Abstract: Methods, apparatus, and program products that can predict misconfigurations in a computing system using machine learning are disclosed herein. One method includes labeling one or more graph nodes or link nodes of a data graph of a computing system that includes one or more security vulnerabilities with a node label or link label, respectively, in which each node label represents the first security vulnerabilities associated with a particular graph node and each link label represents the second security vulnerabilities associated with a particular link node. The method further includes utilizing the graph node(s) or the link node(s) to train a machine learning algorithm to predict one or more misconfigurations in the computing system based on the security vulnerabilities and determining one or more modifications to the computing system for mitigating the one or more misconfigurations. Apparatus and program products that include and/or perform the methods are also disclosed herein.

Abstract: In one aspect, a first device may include at least one processor, a touch-enabled display accessible to the at least one processor, and storage accessible to the at least one processor. The storage may include instructions executable by the at least one processor to facilitate, at the first device, a telephone call with a second device. The instructions may also be executable to, during facilitation of the telephone call, present a graphical user interface (GUI) on the touch-enabled display. The GUI may include a selector that is selectable to command the first device to audibly provide, from the first device to the second device, information as part of the telephone call. The instructions may also be executable to receive user input selecting the selector and to, responsive to receipt of the user input selecting the selector, audibly provide the information to the second device as part of the telephone call.

Abstract: For secure attribute verification, a processor generates a plurality of hashes of a seed and a previous public group index. The processor further iteratively generates a public group index for each hash. The processor generates a one-time user identifier expressed as a hash chain of identifiers each based on one of the public group indexes. The processor verifies user attributes from the one-time user identifier.

Abstract: In one aspect, a first device may include at least one processor, a touch-enabled display accessible to the at least one processor, and storage accessible to the at least one processor. The storage may include instructions executable by the at least one processor to facilitate, at the first device, a telephone call with a second device. The instructions may also be executable to, during facilitation of the telephone call, present a graphical user interface (GUI) on the touch-enabled display. The GUI may include a selector that is selectable to command the first device to audibly provide, from the first device to the second device, information as part of the telephone call. The instructions may also be executable to receive user input selecting the selector and to, responsive to receipt of the user input selecting the selector, audibly provide the information to the second device as part of the telephone call.