Systems and methods for automated and explainable machine learning to generate seamlessly actionable insights by generating explainable personas directly from customer relationship management systems are disclosed. The personas are defined as a collection of segments, scored by likelihood to generate good opportunities, accompanied ranked profile attribute importance, with descriptive names and summaries, associated human and database readable queries which have been generated to optimally find cluster candidates in a broader data universe. Such a system would effectively and accurately model the composition of past clients, perform the categorization in an explainable way such that actions can be taken on the information to have predictable results. What is further required are the mean to categorize small text components, trained over dependent and independent model sets, to enable a cleaner and more explicit representation of information rich short-strings, in order to facilitate a more meaningful representation of the user profiles.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and computing entities for predictive data protection using a data protection policy determination machine learning model. In one embodiment, a method is provided comprising: processing a historical data corpus using the data protection policy determination machine learning model to generate a dynamic data protection policy update describing inferred data protection instructions; determining an attestation subset of the inferred data protection instructions by comparing the instructions and prior data protection instructions described by an existing data protection policy; for each inferred data protection instruction in the attestation subset, determining a per-instruction attestation determination based on end-user feedback; generating an updated data protection policy by updating the existing policy in accordance with each inferred instruction in the attestation subset whose per-instruction attestation determination describes an affirmative attestation determination; and performing the predictive data protection using the updated data protection policy.

A data transcoding device includes a memory device for storing clear data containing private information and a processor configured as a data transcoder. The processor is configured to create packets of the clear data, prepare the packets for transcoding the clear data into an indecipherable multimedia data file appearing as noise, by determining properties of the indecipherable multimedia file based on parameters of the clear data. The processor is configured to generate the indecipherable multimedia file by transcoding the clear data based on the determined properties.

Access to data and resources in a multi-tenant computing system is managed by tagging the data and resources with attributes, as well as by tagging users with attributes. Tenant-specific access policies are configured. When an access request is received from a workload, a policy decision engine processes the attributes that are tagged to the requesting workload (e.g., user, application, etc.) as well as those tagged to the requested data or resource, given a relevant tenant-specific policy. An access decision is provided in response to the access request, and the access decision can be enforced by a tenant-specific enforcement system.

A security solution having a system, a method, or a computer program for protecting contents in a target storage device that is arranged to be removable from a storage system having a unique combination of a system complex key (SCK) and a system identification (SID). The solution includes receiving a request to remove the target storage device from the storage system, where the storage system may have a plurality of storage devices each containing the identical combination of system complex key (SCK) and system identification (SID), and receiving a system complex key password (SCKP). The solution includes comparing the system complex key password (SCKP) to the system complex key (SCK) in the storage system, determining whether the system complex key password (SCKP) matches the system complex key (SCK) in the storage system, and suspending all read or write operations to the target storage device when the system complex key password (SCKP) matches the system complex key (SCK) in the storage system.

This disclosure relates to a data storage device. A data port transmits data between a host computer system and the data storage device over a data channel. The device repeatedly broadcasts advertising packets over a wireless communication channel different from the data channel. Each advertising packet comprises a random value and a message authentication code calculated based on the random value and an identity key. The identity key is readable by a device to be connected and in proximity of the data storage device out of band of the data channel and the communication channel. The identity key enables the device to be connected to verify the message authentication code based on the random value and the identity key to thereby authenticate the data storage device.

An image forming apparatus includes a communication interface and a processor. The communication interface is configured to transmit data to and receive data from a cloud server that provides a cloud service. The processor is configured to receive a token from the cloud server via the communication interface, transmit a request including the token to the cloud server via the communication interface, receive a response including user information from the cloud server via the communication interface, and shift to a login state based on the user information.

Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.

Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.

In a method for embedding user information in webpages, user information of a user who logs into a target website is obtained. The user information is converted into color values. The color values are embedded in a target webpage of the target website. If a webpage is leaked, a user who leaks the webpage can be traced.