Abstract: Systems and methods for managing cybersecurity for an entity are disclosed. An example method includes providing a content portal to a user configured to display a security risk profile via a generated GUI; receiving, via the generated GUI, a first input from the user comprising a selection of a component identified in the security risk profile and a response parameter; providing, via the generated GUI, parameters for a targeted scan of the selected component; receiving, via the generated GUI, a second input from the user comprising a selection of a confirmation of the parameters; identifying a vulnerability associated with a first property or a second property from device connectivity data based on the parameters; initiating the targeted scan of the selected component associated with the vulnerability; determining a result of the targeted scan; updating the security risk profile; and updating a multi-dimensional score based on the updated security risk profile.

Abstract: Systems, methods, and computer-readable storage media are utilized to analyze multi-channel data based on a security model in a computer network environment. One system includes a plurality of data channels configured to access entity data and a processing circuit communicatively coupled to a data channel of the plurality of data channels, the processing circuit configured to identify at least one vulnerability, determine an impact of the at least one vulnerability, assign the first property to a first cybersecurity dimension, generate a cybersecurity risk score based at least on the impact of the at least one vulnerability, and generate a multi-dimensional score for a target computer network environment based on the cybersecurity risk score.

Abstract: In an example embodiment, a solution is provided that allows for intelligent demand-driven data replication. Only the data that is needed has to be replicated, and this data can be kept only as long as needed. This allows cloud-based applications to be built that integrate deeper with the existing customer landscape with the most efficient data footprint. It allows data types that could not be used before to be integrated into an application. There are additional savings due to the reduced data footprint in the database, compared to a full data replication, without giving up resilience or response time.

Abstract: In an example embodiment, a solution is provided that allows for intelligent demand-driven data replication. Only the data that is needed has to be replicated, and this data can be kept only as long as needed. This allows cloud-based applications to be built that integrate deeper with the existing customer landscape with the most efficient data footprint. It allows data types that could not be used before to be integrated into an application. There are additional savings due to the reduced data footprint in the database, compared to a full data replication, without giving up resilience or response time.

Abstract: A method of implementing verification of a complex workflow includes partitioning the workflow into modules, wherein the modules have inputs, processing steps and outputs; selecting, from the workflow, one of the partitioned modules for independent verification by challenge thereof; running, with a computing device, a challenge of the selected module, the challenge comprising comparing reference outputs to outputs of the selected module, wherein reference inputs are received by the selected module and the reference outputs are generated using the reference inputs and one of an ideal performing module or a well-established module; determining whether outputs of the selected module meet verification criteria with respect to the reference outputs, and based on the determining, implementing one of: declaring the selected module verified; subdividing the selected module into smaller modules and repeating the challenge on the smaller modules; or declaring the selected module not verified.

Abstract: A method of implementing verification of a complex workflow includes partitioning the workflow into modules, wherein the modules have inputs, processing steps and outputs; selecting, from the workflow, one of the partitioned modules for independent verification by challenge thereof; running, with a computing device, a challenge of the selected module, the challenge comprising comparing reference outputs to outputs of the selected module, wherein reference inputs are received by the selected module and the reference outputs are generated using the reference inputs and one of an ideal performing module or a well-established module; determining whether outputs of the selected module meet verification criteria with respect to the reference outputs, and based on the determining, implementing one of: declaring the selected module verified; subdividing the selected module into smaller modules and repeating the challenge on the smaller modules; or declaring the selected module not verified.