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    • 22. 发明授权
    • Methods and systems for managing network activity using biometrics
    • 使用生物识别来管理网络活动的方法和系统
    • US09509690B2
    • 2016-11-29
    • US15067696
    • 2016-03-11
    • EyeLock LLC
    • Samuel J. CarterChristopher L. ReamSarvesh MakthalStephen Charles Gerber
    • H04L29/06H04L9/08H04L9/30
    • H04L9/3231H04L9/0816H04L9/30H04L9/3013H04L9/3033H04L9/3066H04L63/0861
    • The present disclosure describes systems and methods for managing network traffic using biometrics. A server may store a first value N, a primitive root modulo N, and a plurality of verification codes generated using the primitive root modulo N to the power of a hash function result of a respective portion of a first biometric template acquired from the user during enrollment. The sever may receive a request to connect to the server, from a client operated by the user. The client may use a first offset identifier from the server to identify a first portion of a second biometric template acquired from the user, and generate a first value corresponding to a common exponentiation function. The server may generate a second value corresponding to the common exponentiation function. The server may determine that the user is authenticated if the first value from the client matches the second value.
    • 本公开描述了使用生物特征来管理网络业务的系统和方法。 服务器可以将第一个值N,原始根模N和使用原始根模N生成的多个验证码存储到从用户获取的第一生物测定模板的相应部分的散列函数结果的功率 注册。 服务器可以从用户操作的客户端接收到连接到服务器的请求。 客户端可以使用来自服务器的第一偏移标识符来识别从用户获取的第二生物测定模板的第一部分,并且生成对应于公共求幂函数的第一值。 服务器可以产生对应于公共求幂函数的第二值。 如果来自客户端的第一个值与第二个值匹配,则服务器可以确定该用户被认证。
    • 23. 发明申请
    • MODEL-BASED PREDICTION OF AN OPTIMAL CONVENIENCE METRIC FOR AUTHORIZING TRANSACTIONS
    • 基于模型的预测用于授权交易的最佳方便度量
    • US20160140567A1
    • 2016-05-19
    • US14945023
    • 2015-11-18
    • EyeLock LLC
    • Keith HannaMikhail TeverovskiyManoj AggarwalSarvesh Makthal
    • G06Q20/40G06Q20/10
    • G06Q20/40145G06Q20/20G06Q20/32G06Q20/401G06Q20/4016
    • The present disclosure describes systems and methods for authorization. The method may include accessing, by an authorization engine for a transaction by a user, an activity pattern model of the user from a database. The activity pattern model of the user may be indicative of a geospatial behavior of the user over time. The authorization engine may determine a set of sensors available for facilitating the transaction, each of the sensors assigned with a usability value prior to the transaction. The authorization engine may access an activity pattern model of the sensors, the activity pattern model of the sensors indicative of geospatial characteristics of one or more of the sensors over time. The authorization engine may determine a convenience metric for each of a plurality of subsets of the sensors, using the activity pattern model of the user, the activity pattern model of the sensors, and usability values of corresponding sensors. Each of the plurality of subsets may include corresponding sensors that can be used in combination to facilitate the transaction. The authorization engine may select, using the determined convenience metrics, a subset from the plurality of subsets to use for the transaction.
    • 本公开描述了用于授权的系统和方法。 该方法可以包括由用户的交易的授权引擎从数据库访问用户的活动模式模型。 用户的活动模式模型可以指示用户随着时间的地理空间行为。 授权引擎可以确定一组可用于促进交易的传感器,每个传感器在交易之前分配有可用性值。 授权引擎可以访问传感器的活动模式模型,传感器的活动模式模型指示一个或多个传感器随时间的地理空间特征。 授权引擎可以使用用户的活动模式模型,传感器的活动模式模型和相应的传感器的可用性值来确定传感器的多个子集中的每一个的便利度量。 多个子集中的每一个可以包括可以组合使用以便于交易的相应的传感器。 授权引擎可以使用确定的便利度量来选择来自多个子集的子集用于交易。