Abstract: A device may obtain registration data associated with a registration of an individual. The registration data may include an image that depicts a physical key and a reference object. The device may process the image to identify a first feature of the physical key and a first measurement of the first feature based on the size of the reference object. The device may store first feature data based on the first feature and the first measurement. The device may obtain second feature data based on a second feature of the physical key and a second measurement of the second feature identified from an insertion of the physical key into a keyhole of an authentication mechanism. The device may determine whether the first feature data corresponds to the second feature data. The device may authenticate the individual based on determining that the first feature data corresponds to the second feature data.

Abstract: Aspects of the disclosure relate to preventing unauthorized screen capture activity. A computing platform may detect, via an infrared sensor associated with a computing device, an infrared signal from a second device attempting an unauthorized image capture of contents being displayed by a display device of the computing device. Subsequently, the computing platform may determine, via the computing platform, the contents being displayed by the display device. Then, the computing platform may retrieve a record of the contents being displayed by the display device. Then, the computing platform may determine a risk level associated with the infrared signal. Subsequently, the computing platform may perform, via the computing platform and based on the risk level, a remediation task to prevent the unauthorized image capture.

Abstract: Aspects of the disclosure relate to preventing unauthorized screen capture activity. A computing platform may detect, via an infrared sensor associated with a computing device, an infrared signal from a second device attempting an unauthorized image capture of contents being displayed by a display device of the computing device. Subsequently, the computing platform may determine, via the computing platform, the contents being displayed by the display device. Then, the computing platform may retrieve a record of the contents being displayed by the display device. Then, the computing platform may determine a risk level associated with the infrared signal. Subsequently, the computing platform may perform, via the computing platform and based on the risk level, a remediation task to prevent the unauthorized image capture.

Abstract: Methods, systems, and devices for public key protection techniques are described. An embedded multimedia card (eMMC) may be formatted to include a permanent write protect group that is configured to prevent disabling of write protection for data stored in the permanent write protect group. The eMMC may store a public key associated with a first host device in the permanent write protect group of the eMMC. A data package may be received from the host device and authenticated by using the public key stored in the permanent write protect group. The embedded memory controller may be configured to prevent modifying or writing data to a permanent write protect group.

Abstract: A software defined data security level method, computer program product, and data processing system. One embodiment may comprise intercepting, by a processor at a data security layer, an input/output (IO) request from a local software application, wherein the IO request includes a header and a data payload, analyzing, by the processor at the data security layer, the data payload of the IO request relative to a service level agreement (SLA), assigning, by the processor at the data security layer, a security level to the IO request based on the analysis.

Abstract: The present application relates to networking technologies, communication cube technologies, and, more particularly, to methods, apparatus, techniques, and means for communication security, encryption, and privacy in network communications.

Abstract: An approach includes receiving a machine learning processing job, executing the machine learning processing job using parallel processing of multiple output pixels each cycle by walking data across processing elements with broadcast weights within regions and executing parallel multiplication operations, and generating an output indicating whether the machine learning processing job was successful or failed. In some embodiments, a schedule of actions is generated for respective machine learning processing jobs. The schedule of actions may include any of a plurality of shift operations in a many to many arrangement or a one to many arrangement, shifting data across region boundaries, fetching data and weights from a memory and distribution thereof to a plurality of regions (e.g., weights are distributed to respective weight memories which subsequently broadcasts those weights in a specified order based on a schedule of actions, and where data is distributed to respective processing elements).

Abstract: The present disclosure provides for a system ensuring the integrity of received data. The system includes a processor, a trusted platform module, and a memory storing instructions. Upon a request from the processor, the trusted platform module generates an asymmetric key pair including a private key and a public key. The trusted platform module provides the public key and an encrypted private key to the processor. The processor generates a checksum of received content data and sends the checksum to the trusted platform module. The processor also loads the encrypted private key into the trusted platform module. The trusted platform module decrypts the encrypted private key, encrypts the checksum with the private key, and provides the encrypted checksum to the processor. The processor sends the content data together with the encrypted checksum to an external device. The external device may decrypt the encrypted checksum with the public key.

Abstract: The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of automatic classification and modeling. The innovation can include determining a failure history of networked architecture, the failure history including data immediately prior to failure. The innovation can include machine learning the failure history to determine failure indicators. The innovation can include generating a black hole model based on the failure history and the machine learning. The innovation can include monitoring a networked architecture. The networked architecture has a set of elements comprising software elements and hardware elements interconnected in a common environment. Each element of the set of elements is monitored. The innovation can include determining an element is trending towards a failure. The trend is determined by a black hole model. The innovation can include enabling security features to prevent the element from failure.

Abstract: The present disclosure provides methods and systems for secure logon. One or more method includes: determining, via authentication information provided by a user of an electronic device, that the user is authorized to access an online account provided by the online account provider; providing the user with a selectable option to enable an expedited logon process by which the user can access the online account by solely providing a particular authentication item of the user; receiving a verification credential in response to a next logon attempt using the expedited logon process; and verifying that the received verification credential matches an assigned verification credential provided to the user for use in conjunction with the next logon attempt using the expedited logon process.

