The technology disclosed herein enables consumer devices to verify the integrity of services running in trusted execution environments. An example method may include: acquiring, by a broker device, integrity data of a first trusted execution environment of a first computing device and integrity data of a second trusted execution environment of a second computing device, wherein the first trusted execution environment executes a first service and the second trusted execution environment executes a second service; storing the integrity data of the first trusted execution environment and the integrity data of the second trusted execution environment in a data storage device as stored integrity data; correlating integrity data of the first trusted execution environment with the first service and the integrity data of the second trusted execution environment with the second service; and providing, by the broker device, the stored integrity data to a plurality of consumer devices.

A device, method, or computer program product for conducting a cryptographic operation in a vehicle is disclosed herein. The device is arranged to receive key data and input data, and to conduct a cryptographic computation of the input data to output data using the key data. The cryptographic computation is conducted with or without side channel attack counter measures, which are toggled based on the key data or based on a control input.

A computing system and method for attestation of secured code, data and execution flows are provided. The computing system includes a processing circuitry; a memory communicatively connected to the processing circuity, the memory containing therein a protected code; and a protector circuitry connected to the processing circuitry; such that upon execution of the protected code by the processing circuitry the computing system is configured to: initialize the protector engine; perform at least one static protection check using the protector circuitry; perform at least one dynamic protection checks using the protector circuitry; and generate a notification upon detection of an error in any one the at least one static check and the at least one dynamic check.

Embodiments are disclosed for a method. The method includes validating training data that is provided for training a machine learning model using ordinary differential equations. The method further includes generating pre-processed training data from the validated training data by generating encrypted training data from the validated training data using homomorphic encryption and generating random noise based on the validated training data. The method also includes training the machine learning model adversarially with the pre-processed training data.

In some implementations, a device may monitor a screenshot function of a user device. The device may receive, via an application, sensitive information associated with an operation of the application. The device may detect a screenshot instruction associated with the screenshot function capturing a screenshot of a graphical user interface of the application that is displaying the sensitive information. The device may control the screenshot function to suspend a capture of the screenshot of the graphical user interface. The device may identify a portion of the graphical user interface that includes the sensitive information. The device may mask portion of the graphical user interface to obfuscate the sensitive information. The device may enable the screenshot function to capture, according to the screenshot instruction, the screenshot with obfuscated sensitive information. The device may unmask the portion to enable the sensitive information to be displayed via the graphical user interface.

Systems and methods for protecting and interacting with data in real time are described by the disclosed subject matter. A method includes monitoring a presentation of data by an application on a display and determining that a portion of the data is restricted. The method includes asking, in real time, the presentation of the portion of the data that is restricted.

Disclosed herein are systems and method for malicious behavior detection in processing chains comprising identifying and monitoring events generated by a first process executing on a computing device; storing snapshots of data modified by any of the events; determining a level of suspicion for the first process, wherein the level of suspicion is a likelihood of the first process being attributed to malware based on the data modified by any of the events; in response to determining that the first process is not trusted based on the determined level of suspicion, identifying at least one sub-process of the first process; and restoring, from the snapshots, objects affected by the first process and the at least one sub-process.

The present disclosure relates to a method for deploying an application in an execution environment using a first and second sets of key pairs. The method comprises: creating a sequence of tasks comprising build tasks followed by a deploy task. The tasks are configured to receive a task input for performing the tasks. The task input comprises a contribution input and an output of a task preceding at least one of the build tasks. The contribution input comprises secrets. The output of the build tasks is encrypted with a respective encryption key of the first set of key pairs, wherein the contribution input of a task subsequent to the first task is encrypted with a respective encryption key of the second set of keys. The tasks may be executed in the execution environment using unencrypted content of the task inputs.

A privacy filter includes a plurality of micro louvers. Each micro louver of the plurality of micro louvers is a same size. Each micro louver of the plurality of micro louvers are laid flat on top of each other to form the privacy filter. The plurality of micro louvers includes a first micro louver and a set of micro louvers. The first micro louver is in a fixed position. The set of micro louvers has a first piezo element at a first end of each micro louver and a second piezo element at a second end of each micro louver. The first end is opposite the second end.

Providing an isolation system that allows analysts to analyze suspicious information in a way that aids in preventing harmful information from spreading to other applications and systems on a network. A plurality of virtual containers may be used by analysts to analyze suspicious information. The analyst may set the virtual environment configurations (e.g., applications, programs, settings, etc.) of the virtual container. The analyst may determine how the suspicious information effects the virtual environment configuration and/or use tools to analyze the suspicious information. When harmful information is identified the virtual container may be discarded (e.g., folded up and deleted), and a new virtual container may be provided to the analyst to continue to analyze the suspicious information and/or new suspicious information.