版权说明 操作指南
首页 > 成果 > 详情

A New Tensor Summary Statistic for Real-Time Detection of Stealthy Anomaly in Avatar Interaction

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Zeng, Jiuzhen;Yang, Laurence t.;Wang, Chao;Su, Junjie;Deng, Xianjun
通讯作者:
Yang, LT
作者机构:
[Zeng, Jiuzhen; Deng, Xianjun] Huazhong Univ Sci & Technol, Hubei Engn Res Ctr Big Data Secur, Sch Cyber Sci & Engn, Hubei Key Lab Distributed Syst Secur, Wuhan, Peoples R China.
[Yang, Laurence t.] Huazhong Univ Sci & Technol, Sch Cyber Sci & Engn, Wuhan, Peoples R China.
[Yang, Laurence t.] Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou, Peoples R China.
[Yang, Laurence t.] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS, Canada.
[Wang, Chao] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
通讯机构:
[Yang, LT ] H
Huazhong Univ Sci & Technol, Sch Cyber Sci & Engn, Wuhan, Peoples R China.
Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou, Peoples R China.
St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS, Canada.
语种:
英文
关键词:
Stealthy anomalysummary statistictensoravatar interactionsecurity
期刊:
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
ISSN:
1551-6857
年:
2025
卷:
21
期:
2
页码:
1-23
基金类别:
National Key R&D Program of China [2022YFE0138600]
机构署名:
本校为其他机构
院系归属:
电气工程学院
摘要:
Avatar is one of the most intuitive central components in Metaverse and faces serious security problems, particularly during the interaction with each other. In this article, we consider the problem of timely detecting the stealthy anomaly in the avatar interaction, which is crucial for security and privacy in Metaverse. With this goal, a new tensor summary statistic is proposed first to well depict the statistical discrepancy between normal and anomalous interaction volume samples, even when anomalies are stealthy. The proposed tensor summary statistic is established from the tensor linear re...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com