At&t Intellectual Property I, LP

Mikhail Istomin

Wei Wang

Jeffrey E Bickford

Paul Giura

Thusitha Jayawardena

Evgene Vahlis

Lars Johnson

Christopher Van Wart

Rachel Rosencrantz

Gokul Singaraju

John Liefert

Andrea Giuseppe Forte

Qi Shen

Roger Piqueras Jover

Suhas Mathur

Baris Coskun

Ilona Murynets

Ramesh Subbaraman

The concepts and technologies disclosed herein are directed to on-demand trusted extended reality ('XR') environments. According to one aspect disclosed herein, a user device can create a trusted list identifying at least one trusted XR environment. The user device can connect to an untrusted XR server computer and can allow a user avatar associated with a user to enter an untrusted XR environment provided by the untrusted XR server. The user device can detect an event for which a trusted XR environment is desired. The user device can select the trusted XR environment to handle the event. The user device can select the trusted XR environment from the trusted list. The user device can instruct the untrusted XR server computer to teleport the user avatar from the untrusted XR environment to the trusted XR environment.

On-demand trusted extended reality environments

A processing system may obtain a first source data and encoding the first source data in accordance with a first key via an encoder associated with an encoder-decoder model to generate a first source data encoding that is a first output of the encoder and a second key that is a second output of the encoder. The processing system may then transmit the first source data encoding to a recipient system, where the second key is for generating a second source data encoding for transmission by the processing system to the recipient system. A processing system may also obtain a first encoded source data from a sending system, apply the first encoded source data and a first key as inputs to a decoder associated with an encoder-decoder model to obtain a first decoded source data and a second key as outputs, and present the first decoded source data.

Machine learning-based encoding/encryption key generation

Concepts and technologies disclosed herein are directed to using proof of work for preventing distributed denial of server ('DDoS') attacks. A server system can receive a resource request from a client system. The resource request can specify a resource. The server system can determine a congestion level based upon a load metric and a threshold. In response to determining that the load metric is above the threshold, the server system can determine that the congestion level is indicative of a high demand period. In response to the resource request being received during the high demand period, the server system can provide a work assignment to the client system. The server system can receive work results for the work assignment sent to the client system. In response to receiving the work results, the server system can process the resource request and can send the resource to the client system.

Using proof of work for preventing distributed denial of service attacks

Aspects of the subject disclosure may include, for example, receiving, from a computing device, a user request to perform a subscriber identity module (SIM) swap for a subscriber, wherein the computing device and a user device are accessible to a user, based on the receiving the user request, generating a code for the SIM swap, resulting in a generated code, providing the generated code to the computing device for presentation, obtaining, from the user device, data associated with the user, the user device, or a combination thereof, facilitating user authentication responsive to the obtaining the data, detecting a transmission of a particular code from the user device, resulting in a detected code, and, based on the detecting the transmission and based on the facilitating the user authentication, performing an action relating to the SIM swap. Other embodiments are disclosed.

Split input and output (IO) for subscriber identity module (SIM) swaps

The concepts and technologies disclosed herein are directed to providing a split ledger for securing extended reality ('XR') environments. According to one aspect, an XR server computer can create an XR environment. The XR server computer can cause a passed ledger to be populated with an environment ID associated with the XR environment. The XR server computer can cause a hash ledger to be populated with a first hash of the environment ID. The XR server computer can register a user for participating in the XR environment and can cause the passed ledger to be populated with a user-created block associated with the user. The XR server computer can cause the hash ledger to be further populated with a second hash of the user-created block. The XR server computer can allow a user avatar associated with the user to join the XR environment.

Split ledger for securing extended reality environments

A system allows for higher security guarantees on public or shared or even compromised equipment, which may be designated as untrusted equipment, without a need to install additional software on it or connect to it outside of general browser interactions. Based on this system, even if it is compromised, proper information separation may ensure security of the sensitive parts of data. That is, trusted information will only go to (outputs) or come from (inputs) trusted devices and insensitive information can go to or come from both trusted and untrusted devices.

Split input and output remote access

Aspects of the subject disclosure may include, for example, a device including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of facilitating establishment of a communications path between an open device and a remote device through a communications network; receiving an indication of potentially sensitive information on the communications path; and facilitating establishment of a secure communications path between a secure device and the remote device through the communications network. Other embodiments are disclosed.

Split input/output system and method for multimedia communications

Aspects of the subject disclosure may include, for example, identifying a first sensitivity level associated with a first data item, comparing the first sensitivity level to a first threshold, resulting in a first comparison, selecting a first device based on the first comparison, transmitting the first data item to the first device based on the selecting of the first device, identifying a second sensitivity level associated with a second data item, wherein the second sensitivity level is different from the first sensitivity level, comparing the second sensitivity level to a second threshold, resulting in a second comparison, selecting a second device based on the second comparison, wherein the second device is different from the first device, and transmitting the second data item to the second device based on the selecting of the second device. Other embodiments are disclosed.

Apparatuses and methods for allocating inputs and outputs in respect of interfaces of devices

Aspects of the subject disclosure may include, for example, a method for training a deep learning model that includes encoding a content item; generating a blended image by combining a background image and the encoded content; decoding the blended image to generate decoded content corresponding to the content item; and defining or specifying a loss function related to the deep learning model. The method also includes determining values of training parameters for the deep learning model to minimize the loss function, thereby obtaining a trained deep learning model. The method also includes an information concealing procedure using the trained deep learning model to conceal user content by encoding the user content and blending the encoded user content with a user-selected image; the information concealing procedure is substantially independent of the user-selected image. Other embodiments are disclosed.

Encoding and concealing information using deep learning

A method for privacy preserving vulnerability detection for devices. In an example, an apparatus may include a processor and memory coupled with the processor that effectuates operations. The operations may include receiving a type of a device; receiving a feature for the device; creating a first hash value based on the device type and the feature; receiving an indication that the first hash value matches a second hash value; and based on the indication that the first hash value matches the second hash function, sending an alert that the device has a vulnerability.

Privacy preserving vulnerability detection for devices

An insider attack resistant system for providing cloud services integrity checking is disclosed. In particular, the system utilizes an automated integrity checking script and virtual machines to check the integrity of a service. The system may utilize the integrity checking script and virtual machines to execute a set of operations associated with the service so as to check the integrity of the service. When executing the set of operations, the system may only have access to the minimum level of access to peripherals that is required for each operation in the set of operations to be executed. After each operation is executed, the system may log each result for each operation, and analyze each result to determine if a failure exists for any of the operations. If a failure exists, the system may determine that a change in an expected system behavior associated with the service has occurred.

Insider attack resistant system and method for cloud services integrity checking

A secure connection is facilitated between a device and a network. A security buffer device is used to determine an available network and connect to the network. The security buffer device can then allow the device to connect to the network via the security buffer device. The security buffer device can monitor any security breaches from the network and perform an action based on the indication of a security breach.

Security network buffer device

Portable storage devices and methods for remotely managing such portable storage devices are disclosed. For example, a method receives a request from an endpoint device to send a command to a portable storage device. The method then authenticates the endpoint device that has sent the request. The method then transmits the command wirelessly to the portable storage device. Similarly, a portable storage device includes a processor and a computer-readable medium in communication with the processor, the computer-readable medium to store instructions. The instructions, when executed by the processor, cause the processor to perform operations that include: wirelessly receiving a command related to an access of a memory of the portable storage device, verifying an authenticity of the command and executing the command when the authenticity of the command is verified.

Growing community of inventors

Brooklyn, NY, United States of America

Mikhail Istomin