Jianye Yu

Title: Innovations of Jianye Yu in IoV Security

Introduction

Jianye Yu is a prominent inventor based in Nanjing, China. He has made significant contributions to the field of Internet of Vehicles (IoV) security. With a total of 2 patents, his work focuses on enhancing the safety and reliability of IoV systems.

Latest Patents

Jianye Yu's latest patents include an "IoV intrusion detection method and device based on improved convolutional neural network." This patent addresses the technical challenges of IoV security by providing a method that collects original data traffic during IoV communication. The data is then processed through a data dimension reduction algorithm to obtain standardized data for analysis. The improved convolutional neural network model performs convolutional calculations and nonlinear activation, ultimately classifying the data set through a SoftMax layer.

Another notable patent is the "Intrusion detection method and system for Internet of Vehicles based on Spark and combined deep learning." This method involves setting up a Spark distributed cluster and constructing a combined deep learning algorithm model that integrates convolutional neural networks (CNN) and long short-term memory (LSTM). The process includes initializing parameters, uploading data to a Hadoop distributed file system, and recognizing data through the CNN-LSTM model.

Career Highlights

Jianye Yu is affiliated with the Nanjing University of Science and Technology, where he continues to advance research in IoV security. His innovative approaches have positioned him as a key figure in the development of secure IoV systems.

Collaborations

He has collaborated with notable colleagues such as Yong Qi and Mingjun Liu, contributing to the advancement of technology in their field.

Conclusion

Jianye Yu's work in IoV security showcases his commitment to innovation and safety in modern transportation systems. His patents reflect a deep understanding of complex algorithms and their application in real-world scenarios.