Cryptographic system with halting key derivation function capabilities

    公开(公告)号:US09716587B1

    公开(公告)日:2017-07-25

    申请号:US13570128

    申请日:2012-08-08

    Applicant: Xavier Boyen

    Inventor: Xavier Boyen

    Abstract: A halting key derivation function is provided. A setup process scrambles a user-supplied password and a random string in a loop. When the loop is halted by user input, the setup process may generate verification information and a cryptographic key. The key may be used to encrypt data. During a subsequent password verification and key recovery process, the verification information is retrieved, a user-supplied trial password obtained, and both are used together to recover the key using a loop computation. During the loop, the verification process repeatedly tests the results produced by the looping scrambling function against the verification information. In case of match, the trial password is correct and a cryptographic key matching the key produced by the setup process may be generated and used for data decryption. As long as there is no match, the loop may continue indefinitely until interrupted exogenously, such as by user input.

    MOBILE DEVICE LOCATOR
    64.
    发明公开

    公开(公告)号:US20240210516A1

    公开(公告)日:2024-06-27

    申请号:US18585597

    申请日:2024-02-23

    CPC classification number: G01S5/02524 G01S5/0278 G01S5/0294 H04W4/029

    Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

    MOBILE DEVICE LOCATOR
    65.
    发明公开

    公开(公告)号:US20230273286A1

    公开(公告)日:2023-08-31

    申请号:US18312962

    申请日:2023-05-05

    CPC classification number: G01S5/02524 H04W4/029 G01S5/0278 G01S5/0294

    Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

    Processing data between data stores

    公开(公告)号:US11487780B2

    公开(公告)日:2022-11-01

    申请号:US15773395

    申请日:2015-11-04

    Abstract: A non-transitory computer readable medium can store machine readable instructions that when accessed and executed by a processing resource cause a computing device to perform operations. The operations can include establishing a connection between data stores (such as a relational data store and a graph engine), wherein the connection includes a shared memory buffer storing data in a data format according to internal structures of the graph engine. The connection between the data stores is bi-directional. The connection enables data that is stored in the shared memory to be processed by either of the graph engine and the relational database. Upon receiving a query, the graph engine or the relational database can be selected to process the data based on a query. The data can be processed by the selected one of the graph engine or the relational database.

    System and method for hierarchical classification

    公开(公告)号:US11449789B2

    公开(公告)日:2022-09-20

    申请号:US16077591

    申请日:2016-02-16

    Abstract: An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.

    Comparable user interface object identifications

    公开(公告)号:US11436133B2

    公开(公告)日:2022-09-06

    申请号:US16086176

    申请日:2016-03-23

    Abstract: Example implementations relate to comparable UI object identifications. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically identify, based on the correlated data points, a set of comparable UI objects.

    Removing wildcard tokens from a set of wildcard tokens for a search query

    公开(公告)号:US11256685B2

    公开(公告)日:2022-02-22

    申请号:US16092522

    申请日:2016-04-15

    Abstract: In one example in accordance with the present disclosure, a method may include separating a list of keywords into a set of word tokens and a set of wildcard tokens. The method may also include removing each wildcard token in the set of wildcard tokens that is inferred by at least one word token in the set of word tokens and removing each wildcard token in the set of wildcard tokens that is inferred by at least one other wildcard token in the set of wildcard tokens. The method may also include executing a search query comprising a new list of keywords that includes each wildcard token not removed from the set of wildcard tokens.

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