SeIoT: Detecting Anomalous Semantics in Smart Homes via Knowledge Graph-Reference-Cited by-同舟云学术

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SeIoT: Detecting Anomalous Semantics in Smart Homes via Knowledge Graph

Published:2024 Issue: Volume:19 Page:7005-7018
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Li Ruoyu¹^ORCID,Li Qing¹^ORCID,Huang Yucheng¹,Zou Qingsong¹^ORCID,Zhao Dan¹^ORCID,Zhang Zhengxin¹^ORCID,Jiang Yong¹^ORCID,Zhu Fa²^ORCID,Vasilakos Athanasios V.³^ORCID

Affiliation:

1. Department of Strategic and Advanced Interdisciplinary Research, Peng Cheng Laboratory, Shenzhen, China

2. College of Information Science and Technology and the College of Artificial Intelligence, Nanjing Forestry University, Nanjing, China

3. Department of Networks and Communications, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

Funder

Major Key Project of PCL

National Key Research and Development Program of China

Shenzhen Key Laboratory of Software Defined Networking

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/10206/10319981/10599285.pdf?arnumber=10599285

Reference52 articles.

1. Modeling, Critical Threshold, and Lowest-Cost Patching Strategy of Malware Propagation in Heterogeneous IoT Networks

2. SmartAuth: User-centered authorization for the Internet of Things;Tian

3. Examining Mirai's Battle over the Internet of Things

4. SoK: Security Evaluation of Home-Based IoT Deployments

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