INTELLIGENT SECURITY MANAGEMENT

A corpus of documents (and other data objects) stored for an entity can be analyzed to determine one or more topics for each document. Elements of the documents can be analyzed to also assign a risk score. The types of topics and security elements, and the associated risk scores, can be learned and...

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Hauptverfasser: RADULOVIC PAUL, GOUGH MICHAEL, CAI NAI QIN, ANGER MAX, SIMMONS CHRISTOPHER, JOHNSON ERIC, BRIM DANIEL, BRAY TYLER STUART, RASGAITIS JACK, BRINKLEY JENNIFER ANNE, CHIN VICTOR, WATSON ALEXANDER
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creator RADULOVIC PAUL
GOUGH MICHAEL
CAI NAI QIN
ANGER MAX
SIMMONS CHRISTOPHER
JOHNSON ERIC
BRIM DANIEL
BRAY TYLER STUART
RASGAITIS JACK
BRINKLEY JENNIFER ANNE
CHIN VICTOR
WATSON ALEXANDER
description A corpus of documents (and other data objects) stored for an entity can be analyzed to determine one or more topics for each document. Elements of the documents can be analyzed to also assign a risk score. The types of topics and security elements, and the associated risk scores, can be learned and adapted over time using, for example, a topic model and random forest regressor. Activity with respect to the documents is monitored, and expected behavior for a user determined using a trained recurrent neural network. Ongoing user activity is processed to determine whether the activity excessivelydeviates from the expected user activity. The activity can also be compared against the activity of user peers to determine whether the activity is also anomalous among the user peer group. For anomalous activity, risk scores of the accessed documents can be analyzed to determine whether to generate an alert. 可以对针对实体存储的文档(和其他数据对象)的语料库进行分析以确定针对每个文档的一个或多个主题。可以分析所述文档的元素以也指派风险分数。可以使用例如主题模型和随机森林回归器来随时间的推移学习和调适主题和安全元素的类型以及相关联的
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Elements of the documents can be analyzed to also assign a risk score. The types of topics and security elements, and the associated risk scores, can be learned and adapted over time using, for example, a topic model and random forest regressor. Activity with respect to the documents is monitored, and expected behavior for a user determined using a trained recurrent neural network. Ongoing user activity is processed to determine whether the activity excessivelydeviates from the expected user activity. The activity can also be compared against the activity of user peers to determine whether the activity is also anomalous among the user peer group. For anomalous activity, risk scores of the accessed documents can be analyzed to determine whether to generate an alert. 可以对针对实体存储的文档(和其他数据对象)的语料库进行分析以确定针对每个文档的一个或多个主题。可以分析所述文档的元素以也指派风险分数。可以使用例如主题模型和随机森林回归器来随时间的推移学习和调适主题和安全元素的类型以及相关联的</abstract><oa>free_for_read</oa></addata></record>
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title INTELLIGENT SECURITY MANAGEMENT
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