Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for dynamic network classification using authenticated neighbor detection. An example includes a network comparator to determine whether a network to be connected by a computing device is a managed network based on network configuration information associated with the network, in response to determining the network is not a managed network, a neighbor comparator to determine a number of different computing devices on the network that are managed computing devices, and in response to determining that the number of the managed computing devices satisfies a threshold, a sensor controller to invoke a sensor of the computing device to obtain data from computing devices associated with the network, the computing devices including the managed computing devices.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for dynamic network classification using authenticated neighbor detection. An example includes a network comparator to determine whether a network to be connected by a computing device is a managed network based on network configuration information associated with the network, in response to determining the network is not a managed network, a neighbor comparator to determine a number of different computing devices on the network that are managed computing devices, and in response to determining that the number of the managed computing devices satisfies a threshold, a sensor controller to invoke a sensor of the computing device to obtain data from computing devices associated with the network, the computing devices including the managed computing devices.

Abstract: There is disclosed in one example a computer-implemented anti-ransomware method, including: selecting a file for inspection; assigning the file to a type class according to a file type identifier; receiving an expected byte correlation for the type class; computing, according to a byte distribution of the file, a byte correlation for the file; comparing, via statistical analysis, the byte correlation to the expected byte correlation; and determining that the file has been compromised, including determining that the file has a byte correlation that deviates from the expected byte correlation by more than a threshold, taking a ransomware remediation action for the file.

Abstract: Particular embodiments described herein provide for a system that can be configured to communicate chat session data during a chat session to a first display of a first electronic device, communicate the chat session data during the chat session to a second display of a second electronic device, receive sensitive data during the chat session from the first electronic device, and protect the sensitive data from being displayed on the second display during the chat session without breaking continuity of the chat session.

Abstract: Particular embodiments described herein provide for a system that can be configured to communicate chat session data during a chat session to a first display of a first electronic device, communicate the chat session data during the chat session to a second display of a second electronic device, receive sensitive data during the chat session from the first electronic device, and protect the sensitive data from being displayed on the second display during the chat session without breaking continuity of the chat session.

Abstract: There is disclosed in one example a ransomware mitigation engine, including: a processor; a convolutional neural network configured to provide file type identification (FTI) services including: identifying an access operation of a file as a write to the file or newly creating the file; computing a byte correlation factor for the file; classifying the file as belonging to a file type; determining with a screening confidence that the file type is correct for the file; determining that the screening confidence is below a screening confidence threshold; and circuitry and logic to provide heuristic analysis including: receiving notification that the confidence is below the confidence threshold; performing a statistical analysis of the file to determine a difference between an expected value and a computed value; determining from the difference, with a detection confidence, that the file has been compromised; and identifying the file as having been compromised by a ransomware attack.

Abstract: A patient support includes a cover defining an interior region, an air permeable first layer located in the interior region, and a support layer located beneath the air permeable first layer. A pressure sensing layer is located underneath the support layer. At least one air supply is coupled to the support layer. A controller is coupled to the air supply and to the pressure sensing layer. The controller controls inflation and deflation of the support layer in response to a signal from the pressure sensing layer.

Abstract: A steganographic coding detector (and method) analyzes one or more pages of a file. For each page containing text strings, the detector counts a number of A0h and 20h characters for the text string. For each text string for which the number of A0h characters is greater than a first threshold, the detector sets a flag to a first state, The first threshold is computed based on the number of 20h characters in that text string. For each text string for which the number of 20h characters is less than the first threshold, the detector sets the flag to a second state. Responsive to the number of text strings that have a flag at the first state being greater than a second threshold, the detector marks the file as being steganographically encoded.

Abstract: There is disclosed in one example a ransomware mitigation engine, including: a processor; a convolutional neural network configured to provide file type identification (FTI) services including: identifying an access operation of a file as a write to the file or newly creating the file; computing a byte correlation factor for the file; classifying the file as belonging to a file type; determining with a screening confidence that the file type is correct for the file; determining that the screening confidence is below a screening confidence threshold; and circuitry and logic to provide heuristic analysis including: receiving notification that the confidence is below the confidence threshold; performing a statistical analysis of the file to determine a difference between an expected value and a computed value; determining from the difference, with a detection confidence, that the file has been compromised; and identifying the file as having been compromised by a ransomware attack.

Abstract: This disclosure describes certain exemplary embodiments of a patient support having a plurality of vertically-oriented on substantially can-shaped inflatable bladders. In one embodiment, the patient support includes a support layer positioned above the vertical bladders. In another embodiment, the patient support includes a high air loss device. In still another embodiment, the patient support includes a pneumatic device located within the patient support.

Abstract: A steganographic coding detector (and method) analyzes one or more pages of a file. For each page containing text strings, the detector counts a number of A0h and 20h characters for the text string. For each text string for which the number of A0h characters is greater than a first threshold, the detector sets a flag to a first state, The first threshold is computed based on the number of 20h characters in that text string. For each text string for which the number of 20h characters is less than the first threshold, the detector sets the flag to a second state. Responsive to the number of text strings that have a flag at the first state being greater than a second threshold, the detector marks the file as being steganographically encoded.

Abstract: Particular embodiments described herein provide for a system that can be configured to communicate chat session data during a chat session to a first display of a first electronic device, communicate the chat session data during the chat session to a second display of a second electronic device, receive sensitive data during the chat session from the first electronic device, and protect the sensitive data from being displayed on the second display during the chat session without breaking continuity of the chat session.

Abstract: This disclosure describes systems, methods, and computer-readable media related to an incident response tool using data exchange layer. In some embodiments, a data collector may be generated by an incident response server. The incident response server may transmit a data collector to multiple broker servers, where each broker server may transmit the data collector to multiple user devices associated with the broker server. The incident response server may receive data from the data collectors executing on the user devices and may analyze the received data.

Abstract: This disclosure describes systems, methods, and computer-readable media related to an incident response tool using data exchange layer. In some embodiments, a data collector may be generated by an incident response server. The incident response server may transmit a data collector to multiple broker servers, where each broker server may transmit the data collector to multiple user devices associated with the broker server. The incident response server may receive data from the data collectors executing on the user devices and may analyze the received data.