System and method for detecting security risks in a computer system

    公开(公告)号:US10909242B2

    公开(公告)日:2021-02-02

    申请号:US16169081

    申请日:2018-10-24

    Abstract: A system and method are provided for identifying security risks in a computer system. The system includes an event stream generator configured to collect system event data from the computer system. The system further includes a query device configured to receive query requests that specify parameters of a query. Each query request includes at least one anomaly model. The query request and the anomaly model are included in a first syntax in which a system event is expressed as {subject-operation-object}. The system further includes a detection device configured to receive at least one query request from the query device and continuously compare the system event data to the anomaly models of the query requests to detect a system event that poses a security risk. The system also includes a reporting device configured to generate an alert for system events that pose a security risk detected by the detection device.

    WORD-OVERLAP-BASED CLUSTERING CROSS-MODAL RETRIEVAL

    公开(公告)号:US20210027019A1

    公开(公告)日:2021-01-28

    申请号:US16918353

    申请日:2020-07-01

    Abstract: A system for cross-modal data retrieval is provided that includes a neural network having a time series encoder and text encoder which are jointly trained using an unsupervised training method which is based on a loss function. The loss function jointly evaluates a similarity of feature vectors of training sets of two different modalities of time series and free-form text comments and a compatibility of the time series and the free-form text comments with a word-overlap-based spectral clustering method configured to compute pseudo labels for the unsupervised training method. The computer processing system further includes a database for storing the training sets with feature vectors extracted from encodings of the training sets. The encodings are obtained by encoding a training set of the time series using the time series encoder and encoding a training set of the free-form text comments using the text encoder.

    AERIAL FIBER OPTIC CABLE LOCALIZATION BY DISTRIBUTED ACOUSTIC SENSING

    公开(公告)号:US20200319017A1

    公开(公告)日:2020-10-08

    申请号:US16838105

    申请日:2020-04-02

    Inventor: Yue TIAN

    Abstract: Aspects of the present disclosure describe aerial fiber optical cable localization using distributed acoustic sensing (DAS) that advantageously may determine the locality of electrical transformers affixed to utility poles along with the aerial fiber optical cable as well as any length(s) of fiber optical cable between the poles. Further aspects employ survey manned or unmanned, aerial or terrestrial survey vehicles that acoustically excite locations along the fiber optical cable and associate those DAS excitations with global positioning location (GPS).

    OPTICAL FIBER NONLINEARITY COMPENSATION USING NEURAL NETWORKS

    公开(公告)号:US20190393965A1

    公开(公告)日:2019-12-26

    申请号:US16449319

    申请日:2019-06-21

    Abstract: Aspects of the present disclosure describe systems, methods and structures for optical fiber nonlinearity compensation using neural networks that advantageously employ machine learning (ML) algorithms for nonlinearity compensation (NLC) that advantageously provide a system-agnostic model independent of link parameters, and yet still achieve a similar or better performance at a lower complexity as compared with prior-art methods. Systems, methods, and structures according to aspects of the present disclosure include a data-driven model using the neural network (NN) to predict received signal nonlinearity without prior knowledge of the link parameters. Operationally, the NN is provided with intra-channel cross-phase modulation (IXPM) and intra-channel four-wave mixing (IFWM) triplets that advantageously provide a more direct pathway to underlying nonlinear interactions.

    MISO (MultIStore-Online-tuning) System
    160.
    发明申请
    MISO (MultIStore-Online-tuning) System 有权
    MISO(Multistore-Online-tuning)系统

    公开(公告)号:US20160147832A1

    公开(公告)日:2016-05-26

    申请号:US14321881

    申请日:2014-07-02

    Abstract: A system includes first and second data stores, each store having a set of materialized views of the base data and the views comprise a multistore physical design; an execution layer coupled to the data stores; a query optimizer coupled to the execution layer; and a tuner coupled to the query optimizer and the execution layer, wherein the tuner determines a placement of the materialized views across the stores to improve workload performance upon considering each store's view storage budget and a transfer budget when moving views across the stores.

    Abstract translation: 系统包括第一和第二数据存储,每个存储具有一组基本数据的物化视图,并且视图包括多存储物理设计; 耦合到数据存储的执行层; 耦合到执行层的查询优化器; 以及耦合到所述查询优化器和所述执行层的调谐器,其中,所述调谐器在跨所述商店移动视图时,在考虑每个商店的视图存储预算和转移预算时,确定跨所述商店的物化视图的放置以改善工作负载性能。

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