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NODOZE: Combatting Threat Alert Fatigue with Automated Provenance Triage
Wajih Ul Hassan
, Shengjian Guo
, Ding Li
, Zhengzhang Chen
, Kangkook Jee
, Zhichun Li
,
Adam Bates
Electrical and Computer Engineering
Information Trust Institute
Siebel School of Computing and Data Science
Research output
:
Chapter in Book/Report/Conference proceeding
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Conference contribution
Overview
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Keyphrases
Triage
100%
Anomaly Score
100%
Alert Fatigue
100%
False Alarm
75%
Cyber
75%
Dependency Graph
50%
Detection Software
50%
Threat Detection
50%
Order of Magnitude
25%
Contextual Information
25%
Lower Average
25%
Runtime Overhead
25%
Graph-based
25%
Intrusion Detection System
25%
Information Overload
25%
Suspiciousness
25%
Large Enterprises
25%
Cut-off Threshold
25%
Traditional Tools
25%
Historical Information
25%
Vital Data
25%
Network Diffusion
25%
Diffusion Algorithm
25%
Causal Dependency Graph
25%
Computer Science
Dependency Graph
100%
Threat Detection
66%
Generate Alert
66%
Needed Information
33%
Contextual Information
33%
Intrusion Detection System
33%
Historical Information
33%
Suspicious Activity
33%