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272 条记录 (耗时 0.049 秒)

    Privacy-preserving probabilistic inference based on hidden markov models
    81.
    发明授权
    Privacy-preserving probabilistic inference based on hidden markov models 有权
    基于隐马尔可夫模型的隐私保护概率推理

    公开(公告)号：US08433893B2

    公开(公告)日：2013-04-30

    申请号：US13076418

    申请日：2011-03-30

    申请人： Wei Sun ,  Shantanu Rane

    发明人： Wei Sun ,  Shantanu Rane

    IPC分类号： H04L29/06

    CPC分类号： H04L9/00 ,  G09C1/00 ,  H04L9/008 ,  H04L2209/42

    摘要： Parameters of a hidden Markov model (HMM) are determined by a server based on an observation sequence stored at a client, wherein the client has a decryption key and an encryption key of an additively homomorphic cryptosystem, and the server has only the encryption key. The server initializes parameters of the HMM and updates the parameters iteratively until a difference between a probability of the observation sequence of a current iteration and a probability of the observation sequence of a previous iteration is above a threshold, wherein, for each iteration, the parameters are updated based on an encrypted conditional joint probability of each pair of states given the observation sequence and the parameters of the HMM, wherein the encrypted conditional probability is determining in an encrypted domain using a secure multiparty computation (SMC) between the server and the client.

    摘要翻译： 隐马尔可夫模型（HMM）的参数由服务器基于存储在客户端的观察序列确定，其中客户端具有加密同态密码系统的解密密钥和加密密钥，并且服务器仅具有加密密钥。 服务器初始化HMM的参数并重复更新参数，直到当前迭代的观察序列的概率与先前迭代的观察序列的概率之间的差异高于阈值，其中，对于每次迭代，参数 基于给定观察序列和HMM的参数的每对状态的加密条件联合概率更新，其中加密的条件概率在加密域中使用服务器和客户端之间的安全多方计算（SMC）来确定 。

    Method for determining functions applied to signals
    82.
    发明授权
    Method for determining functions applied to signals 有权
    用于确定应用于信号的功能的方法

    公开(公告)号：US08416955B2

    公开(公告)日：2013-04-09

    申请号：US12631974

    申请日：2009-12-07

    申请人： Shantanu Rane ,  Wei Sun ,  Anthony Vetro

    发明人： Shantanu Rane ,  Wei Sun ,  Anthony Vetro

    IPC分类号： H04L9/08

    CPC分类号： H04L9/3093 ,  H04L9/008

    摘要： A system and a method for determining a result of applying a function to signals is disclosed. The function is a polynomial function including monomials, in which the first signal in a first power forming a first part of the monomial and the second signal in a second power forming a second part of the monomial, wherein the first part of the monomial encrypted with a key is a first encrypted signal, and the second part of the monomial encrypted with the key is a second encrypted signal, comprising the steps of transmitting a first input signal encrypted with a second public key to the second processor, wherein the first input signal includes the first encrypted signal, transmitting a second input signal encrypted with a first public key to the first processor, wherein the second input signal includes a product of the first encrypted signal and the second encrypted signal.

    摘要翻译： 公开了一种用于确定将功能应用于信号的结果的系统和方法。 该函数是包括单项式的多项式函数，其中形成单项式的第一部分的第一功率中的第一信号和形成单项式的第二部分的第二功率中的第二信号，其中单项的第一部分用 密钥是第一加密信号，并且用密钥加密的单项项的第二部分是第二加密信号，包括以下步骤：向第二处理器发送用第二公钥加密的第一输入信号，其中第一输入信号 将第一加密信号包括在第一处理器中传送用第一公开密钥加密的第二输入信号，其中第二输入信号包括第一加密信号和第二加密信号的乘积。

    TUNING PARAMETER OF KALMAN FILTER IN A WHEEL INSPECTION
    84.
    发明申请
    TUNING PARAMETER OF KALMAN FILTER IN A WHEEL INSPECTION 有权
    KALMAN过滤器在轮胎检查中的调谐参数

    公开(公告)号：US20120316727A1

    公开(公告)日：2012-12-13

    申请号：US13590788

    申请日：2012-08-21

    申请人： Ning Duan ,  Ke Hu ,  Zhong Bo Jiang ,  Wen Ting Mo ,  Wei Sun ,  Xin Zhang

    发明人： Ning Duan ,  Ke Hu ,  Zhong Bo Jiang ,  Wen Ting Mo ,  Wei Sun ,  Xin Zhang

    IPC分类号： G01M17/10

    CPC分类号： G01M17/013

    摘要： An apparatus for tuning a parameter of a Kalman filter in a wheel inspection for a vehicle is disclosed. The apparatus includes an association module that associates wheel inspection data of the vehicle with locations of corresponding wheels in the vehicle; an evaluation module that evaluates a wheel stable score of the vehicle based on the wheel inspection data and the association, where the wheel stable score indicates reliability of the wheel inspection; and a parameter tuning module that tunes a measurement error covariance of the Kalman filter according to the evaluated wheel stable score.

