be incorporated into the procedural rules defining the business process. Therefore, workflow technology is applied in civil airport ELV (Electronic Low Voltage) information system based on middleware service layer, to avoid unnecessary overlapping development of computer management and control system. Firstly, the construction of ELV system is was analyzed and content of workflow modeling is was introduced. Secondly, three kinds of ELV system architecture based on workflow technology are were discussed. Finally, the realization of distributed prototype system taking on main control workflow engine is was described.