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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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