Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask

Author:

Xiao Jingyu1ORCID,Xu Zhiyao2ORCID,Zou Qingsong3ORCID,Li Qing4ORCID,Zhao Dan5ORCID,Fang Dong6ORCID,Li Ruoyu7ORCID,Tang Wenxin7ORCID,Li Kang7ORCID,Zuo Xudong7ORCID,Hu Penghui8ORCID,Jiang Yong3ORCID,Weng Zixuan9ORCID,Lyu Michael R.10ORCID

Affiliation:

1. Peng Cheng Laboratory & Tsinghua Shenzhen International Graduate School, Shenzhen, China

2. Xi'an University of Electronic Science and Technology, Xi'an, China

3. Tsinghua Shenzhen International Graduate School & Peng Cheng Laboratory, Shenzhen, China

4. Peng Cheng Laboratory, Shenzhen, China

5. Peng Cheng Laborotary, Shenzhen, China

6. Tencent, Shenzhen, China

7. Tsinghua Shenzhen International Graduate School, Shenzhen, China

8. Tsinghua University, Beijing, China

9. Beijing Jiaotong University, Beijing, China

10. The Chinese University of Hong Kong, Hong Kong, China

Funder

Major Key Project of PCL

National Key Research and Development Program of China

Shenzhen Key Lab of Software Defined Networking

Publisher

ACM

Reference38 articles.

1. An ML Behavior-Based Security Control for Smart Home Systems

2. Jiawang Bai Kuofeng Gao Shaobo Min Shu-Tao Xia Zhifeng Li and Wei Liu. 2024. BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP. In CVPR.

3. Z. Berkay Celik, Leonardo Babun, Amit Kumar Sikder, Hidayet Aksu, Gang Tan, Patrick D. McDaniel, and A. Selcuk Uluagac. 2018. Sensitive Information Tracking in Commodity IoT. In 27th USENIX Security Symposium, USENIX Security 2018, Baltimore, MD, USA, August 15-17, 2018, William Enck and Adrienne Porter Felt (Eds.). USENIX Association, 1687--1704. https://www.usenix.org/conference/usenixsecurity18/presentation/celik

4. Behavior sequence transformer for e-commerce recommendation in Alibaba

5. Zhaomin Chen, Chai Kiat Yeo, Bu Sung Lee, and Chiew Tong Lau. 2018. Autoencoder-based network anomaly detection. In 2018 Wireless telecommunications symposium (WTS). IEEE, 1--5.

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