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CSM Automated Confidence Score Measurement of Threat Indicators

Abstract The volume and frequency of cyber attacks have exploded in recent years. Organizations subscribe to multiple threat intelligence feeds to increase their knowledge base and better equip their security teams with the latest information in threat intelligence domain. Though such subscriptions add intelligence and can help in taking more informed decisions, organizations have to put considerable efforts in facilitating and analyzing a large number of threat indicators. This problem worsens further, due to a large number of false positives and irrelevant events detected as threat indicators by existing threat feed sources. It is often neither practical nor cost-effective to analyze every single alert considering the staggering volume of indicato... (more)
Created Date 2017
Contributor Modi, Ajay (Author) / Ahn, Gail-Joon (Advisor) / Zhao, Ziming (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Subject Computer science / Confidence Score / Graph Propagation / Threat Indicators / Threat Intelligence / Threat Score
Type Masters Thesis
Extent 91 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis