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11. 发明授权

US08898478B2 Method for querying data in privacy preserving manner using attributes 有权
标题翻译：使用属性以隐私保护方式查询数据的方法
公开(公告)号：US08898478B2
公开(公告)日：2014-11-25
申请号：US13525191
申请日：2012-06-15
申请人： Wei Sun , Shantanu Rane
发明人： Wei Sun , Shantanu Rane
IPC分类号： G06F11/30 , G06F12/14 , H04L9/00 , G06F21/60
CPC分类号： G06F21/602 , G06F21/6254 , G06F2221/2107 , H04L9/00 , H04L9/008 , H04L9/3073
摘要： A client queries a set of encrypted data instances located at a server with a query attribute of the client. The set of encrypted data instances is associated with a set of ciphertexts, wherein a ciphertext is an encrypted function of a representation of a corresponding data instance and a data instance attribute extracted from the corresponding data instance. The client decrypts the ciphertext from the set of ciphertexts based on a distance function of the query attribute and the data instance attribute to produce the representation, and accesses the corresponding data instance using the representation.
摘要翻译：客户端使用客户端的查询属性查询位于服务器的一组加密数据实例。一组加密数据实例与一组密文相关联，其中密文是对应数据实例的表示的加密函数和从相应的数据实例提取的数据实例属性。客户端根据查询属性和数据实例属性的距离函数从密文集中解密密文，以生成表示，并使用该表示访问相应的数据实例。

12. 发明申请

US20140105385A1 Method for Privacy-Preserving Order Selection of Encrypted Element 有权
标题翻译：加密元素隐私保护顺序选择方法
公开(公告)号：US20140105385A1
公开(公告)日：2014-04-17
申请号：US12965066
申请日：2010-12-10
申请人： Shantanu Rane , Wei Sun
发明人： Shantanu Rane , Wei Sun
IPC分类号： H04L9/08
CPC分类号： H04L9/0819 , H04L9/008 , H04L2209/46
摘要： A system and a method select an encrypted element in an encrypted vector according to an order of the encrypted element in the encrypted vector. The selecting is performed in a privacy-preserving manner. Values of the elements of the encrypted vector are scaled, such that the order of the elements in the encrypted vector is preserved, and then permuted to produce a scaled permuted vector. Information in the encrypted domain indicative of an order of elements in the scaled permuted vector is provided to a second processor having a private key. The second processor decrypts the information to determine the index of the encrypted element based on the order of the elements. The encrypted element is obliviously selected based on the index.
摘要翻译：系统和方法根据加密向量中加密元素的顺序选择加密向量中的加密元素。以隐私保护的方式执行选择。加密矢量的元素的值被缩放，使得保存加密矢量中的元素的顺序，然后被排列以产生缩放的置换向量。将表示缩放置换向量中的元素的顺序的加密域中的信息提供给具有私钥的第二处理器。第二处理器根据元素的顺序解密信息以确定加密元素的索引。基于索引忽略加密元素。

13. 发明授权

US08473537B2 Secure multi-party computation of normalized sum-type functions 有权
标题翻译：安全多方计算归一化求和函数
公开(公告)号：US08473537B2
公开(公告)日：2013-06-25
申请号：US12890151
申请日：2010-09-24
申请人： Shantanu Rane , Ye Wang , Wei Sun , Prakash Ishwar
发明人： Shantanu Rane , Ye Wang , Wei Sun , Prakash Ishwar
IPC分类号： G06F7/38
CPC分类号： G06F7/5057 , G06F7/5443 , H03M13/1111 , H03M13/658 , H04B10/6165 , H04L9/3218 , H04L2209/46 , H04L2209/50
摘要： Embodiments of present invention disclose a system and a method for determining a result of a function applied to a first vector and a second vector, wherein the function is a normalized sum-type function. The first vector is stored at a first processor, and the second vector is stored at a second processor. The system and the method determine a joint empirical probability distribution (JEPD) of the first vector and the second vector using a secure multi-party computation. The function is determined as a normalized summation of products of values of the JEPD with corresponding values of the function.
摘要翻译：本发明的实施例公开了一种用于确定应用于第一矢量和第二矢量的功能的结果的系统和方法，其中该功能是归一化的和型功能。第一矢量存储在第一处理器中，第二矢量被存储在第二处理器中。系统和方法使用安全多方计算确定第一向量和第二向量的联合经验概率分布（JEPD）。该函数被确定为JEPD的值的乘积与函数的相应值的归一化求和。

14. 发明申请

US20120254606A1 Privacy-Preserving Probabilistic Inference Based on Hidden Markov Models 有权
标题翻译：基于隐马尔可夫模型的隐私保护概率推理
公开(公告)号：US20120254606A1
公开(公告)日：2012-10-04
申请号：US13076424
申请日：2011-03-31
申请人： Wei Sun , Shantanu Rane
发明人： Wei Sun , Shantanu Rane
IPC分类号： H04L9/28 , G06N5/04
CPC分类号： H04L9/008 , G06N7/005 , H04L2209/46 , H04L2209/50
摘要： A most likely sequence of states corresponding to an observation sequence stored at a client is determined securely with respect to a HMM stored at a server. An encryption of a log-probability of the current element of the observation sequence is determined for each state of the HMM. A product of an encryption of the log-probability of the state for the current element, an encryption of a transition probability to the state, and the encryption of a log-probability of the current element of the observation sequence is determined iteratively, for each state of the HMM, to produce an encrypted matrix of indexes of the states; and the encrypted matrix is transmitted to the client.
摘要翻译：相对于存储在服务器中的HMM，安全地确定对应于存储在客户端的观察序列的最可能的状态序列。针对HMM的每个状态确定对观察序列的当前元素的对数概率的加密。对于每一个，迭代地确定对当前元素的状态的对数概率的加密，对状态的转移概率的加密以及观察序列的当前元素的对数概率的加密的乘积 HMM的状态，以产生状态索引的加密矩阵; 并将加密的矩阵传送给客户端。

15. 发明授权

US08249250B2 Secure similarity verification between homomorphically encrypted signals 有权
标题翻译：同态加密信号之间的安全相似性验证
公开(公告)号：US08249250B2
公开(公告)日：2012-08-21
申请号：US12413990
申请日：2009-03-30
申请人： Shantanu Rane , Wei Sun , Anthony Vetro
发明人： Shantanu Rane , Wei Sun , Anthony Vetro
IPC分类号： H04L9/00 , G06F21/00
CPC分类号： H04L9/008 , G09C1/00 , H04L9/302 , H04L9/321 , H04L9/3271
摘要： A method for verifying a similarity between a first signal and a second signal is described. The first and the second signals are encrypted homomorphically using a key. First, we acquire a set of error patterns determined by a similarity constraint. Then, each error pattern is homomorphically encrypted using the key and presented to a verifier in the setup phase. The verifier declares the first signal similar to the second signal, if any error pattern in the set of error patterns satisfies a homomorphic relationship between the first encrypted signal and the second encrypted signal.
摘要翻译：描述了用于验证第一信号和第二信号之间的相似性的方法。第一和第二信号使用密钥同态加密。首先，我们获取由相似性约束确定的一组错误模式。然后，使用密钥对每个错误模式进行同态加密，并在设置阶段提供给验证者。验证者声明类似于第二信号的第一信号，如果错误模式集合中的任何错误模式满足第一加密信号和第二加密信号之间的同态关系。

16. 发明授权

US08625782B2 Method for privacy-preserving computation of edit distance of symbol sequences 有权
标题翻译：符号序列编辑距离的隐私保留计算方法
公开(公告)号：US08625782B2
公开(公告)日：2014-01-07
申请号：US12703150
申请日：2010-02-09
申请人： Shantanu Rane , Wei Sun
发明人： Shantanu Rane , Wei Sun
IPC分类号： H04L9/00
CPC分类号： H04L9/008 , H04L2209/46 , H04L2209/50
摘要： Embodiments of the invention discloses a system and a method for determining an encrypted edit distance as an encryption of a minimum cost of transformation of a first sequence into a second sequence based on an insertion cost, a deletion cost, and a substitution cost. The method determines recursively a current element of the matrix as an encryption of a minimum of a first element, a second element, and a third element to produce the dynamic programming solution, wherein the first element represents the insertion cost, the second element represents the deletion cost, and the third element represents the substitution costs, and wherein the current element, the first element, the second element, and the third element are homomorphically encrypted with a public key; and selects the dynamic programming solution as the encrypted edit distance, wherein steps of the method are performed by a first processor and a second processor.
摘要翻译：本发明的实施例公开了一种用于基于插入成本，删除成本和替代成本来确定加密编辑距离作为第一序列到第二序列的最小转换成本的加密的系统和方法。该方法递归地确定矩阵的当前元素作为第一元素，第二元素和第三元素的最小值的加密以产生动态规划解决方案，其中第一元素表示插入成本，第二元素表示删除成本，第三元素表示替代成本，并且其中当前元素，第一元素，第二元素和第三元素被公共密钥同态加密; 并且选择动态编程解决方案作为加密的编辑距离，其中该方法的步骤由第一处理器和第二处理器执行。

