Methods and systems using an AI co-processor to detect anomalies caused by malware in storage devices

Abstract

Computer implemented systems and methods for performing electromotive force analysis of a storage device that include a storage device, an Artificial Intelligence Co-processor (AI-Coprocessor) chipset, a thin coil inductor positioned in proximity to a portion of the surface of the storage device for capturing data from electro motive radia generated by the storage device, an analog-to-digital-converter, and at least one probe for communicating the captured data to an analog-to-digital converter. The data is captured by the thin coil inductor and communicated to the analog-to-digital-converter via the at least one probe and the analog-to-digital-converter digitizes the voltage level of the captured data and communicates the results of the digitization and amplification to the Ai-Coprocessor. The Ai-Coprocessor chipset performs analysis of the data to detect any anomalies in the operation of the storage device and outputs those result for further processing. Embodiments include the use of an NVM Express protocol or an AHCI controller engine so it can detect in real time any hardware threats or attacks such as side channel attack, power glitch and any other hardware changes. Embodiments can detect malicious activities such as ransomware, virus and malware, or non-malicious activities by measuring the electromotive force energy caused by anomalous activities.

Dependencies are inferred from the claim text.