Abstract: A privacy protection component can automatically comply with a set of privacy requirements when displaying input data. An ingestion module collects input data describing network activity executed by a network entity. A clustering module identifies data fields with data values within the input data as data identifiable to the network entity using machine-learning models trained on known data fields and their data. The clustering module also clusters the data values with other data values having similar characteristics using machine-learning models to infer a privacy level associated with each data field. The privacy level is utilized to indicate whether a data value in that data field should be anonymized. A permission module determines a privacy status of that data field by comparing the privacy level from the clustering module to a permission threshold. An aliasing module applies an alias transform to the data value of that data field with a privacy alias to anonymize that data value in that data field.

Abstract: The network reachability module maps and dynamically tracks network reachability of network addresses and/or devices. The network reachability module can map and dynamically track network reachability of a response-orchestrator engine, via communicating and cooperating with the response-orchestrator engine. The network reachability module has a tracking module to 1) monitor network traffic and 2) keep a list of known devices and/or known subnets on the network, which is dynamically tracked and updated as previously unknown devices and subnets on the network are detected. A trigger module generates a spoofed transmission and/or response communication, supported by a network protocol used by the network. The spoofed transmission and/or response communication can be used to map network reachability of i) network devices, ii) network addresses, and iii) any combination of both, which either 1) can receive or 2) cannot receive protocol communications from a host for the network reachability module in the network.

Abstract: An expert interface component can automatically connect a system user with a system support expert. A user interface module can present a threat-tracking graphical user interface and a query interface component integrated into the threat-tracking graphical user interface to a system user belonging to a client team to review a potential cyber threat and receive a query for assistance. The query interface component can allow the system user to digitally grab a visual data container displaying information and containing a data object. The query interface component can collect the visual data container from the threat-tracking graphical user interface into a collection window of the query interface component. A communication module provides an incident ticket containing the query and the visual data container to a system support expert at a remote platform.

Abstract: An analyzer module forms a hypothesis on what are a possible set of cyber threats that could include the identified abnormal behavior and/or suspicious activity with AI models trained with machine learning on possible cyber threats. The Analyzer analyzes a collection of system data, including metric data, to support or refute each of the possible cyber threat hypotheses that could include the identified abnormal behavior and/or suspicious activity data with the AI models. A formatting and ranking module outputs supported possible cyber threat hypotheses into a formalized report that is presented in 1) printable report, 2) presented digitally on a user interface, or 3) both.

Abstract: The appliance extension is designed and constructed to be a secure extension of the threat visualizer user interface of the cyber security appliance installed in the system with a limited set of functions including monitoring, investigating, and taking actions to counter the detected cyber threat, all of which an operator can securely take from the appliance extension; rather than, needing to log into the cyber security appliance and investigate potential cyber threats at a location where the cyber security appliance is installed in the system.