17. 发明申请

US20130340098A1 Method for Outsourcing Data for Secure Processing by Untrusted Third Parties 有权
标题翻译：外判不可信第三方安全处理数据的方法
公开(公告)号：US20130340098A1
公开(公告)日：2013-12-19
申请号：US13525218
申请日：2012-06-15
申请人： Shantanu Rane , Wei Sun
发明人： Shantanu Rane , Wei Sun
IPC分类号： G06F21/24 , G06F15/16
CPC分类号： H04L63/0428 , H04L41/069 , H04L63/0407
摘要： Data is generated in a client based on events at a client, wherein each event is associated with a first dimension, a second dimension and a quantity. A random value is generated for each interval of the first dimension and each instance of the second dimension. The quantity of each event is modified using the random value to determine a modified quantity. A running total for each interval of the first dimension and each instance of the second dimension is determined using the modified quantities and transmitted to an untrusted third party. An exact result of processing the modified quantities and the running totals by the untrusted third party can then be received and decoded by the client.
摘要翻译：基于客户机上的事件在客户端中生成数据，其中每个事件与第一维度，第二维度和数量相关联。为第一维度和第二维度的每个实例的每个间隔生成随机值。使用随机值修改每个事件的数量以确定修改的数量。使用修改的数量确定第一维度的每个间隔和第二维度的每个实例的运行总计并传送到不可信的第三方。然后可以由客户接收并解码由不可信第三方处理修改的数量和运行总计的确切结果。

18. 发明申请

US20130339751A1 Method for Querying Data in Privacy Preserving Manner Using Attributes 有权
标题翻译：使用属性保护隐私方式查询数据的方法
公开(公告)号：US20130339751A1
公开(公告)日：2013-12-19
申请号：US13525191
申请日：2012-06-15
申请人： Wei Sun , Shantanu Rane
发明人： Wei Sun , Shantanu Rane
IPC分类号： G06F21/22
CPC分类号： G06F21/602 , G06F21/6254 , G06F2221/2107 , H04L9/00 , H04L9/008 , H04L9/3073
摘要： A client queries a set of encrypted data instances located at a server with a query attribute of the client. The set of encrypted data instances is associated with a set of ciphertexts, wherein a ciphertext is an encrypted function of a representation of a corresponding data instance and a data instance attribute extracted from the corresponding data instance. The client decrypts the ciphertext from the set of ciphertexts based on a distance function of the query attribute and the data instance attribute to produce the representation, and accesses the corresponding data instance using the representation.
摘要翻译：客户端使用客户端的查询属性查询位于服务器的一组加密数据实例。一组加密数据实例与一组密文相关联，其中密文是对应数据实例的表示的加密函数和从相应的数据实例提取的数据实例属性。客户端根据查询属性和数据实例属性的距离函数从密文集中解密密文，以生成表示，并使用该表示访问相应的数据实例。

19. 发明授权

US08433892B2 Privacy-preserving probabilistic inference based on hidden Markov models 有权
标题翻译：基于隐马尔可夫模型的隐私保护概率推理
公开(公告)号：US08433892B2
公开(公告)日：2013-04-30
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： H04L29/06
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。

20. 发明申请

US20120254605A1 Privacy-Preserving Probabilistic Inference Based on Hidden Markov Models 有权
标题翻译：基于隐马尔可夫模型的隐私保护概率推理
公开(公告)号：US20120254605A1
公开(公告)日：2012-10-04
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： H04L9/00
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。

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