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Safety_Critical_Machine_Learning |
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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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General Synaptics Aerospace_and_Defence_Machine_Learning_Company VAT NUMBER:_IT02670700992 REA NUMBER: GE-503104 Email:_luca.marchese@synaptics.org |
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Copyright© 2026 General Synaptics |
