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XANBAD™ [eXplAinable
Neural networks for Network Behavior Anomaly
Detection]: malicious traffic is common in today’s Internet. Intrusion
Detection Systems (IDSs) provide a means to detect
patterns of bytes in packets that are certainly or probably associated with
malicious activity. This is essentially a pattern recognition task where an IDS analyzes incoming data while attempting to detect
known patterns (signatures) that indicate the presence of a known intruder.
Current Intrusion Detection Systems (IDS) performance may become a bottleneck
at high bandwidth. There is, therefore, a need for a method and circuitry to
form an IDS that is able to detect intrusions, identify
a variety of attacks, and run at the real-time speed of the high performance
network. |
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©2024_Luca_Marchese_All_Rights_Reserved Aerospace_&_Defence_Machine_Learning_Company VAT:_IT0267070992 NATO_CAGE_CODE:_AK845 Email:_luca.marchese@synaptics.org |
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