Mellanox Technologies, Ltd.

Medasense Biometrics Ltd.

Shauli Arazi

Bartley Richardson

Chen Rozenbaum

Aviem Amossi

Avi Kayton

Apparatuses, systems, and techniques for detecting that a host device is subject to a malicious network attack using a machine learning (ML) detection system are described. A computing system includes a graphics processing unit (GPU) and an integrated circuit with a network interface, and a hardware acceleration engine. The integrated circuit hosts a hardware-accelerated security service to extract features from network data and metadata from the hardware acceleration engine and sends the extracted features to the GPU. Using the ML detection system, the GPU determines whether the host device is subject to a malicious network attack using the extracted features. The GPU can send an enforcement rule to the integrated circuit responsive to a determination that the host device is subject to the malicious network activity.

Accelerated data movement between data processing unit (DPU) and graphics processing unit (GPU) to address real-time cybersecurity requirements

Disclosed is a system for monitoring physiological parameters during a medical interventional procedure involving high intensity/energy radiofrequency electrical currents/voltages applied through a body of a subject, the system including an electrode-based sensor, configured to close an electrical conduction path passing through a body of a subject, and one or more non-electrode-based sensors, a plurality of electrical lines, a monitor, and a filter array including EMI filters mounted at specific locations and characterized by a frequency response curve having a magnitude of an attenuation in a first frequency range (typical of operating frequencies of high intensity/energy radiofrequency medical interventional equipment), which is greater than a magnitude of an attenuation in a second frequency range (typical of the sampling frequencies of the electrode-based sensor and the one or more non-electrode-based sensors), the system being thereby configured for suppressing noise induced by the medical interventional equipment.

Growing community of inventors

Tel Aviv, Israel

Shauli Arazi