Identifying security breaches from clustering properties

    公开(公告)号:US20170295189A1

    公开(公告)日:2017-10-12

    申请号:US15095177

    申请日:2016-04-11

    Abstract: Embodiments of the present invention may provide the capability to identify security breaches in computer systems from clustering properties of clusters generated based on monitored behavior of users of the computer systems by using techniques that provide improved performance and reduced resource requirements. For example, behavior of users or resources may be monitored and analyzed to generate clusters and train clustering models. Labeling information relating to some user or resource may be received. When users or resources are clustered and when a cluster contains some labeled users/resources then an anomaly score can be determined for a user/resource belonging to the cluster. A user or resource may be detected to be an outlier of at least one cluster to which the user or resource has been assigned, and an alert indicating detection of the outlier may be generated.

    Ensure valid range of values of a vector for distance calculations using homomorphic encryption or functional encryption

    公开(公告)号:US11418319B2

    公开(公告)日:2022-08-16

    申请号:US16862612

    申请日:2020-04-30

    Abstract: Embodiments may provide distance computations on homomorphic and/or functional encrypted vectors while detecting whether the resulting distance has wrapped around due to the vectors having elements not in an allowed range. A method of user authentication processing may comprise receiving and storing enrollment information from a client computer system, the enrollment information comprising a template of authentication data and at least one additional encrypted vector, receiving an additional template to be used to authenticate the user from the client computer system, authenticating the user using the received additional template using the stored template and the stored at least one additional encrypted vector, and determining that authentication is successful when the received additional template matches the stored template and is valid based on the stored at least one additional encrypted vector.

    Simulation of internet of things environment

    公开(公告)号:US10235480B2

    公开(公告)日:2019-03-19

    申请号:US15182630

    申请日:2016-06-15

    Abstract: A method, system, and product for simulation of Internet of Things (IoT) environment. The method performed by a simulation node in the IoT environment, which comprises the simulation node and a cloud server connected by a computerized network. The method comprises selecting a simulated IoT device to simulate from a plurality of simulated IoT devices that are being simulated by the simulation node; invoking a real-world model to obtain real-world simulated values; determining a simulated behavior of the selected simulated IoT device by invoking a device model and providing the real-world simulated values thereto, o wherein the simulated behavior comprises transmitting a message to the cloud server; setting a next simulated action of the simulation node to occur at a designated time, wherein the next simulated action is the simulated behavior; and performing the next simulated action at the designated time.

    AUTOMATIC DECOMPOSITION OF SIMULATION MODEL
    8.
    发明申请

    公开(公告)号:US20170364613A1

    公开(公告)日:2017-12-21

    申请号:US15182631

    申请日:2016-06-15

    CPC classification number: G06F17/5009 G05B2219/23456

    Abstract: Method, system and product for decomposing a simulation model. The method comprising automatically decomposing the simulation model into a predetermined number of co-simulation components, wherein each co-simulation component is allocated to a different simulation platform, wherein said automatically decomposing comprises: defining a target optimization function, wherein the target optimization function computes an estimated run time of the simulation model, wherein the target optimization function is based on a communication time within each co-simulation component and a communication time between each pair of co-simulation components; and determining a decomposition of the simulation model that optimizes a value of the target optimization function. The method further comprises executing the decomposed simulation model by executing in parallel each co-simulation component on a different simulation platform, whereby the simulation model is executed in a distributed manner.

    Sensitive data obfuscation in output files
    9.
    发明授权
    Sensitive data obfuscation in output files 有权
    输出文件中的敏感数据混淆

    公开(公告)号:US09501654B1

    公开(公告)日:2016-11-22

    申请号:US14945878

    申请日:2015-11-19

    Abstract: Embodiments include method, systems and computer program products for protecting sensitive data. Aspects include accessing computer readable program instructions having one or more output commands. Aspects also include locating the one or more output commands in the computer readable program instructions. Aspects also include identifying target output variables and output constants in the one or more output commands. Aspects also include modifying the computer readable program instructions to append one or more obfuscate commands to the target output variables.

    Abstract translation: 实施例包括用于保护敏感数据的方法,系统和计算机程序产品。 方面包括访问具有一个或多个输出命令的计算机可读程序指令。 方面还包括将一个或多个输出命令定位在计算机可读程序指令中。 方面还包括在一个或多个输出命令中识别目标输出变量和输出常数。 方面还包括修改计算机可读程序指令以将一个或多个模糊化命令附加到目标输出变量。

    Migrating infrastructure as code between different cloud providers

    公开(公告)号:US11704119B2

    公开(公告)日:2023-07-18

    申请号:US17458125

    申请日:2021-08-26

    CPC classification number: G06F8/76 G06F8/51 G06F40/40 G06N20/00

    Abstract: A method for automatically migrating infrastructure as code (IaC) from a first cloud infrastructure platform to a second cloud infrastructure platform is provided. The method may include receiving an original IaC comprising a first type of coding language. The method may further include using natural language processing to map a connection between the first type of coding language and a second type of coding language. The method may further include based on the mapped connection, using the NLP to automatically generate a partial translation of the first type of coding language to the second type of coding language. The method may further include using a machine learning algorithm to correct at least one inaccuracy in the partial translation. The method may further include generating a complete translation and implementing a second IaC on the second cloud infrastructure platform based on the complete translation.

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