File:BLOCKCHAIN NETWORK BEHAVIOR-BASED ANOMALY DETECTION (IA blockchainnetwor1094563492).pdf
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Summary[edit]
BLOCKCHAIN NETWORK BEHAVIOR-BASED ANOMALY DETECTION
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| Author |
Pendino, Stephanie R. |
| Title |
BLOCKCHAIN NETWORK BEHAVIOR-BASED ANOMALY DETECTION |
| Publisher |
Monterey, CA; Naval Postgraduate School |
| Description |
Blockchain technology has the potential to improve the areas of additive manufacturing, supply chain management, and many others within the Navy. An anomaly detection scheme that characterizes blockchain parameters as normal or anomalous using statistical analysis and hierarchical clustering methods was developed in this thesis. The histograms, probability distributions, and boxplots of the data were used to estimate thresholds for outliers that may indicate attacks. The thresholds obtained from dendrograms were used to form clusters and sub-clusters based on the hierarchical data structure; data point indices that do not fall within the threshold are considered anomalous and not included in the clusters. The anomaly detection scheme was implemented in the MATLAB programming environment and validated by successful anomaly detection corresponding to an attack on the public Ethereum blockchain network and in an experimental doorknob-rattling attack on a local blockchain research network. Hierarchical clustering proved to be a more powerful anomaly detection method than statistical analysis methods. Subjects: blockchain; k-means; hierarchical clustering; anomaly detection |
| Language | English |
| Publication date | September 2019 |
| Current location |
IA Collections: navalpostgraduateschoollibrary; fedlink |
| Accession number |
blockchainnetwor1094563492 |
| Source | |
| Permission (Reusing this file) |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. |
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This work is in the public domain in the United States because it is a work prepared by an officer or employee of the United States Government as part of that person’s official duties under the terms of Title 17, Chapter 1, Section 105 of the US Code.
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| This file has been identified as being free of known restrictions under copyright law, including all related and neighboring rights. | ||
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| current | 08:04, 15 July 2020 |  | 1,275 × 1,650, 72 pages (1.59 MB) | Fæ (talk | contribs) | FEDLINK - United States Federal Collection blockchainnetwor1094563492 (User talk:Fæ/IA books#Fork8) (batch 1993-2020 #10477) |
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