The experiment shows that our filtering technique recognizes 15% of names in our dataset as malicious.
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This paper proves that some ICN configuration prevents information leakages via Data packets and shows that it is an open problem to prevent interest packets ...
Dive into the research topics of 'Name anomaly detection for ICN'. Together they form a unique fingerprint. Sort by; Weight · Alphabetically. Engineering ...
The Machine Learning page displays a list of devices that are currently using machine learning for anomaly detection, as well as devices for which you can ...
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On the Devices page ( ), click the Device Name for the device on which you want to enable anomaly detection. · On the Machine Learning tab, click the Add ML ...
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It is proved that some ICN configuration prevents information leakages via Data packets and it is shown that it is an open problem to prevent interest ...
In [22] , a simple filter technique based on web URL statistics for firewalls is proposed to detect anomalous information-centric IoV names. The authors in [23] ...
ML-based anomaly detection relies on powerful algorithms that automatically learn normal patterns in large, high-dimensional data sets and use this information ...
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Anomaly detection is examining specific data points and detecting rare occurrences that seem suspicious because they're different from the established ...
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Jun 10, 2024 · Anomaly detection is the process of analyzing company data to find data points that don't align with a company's standard data pattern.
Missing: Name ICN.