Insider Threat Detection Using An Unsupervised Learning Method: COPOD

2021 ◽  
Author(s):  
Xiaoshuang Sun ◽  
Yu Wang ◽  
Zengkai Shi
Keyword(s):  
Unsupervised Learning ◽  
Insider Threat ◽  
Threat Detection ◽  
Learning Method

EVOLVING INSIDER THREAT DETECTION STREAM MINING PERSPECTIVE

2013 ◽  
Vol 22 (05) ◽  
pp. 1360013 ◽  
Author(s):  
PALLABI PARVEEN ◽  
NATHAN MCDANIEL ◽  
ZACKARY WEGER ◽  
JONATHAN EVANS ◽  
BHAVANI THURAISINGHAM ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Unsupervised Learning ◽  
Large Data ◽  
Insider Threat ◽  
Threat Detection ◽  
Stream Mining ◽  
Insider Threats ◽  
System Logs ◽  
The Cost ◽  
Future Work

Evidence of malicious insider activity is often buried within large data streams, such as system logs accumulated over months or years. Ensemble-based stream mining leverages multiple classification models to achieve highly accurate anomaly detection in such streams, even when the stream is unbounded, evolving, and unlabeled. This makes the approach effective for identifying insider threats who attempt to conceal their activities by varying their behaviors over time. This paper applies ensemble-based stream mining, supervised and unsupervised learning, and graph-based anomaly detection to the problem of insider threat detection. It demonstrates that the ensemble-based approach is significantly more effective than traditional single-model methods, supervised learning outperforms unsupervised learning, and increasing the cost of false negatives correlates to higher accuracy. Future work will consider a wider range of tunable parameters in an effort to further reduce false positives, include a more sophisticated polling algorithm for weighting better models, and implement parallelization to lower runtimes to more rapidly detect emerging insider threats.

A benchmark for visual analysis of insider threat detection

2021 ◽  
Vol 65 (9) ◽  
Author(s):  
Ying Zhao ◽  
Kui Yang ◽  
Siming Chen ◽  
Zhuo Zhang ◽  
Xin Huang ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Insider Threat ◽  
Threat Detection
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