Abstract: A method is disclosed of a secure component (SC) of a local attestation server (LAS) for populating an enclave associated with the LAS. The SC comprises stored encrypted population information previously received in a data packet and encrypted by an encryption key matching a private decryption key of a trusted platform module (TPM) associated with the LAS. The method comprises receiving a public part of a temporary asymmetric key from the enclave, establishing a secure session between the SC and the TPM, sending (to the TPM by using the secure session) the encrypted population information and the public part of the temporary asymmetric key, receiving (from the TPM by using the secure session) the population information decrypted by the private decryption key and re-encrypted by the public part of the temporary asymmetric key, and transmitting the re-encrypted population information to the enclave. An additional method is also disclosed for enabling the population of the enclave.

Abstract: The invention relates to methods for implementing a unified framework for big data usage analytics and security profiling across heterogeneous platforms and multiple clusters. An embodiment of the present invention may be applied in various applications and use cases. This may include auditing for Big Data lakes; capacity assessment and charge back functionality for Big Data infrastructure and clusters and resource usage analytics.

Abstract: Methods, systems and computer program products are described to improve machine learning (ML) model-based classification of data items by identifying and removing inaccurate training data. Inaccurate training samples may be identified, for example, based on excessive variance in vector space between a training sample and a mean of category training samples, and based on a variance between an assigned category and a predicted category for a training sample. Suspect or erroneous samples may be selectively removed based on, for example, vector space variance and/or prediction confidence level. As a result, ML model accuracy may be improved by training on a more accurate revised training set. ML model accuracy may (e.g., also) be improved, for example, by identifying and removing suspect categories with excessive (e.g., weighted) vector space variance. Suspect categories may be retained or revised. Users may (e.g., also) specify a prediction confidence level and/or coverage (e.g., to control accuracy).

Abstract: Technology related to multi-device authentication is disclosed. In one example, a method can include receiving a request from a requesting client device to access a secured server. A command can be sent to an authenticating device to capture environmental information in proximity to the authenticating device. The captured environmental information can be used to verify the requesting client device and the authenticating device are near each other. The received request can be forwarded to the secured server in response to verifying the requesting client device and the authenticating device are near each other.

Abstract: In one aspect, a computerized-process for implementing Security Assessment For Enterprise (SAFE) Scoring Model include the step of generating a cybersecurity model by the following steps. The process determines a Governance Policy Score. The process determines a People Awareness Score. The process determines a Cybersecurity Architecture Score. The process determines an External Score. The process determines a Technology Score.

Abstract: A method for moderation in a permissioned blockchain using a hash-oriented scheme includes: storing a blockchain including a most recent block; receiving transaction data values; receiving a first reference value and a second reference value; generating a first hash value by hashing the first reference value; generating a block proof including the first hash value, a second hash value, a third reference value, and a block value; verifying a block header of the most recent block using the block proof; receiving a new block value; generating a new block header including the first reference value, the second reference value, a fourth reference value, and the new block value; generating a new block for the blockchain including the new block header and the transaction data values; and transmitting the new block to one or more additional nodes associated with the blockchain.

Abstract: A network-based service may provide a machine learning model for different clients. The network-based service may implement an interface that allows a client to identify a test data set for validating versions of the machine learning model specifically for the client. When a new version of the machine learning model is created, a validation test using the test data set identified by the client may be used. Results of the validation test may be used to make a decision regard whether to migrate workloads for the client to the new version of the machine learning model.

Abstract: A method of certifying a state of a platform includes receiving one or more software elements of a software stack of the platform by an authentication module and performing a hash algorithm on the software stack to generate one or more hash values. The software stack uniquely determines a software state of the platform. The method includes generating creation data, a creation hash, and a creation ticket, corresponding to the hash values and sending the creation ticket to the platform. The method also includes receiving the creation ticket by the authentication module and certifying the creation data and the creation hash based on the creation ticket. The method further includes generating a certified structure based on the creation data and performing the hash algorithm on the certified structure to generate a hash of the certified structure. The certified structure uniquely determines the software state of the platform.

Abstract: An electronic device is provided. The electronic device includes a display configured to display information, an input device configured to receive a user input, an image sensor, a processor electrically connected with the display, the input device, and the image sensor, and a non-transitory computer readable storage medium electrically connected with the processor that stores instructions that cause the processor to control the display to display first-level information as a locking mode is partially released when partial authentication passes based on bio-information acquired through the image sensor in a state in which the electronic device is in the locking mode, and control the display to display second-level information having a security level higher than a security level of the first-level information as the locking mode is fully released when full authentication passes based on a user input made through the input device.

Abstract: A method for applying agency and regulation modeling in a multi-tenant architecture system includes accessing merchant's representation in an identity manager. The merchant is managed via a full representation by an original identity manager. The method includes performing a first service for the merchant via the representation, and determining, based on results of the first service and on policies of the first service provider, that performance of a second service is required for completion of the first service. The second service is provided by a second service provider onboarded into the first service provider, where the second service amends policy requirements of the first service provider. The method includes accessing a first subservice of the second service using the representation to generate second results for use at a second subservice of the second service, the second subservice configured to use transaction resources of the first representation.