Acronis International had one patents in internet of things during Q2 2024. Acronis International GmbH has developed systems and methods for detecting vulnerabilities in devices within a network by intercepting packets, extracting device behavior features, using machine learning to identify device types, conducting security scans specific to device types, and generating vulnerability assessment reports when vulnerabilities are detected. GlobalData’s report on Acronis International gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Acronis International had no grants in internet of things as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for detecting vulnerablities in internet-of-things (IOT) devices (Patent ID: US20240205257A1)
The patent by Acronis International GmbH discloses systems and methods for detecting vulnerabilities in devices within a network. The method involves intercepting network packets, identifying packets corresponding to a specific device, extracting features from these packets, using machine learning to determine the device type, conducting a security scan tailored to the device type, and generating a vulnerability assessment report if a vulnerability is detected. Different security scans can be performed for different device types, and a zero-shot learning framework is utilized by the machine learning algorithm. The system includes a hardware processor configured to execute these steps, with the ability to perform remediation actions to resolve detected vulnerabilities.
Furthermore, the patent describes a method for detecting vulnerabilities in devices within a network, involving the extraction and embedding of features from network packets, execution of a machine learning algorithm to determine device types, and conducting security scans specific to each device type. The system can identify different subsets of packets for different devices, determine prediction probabilities for accuracy, and utilize sequence-based or aggregation-based features for analysis. Attributes in the training dataset describe device types, network parameters, and device relationships. The system can generate vulnerability assessment reports and perform remediation actions to address detected vulnerabilities, enhancing network security and threat detection capabilities.
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