To improve the network experience in a network, a unique device identifier (UDID) can be generated by a UDID generation module of a client device. The UDID generation module utilizes one or more device parameters as well as a service set identifier (SSID) as input(s) to the UDID generation module. The UDID can be reported to an access point device of the network so that the access point device can track, monitor, control, etc. the client device within the network, for example, when media access control randomization (rMAC) is utilized by the network to protect the privacy of the client device or a user of the client device. The same UDID is generated each time the client device joins the network so that the client device need not store the UDID.

A privacy management system that is configured to process one or more data subject access requests and further configured to: (1) enable a data protection officer to submit an audit request; (2) perform an audit based on one or more parameters provided as part of the request (e.g., one or more parameters such as how long an average request takes to fulfill, one or more parameters related to logging and/or tracking data subject access requests and/or complaints from one or more particular customer advocacy groups, individuals, NGOs, etc.); and (3) provide one or more audit results to the officer (e.g., by displaying the results on a suitable display screen).

System and method are disclosed for preserving privacy of shared data over a shared network. A vector encoder transforms received data into a feature vector. An autoencoder includes a neural network-based encoder transforms the feature vector into a fixed size latent space representation of the received data. A neural network-based decoder of the autoencoder is configured to reconstruct the feature vector from the latent space representation. The autoencoder is trained using training data with an objective to minimize reconstruction error. A vector decoder transforms the reconstructed feature vector into reconstructed data. The latent space representation of data from the trained autoencoder is shared as anonymized data with at least one trusted party over the shared network, decoded offline using a replica of the trained decoder.

Techniques are provided for community threat intelligence for operational technology networks. For a plurality of OT networks, at least one monitoring device processes OT network traffic and collects telemetry data, and a telemetry sanitization system applies a sanitization process to the telemetry data to generate sanitized telemetry data that does not include sensitive data. A computer system receives sanitized telemetry data from the telemetry sanitization systems provided for the plurality of OT networks, maintains threat intelligence data generated based on the sanitized telemetry data, and provides access to at least one of the threat intelligence data and the sanitized telemetry data to a plurality of users.

An asset information collection apparatus includes: a first reception part configured to cause a plurality of first servers to anonymize a plurality of items of asset information and to generate a plurality of items of anonymous asset information such that a specific individual cannot be identified based on the items of asset information when the items of asset information stored in the first servers are viewed by one or more user terminals, and configured to receive the items of anonymous asset information from the first servers; a second reception part configured to be for one or more users using the one or more user terminals and to receive one or more identifiers that is not capable of identifying a specific individual from the first servers; and a storage part configured to store the items of anonymous asset information in association with the one or more identifiers.

Methods, systems, and computer readable media for hiding network function (NF) instance identifiers (IDs) in communications networks are disclosed. One method for hiding NF instance IDs in a communications network occurs at an NF repository function (NRF) comprising at least one processor. The method comprises: receiving, from a first NF, an NF registration request message for registering a first NF instance of the first NF, wherein the NF registration request message includes a first NF instance ID for identifying the first NF instance; storing, in a data store, a mapping between the first NF instance ID and at least one pseudo NF instance ID, wherein the data store includes mappings between NF instance IDs and related pseudo NF instance IDs; and generating and sending, to the first NF, an NF registration response message including the at least one pseudo NF instance ID for identifying the first NF instance.

A sender device can determine that data associated with an application is to be sent to a service via a network. The sender device can generate resource queries directed to at least two participant devices and receive responses indicating whether each of the participant devices has a resource available to host a virtual network function (“VNF”). The sender device can generate commands directed to security interface applications executed by the participant devices. The commands can instruct the participant devices to instantiate the VNFs. The sender device can partition the data into data partitions directed to the participant devices. The sender device can send the data partitions to the VNFs of the participant devices. The VNFs can forward the data partitions to a network access device that can combine the data partitions and send the data to the service via the network.

A method for local data storage governance may include: authenticating, by a privacy service computer program, a user accessing the privacy service using a privacy application; receiving, by the privacy service computer program and from a proxy service, user activity data; saving, by the privacy service computer program, the user activity data to a privacy database; receiving, by the privacy service computer program and from the privacy application, a request for the user activity data; retrieving, by the privacy service computer program and from the privacy database, the user activity data; communicating, by the privacy service computer program, the user activity data to the privacy application, wherein the privacy application stores the user activity data in local storage; receiving, by the privacy service computer program, an acknowledgement of the user activity data; and purging, by the privacy service computer program, the user activity data from the privacy database.

Technology for a device operable for secured user access is described. The technology can comprise one or more processors. The device can be configured to identify an intruder indicator, wherein the intruder indicator can indicate that an intruder has been detected in a proximity of either the local device or a remote device in communication with the local device. The device can be configured to activate one or more privacy filters at the local device. The device can be configured to encode data based on the one or more privacy filters.

Aspects of the disclosure relate to information masking. A computing platform may receive, from a user computing device, a request to access information that includes personal identifiable information (PII). The computing platform may retrieve source data comprising the PII and mask, within the source data and based on a data management policy, the PII. The computing platform may send the masked information in response to the request to access the information. The computing platform may receive a request to unmask the masked information and unmask the PII. The computing platform may log the request to unmask the masked information in an unmasking event log and send the unmasked PII in response to the request to unmask the masked information. The computing platform may apply a machine learning model to the unmasking event log to identify malicious events and trigger remediation actions based on identification of the malicious events.