Titlebook: Machine Learning for Cyber Security; 4th International Co Yuan Xu,Hongyang Yan,Jin Li Conference proceedings 2023 The Editor(s) (if applica

施魔法

Phenothiazines

,Federated Community Detection in Social Networks,akage remains an area of ongoing and indispensable focus. Therefore, anonymization and differential privacy based community detection methods are proposed to protect the privacy of social network information. However, the above methods cause inevitable accuracy loss in some way, resulting in the low

水槽

Overthrow

TATE

,Extracting Random Secret Key Scheme for One-Time Pad Under Intelligent Connected Vehicle,d through Bluetooth, WiFi or OBD interfaces, so that attackers can remotely attack vehicles through these channels. Hence we create one-time pads to protect the in-vehicle network. Intelligent connected vehicle (ICV) is an information physical system, thus finding a suitable entropy source from its

Comprise

Occupation

,Bipolar Picture Fuzzy Graph Based Multiple Attribute Decision Making Approach–Part I,o learn the correlation between different attributes, and the graph model is an appropriate tool to analyze it. In this work, the MADM problem is formulated in the bipolar picture fuzzy graph framework, and decision making algorithms are designed to characterize the relationships among attributes. T

Etymology

,Priv-IDS: A Privacy Protection and Intrusion Detection Framework for In-Vehicle Network,hicles, integrated with modern communication and network technology, to achieve intelligent information exchange and sharing. As an international standardized communication protocol, controller area network (CAN) plays an important role in vehicle communication. However, due to the CAN is plaintext

Chagrin

FACT

An Unsupervised Surface Anomaly Detection Method Based on Attention and ASPP,eam anomaly detection models suffer from low detection accuracy and poor generalization performance. Therefore, this paper designs an unsupervised surface anomaly detection model based on attention and atrous spatial pyramid pooling. The proposed model learns anomaly images and their normal reconstr