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- W2340964477 abstract "Abstract : Network intrusion detection systems (IDS) are powerful network defense tools that monitor network traffic in real time and generate alarms based on known signatures; however, the increasing complexity of cyber threats (e.g., advanced malware), distributed denial-of-service attacks, and session-hijacking have produced large alarm sets. Analysts may miss an alarm or a mission-critical system may become compromised due to the amount of data required for processing. This information overload often leads to unknown cyber postures, system capabilities, and ultimately mission impacts due to cyber threats. In this technical document, we propose Multistage Analysis of Cyber Threats for Quick Mission Impact Assessment (CyberIA), a multistage approach to log reduction as well as the development of framework to support IDS alarm analysis for network impact assessments. The system is composed of two phases of algorithms. The first phase utilizes a k-means clustering algorithm, and the second phase utilizes a supervised machine-learning system to minimize the clustered log sets. The final result is coupled with a network graph database to determine the impact on networked systems." @default.
- W2340964477 created "2016-06-24" @default.
- W2340964477 creator A5066256429 @default.
- W2340964477 date "2015-09-01" @default.
- W2340964477 modified "2023-10-16" @default.
- W2340964477 title "Multistage Analysis of Cyber Threats for Quick Mission Impact Assessment (CyberIA)" @default.
- W2340964477 cites W1963868908 @default.
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- W2340964477 doi "https://doi.org/10.21236/ada626130" @default.
- W2340964477 hasPublicationYear "2015" @default.
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