Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection
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Tian et al. (2020) proposed an insider threat detection method integrating neural networks with Dempster-Shafer theory, using Attention-LSTM, resulting in 95.47% accuracy that outperforms six standard baseline anomaly detection techniques.
“Tian et al. (2020) [55] proposed an insider threat detection method that integrates neural networks with Dempster-Shafer theory, using Attention-LSTM for multichannel processing to separate attack traffic from normal data, resulting in a 95.47% accuracy that outperforms six standard baseline anomaly detection techniques.”
From A systematic review on insider threat detection using natural language processing (2025) · cites this paper as [55]
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- Authors
- Tian, Z., Shi, W., Tan, Z., Qiu, J., Sun, Y., Jiang, F., & Liu, Y.
- Affiliations
- Guangzhou University (CN)
- Carleton University (CA)
- Edinburgh Napier University (GB)
- Harbin Institute of Technology (CN)
- Hebei University of Science and Technology (CN)
- Corresponding author
- Tian, Zhihong
- Shi, Wei
- Tan, Zhiyuan
- Qiu, Jing
- Sun, Yanbin
- Jiang, Feng
- Liu, Yan
- Venue
- Mobile Networks and Applications
- Published
- 2020-10-09
- Volume
- 29
- Issue
- 5
- Pages
- 1680-1689
- ISSN
- 1383-469X (ISSN-L)
- 1572-8153
- OpenAlex
- W3092238202
- Cited by
- 24
- References
- 51
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 3 · 2023: 5 · 2022: 2 · 2021: 5
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Mobile Networks and Applications (publishedVersion)
- Edinburgh Napier Research Repository (Edinburgh Napier University) (submittedVersion, cc-by)
- Edinburgh Napier Research Repository (Edinburgh Napier University) (submittedVersion, other-oa)
- Funders
- National Natural Science Foundation of China (61871140)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- insider threat detection, Dempster-Shafer theory, deep learning, long short-term memory, multi-head attention, anomaly detection, network behavior analysis, evidence combination, CERT insider threat dataset, real-time detection
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