    摘要翻译： 公开了一种用于调整车辆车轮检查中的卡尔曼滤波器的参数的装置。 该装置包括关联模块，其将车辆的车轮检查数据与车辆中相应车轮的位置相关联; 评估模块，其基于车轮检查数据和关联来评估车辆的车轮稳定分数，其中车轮稳定分数表示车轮检查的可靠性; 以及参数调谐模块，根据评估轮稳定分数调整卡尔曼滤波器的测量误差协方差。

    Method for determining functions applied to signals
    87.
    发明授权
    Method for determining functions applied to signals 有权
    用于确定应用于信号的功能的方法

    公开(公告)号：US08311213B2

    公开(公告)日：2012-11-13

    申请号：US12631939

    申请日：2009-12-07

    申请人： Shantanu Rane ,  Wei Sun ,  Anthony Vetro

    发明人： Shantanu Rane ,  Wei Sun ,  Anthony Vetro

    IPC分类号： H04L29/00

    CPC分类号： H04L9/008

    摘要： Embodiments of the invention discloses a system and a method for determining a result of applying a function to signals including a first signal and a second signal, wherein the function is a polynomial function of the signals such that a monomial in the function includes the first signal having a power less than or equal to a first maximum power, and wherein the first signal is partitioned into a first subsignal and a second subsignal, comprising a processor for performing steps of the method, comprising the steps of acquiring a second signal and a second subsignal; acquiring a set of encrypted powers of the first subsignal, wherein the set of encrypted powers of the first subsignal includes homomorphically encrypted powers of the first subsignal; and determining an encrypted result of the function based on a second subsignal, the set of encrypted powers of the first subsignal, and the second signal.

    摘要翻译： 本发明的实施例公开了一种用于确定对包括第一信号和第二信号的信号应用功能的结果的系统和方法，其中所述函数是所述信号的多项式函数，使得所述函数中的单项包括所述第一信号 具有小于或等于第一最大功率的功率，并且其中所述第一信号被划分为第一子信号和第二子信号，包括用于执行所述方法的步骤的处理器，包括以下步骤：获取第二信号和第二信号 次信号 获取所述第一子信号的一组加密功率，其中所述第一子信号的加密功率集合包括所述第一子信号的同态加密功率; 以及基于第二子信号确定所述函数的加密结果，所述第一子信号的加密功率集合和所述第二信号。

    Privacy-Preserving Probabilistic Inference Based on Hidden Markov Models
    89.
    发明申请
    Privacy-Preserving Probabilistic Inference Based on Hidden Markov Models 有权
    基于隐马尔可夫模型的隐私保护概率推理

    公开(公告)号：US20120254612A1

    公开(公告)日：2012-10-04

    申请号：US13076410

    申请日：2011-03-30

    申请人： Shantanu Rane ,  Wei Sun ,  Manas A. Pathak ,  Bhiksha Raj

    发明人： Shantanu Rane ,  Wei Sun ,  Manas A. Pathak ,  Bhiksha Raj

    IPC分类号： G06N5/02 ,  H04L9/32

    CPC分类号： H04L9/008 ,  G06N7/005 ,  H04L2209/46

    摘要： A probability of an observation sequence stored at a client is evaluated securely with respect to a hidden Markov model (HMM) stored at a server. The server determines, for each state of the HMM, an encryption of a log-probability of a current element of the observation sequence. Determines, for each state of the HMM, an encryption of a log-summation of a product of a likelihood of the observation sequence based on a previous element of the observation sequence and a transition probability to the state of the HMM. Determines an encryption of a log-likelihood of the observation sequence for each state as a product of the encryption of a log-summation and an encryption of a corresponding log-probability of the current element of the observation sequence; and determines an encryption of the log-probability of the observation sequence based on the log-likelihood of the observation sequence for each state.

    摘要翻译： 相对于存储在服务器中的隐马尔可夫模型（HMM），安全地评估存储在客户端的观察序列的概率。 对于HMM的每个状态，服务器确定观察序列的当前元素的对数概率的加密。 确定对于HMM的每个状态，基于观测序列的先前元素和HMM状态的转移概率，对观测序列的可能性的乘积的对数加和进行加密。 确定每个状态的观察序列的对数似然度的加密，作为对数求和的加密和观察序列的当前元素的相应对数概率的加密的乘积; 并且基于每个状态的观察序列的对数似然度来确定观察序列的对数概率的加密。