In the existing French Named Entity Recognition (NER) research, the machine learning models mostly use the character morphological features of words, and the multilingual generic named entity models use the semantic features represented by word embedding, both without taking into account the semantic, character morphological and grammatical features comprehensively. Aiming at this shortcoming, a deep neural network based model CGC-fr was designed to recognize French named entity. Firstly, word embedding, character embedding and grammar feature vector were extracted from the text. Then, character feature was extracted from the character embedding sequence of words by using Convolution Neural Network (CNN). Finally, Bi-directional Gated Recurrent Unit Network (BiGRU) and Conditional Random Field (CRF) were used to label named entities in French text according to word embedding, character feature and grammar feature vector. In the experiments, F1 value of CGC-fr model can reach 82.16% in the test set, which is 5.67 percentage points, 1.79 percentage points and 1.06 percentage points higher than that of NERC-fr, LSTM(Long Short-Term Memory network)-CRF and Char attention models respectively. The experimental results show that CGC-fr model with three features is more advantageous than the others.

In cloud environment, the code of pivotal business in Virtual Machine (VM) can be modified by malicious software in many ways, which can pose a threat to its stable operation. Traditional measurement systems based on host are liable to be bypassed or attacked. To solve the problem that it is difficult to obtain a complete virtual machine running process code and verify its integrity at Virtual Machine Monitor (VMM) layer, a paging-measurement method based on hardware virtualization was proposed. The Kernel-based Virtual Machine (KVM) was used as the VMM to capture the system calls of virtual machine process in VMM and regarde it as the trigger point of the measurement process; the semantic differences of different virtual machine versions were solved by using relative address offset, then the paging-measurement method could verify the code integrity of running process in virtual machine transparently at VMM layer. The implemented prototype system of VMPMS (Virtual Machine Paging-Measurement System) can effectively measure the virtual machine process code with acceptable performance loss.