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    • 1. 发明授权
    • Privacy-preserving aggregation of Time-series data
    • 时间序列数据的隐私保护聚合
    • US08555400B2
    • 2013-10-08
    • US13021538
    • 2011-02-04
    • Runting ShiRichard ChowTsz Hong Hubert Chan
    • Runting ShiRichard ChowTsz Hong Hubert Chan
    • G06F17/30H04L9/00H04L9/32
    • H04L9/3006H04L9/008H04L9/0833H04L9/088H04L2209/08H04L2209/46
    • A private stream aggregation (PSA) system contributes a user's data to a data aggregator without compromising the user's privacy. The system can begin by determining a private key for a local user in a set of users, wherein the sum of the private keys associated with the set of users and the data aggregator is equal to zero. The system also selects a set of data values associated with the local user. Then, the system encrypts individual data values in the set based in part on the private key to produce a set of encrypted data values, thereby allowing the data aggregator to decrypt an aggregate value across the set of users without decrypting individual data values associated with the set of users, and without interacting with the set of users while decrypting the aggregate value. The system also sends the set of encrypted data values to the data aggregator.
    • 私有流聚合(PSA)系统将用户的数据贡献给数据聚合器,而不会影响用户的隐私。 系统可以通过在一组用户中确定本地用户的私钥来开始,其中与用户组和数据聚合器相关联的私钥的总和等于零。 该系统还选择与本地用户相关联的一组数据值。 然后,系统部分地基于私钥对集合中的各个数据值进行加密以产生一组加密的数据值,从而允许数据聚合器在该组用户之间解密聚合值,而不会解密与 一组用户,并且在解密聚合值时不与该组用户交互。 该系统还将一组加密的数据值发送到数据聚合器。
    • 2. 发明申请
    • PRIVACY-PRESERVING AGGREGATION OF TIME-SERIES DATA
    • 隐私保护时间序列数据的聚合
    • US20120204026A1
    • 2012-08-09
    • US13021538
    • 2011-02-04
    • Runting ShiRichard ChowTsz Hong Hubert Chan
    • Runting ShiRichard ChowTsz Hong Hubert Chan
    • H04L9/32
    • H04L9/3006H04L9/008H04L9/0833H04L9/088H04L2209/08H04L2209/46
    • A private stream aggregation (PSA) system contributes a user's data to a data aggregator without compromising the user's privacy. The system can begin by determining a private key for a local user in a set of users, wherein the sum of the private keys associated with the set of users and the data aggregator is equal to zero. The system also selects a set of data values associated with the local user. Then, the system encrypts individual data values in the set based in part on the private key to produce a set of encrypted data values, thereby allowing the data aggregator to decrypt an aggregate value across the set of users without decrypting individual data values associated with the set of users, and without interacting with the set of users while decrypting the aggregate value. The system also sends the set of encrypted data values to the data aggregator.
    • 私有流聚合(PSA)系统将用户的数据贡献给数据聚合器,而不会影响用户的隐私。 系统可以通过在一组用户中确定本地用户的私钥来开始,其中与用户组和数据聚合器相关联的私钥的总和等于零。 该系统还选择与本地用户相关联的一组数据值。 然后,系统部分地基于私钥对集合中的各个数据值进行加密以产生一组加密的数据值,从而允许数据聚合器在该组用户之间解密聚合值,而不会解密与 一组用户,并且在解密聚合值时不与该组用户交互。 该系统还将一组加密的数据值发送到数据聚合器。
    • 4. 发明授权
    • Privacy-preserving collaborative filtering
    • 隐私保护协同过滤
    • US08478768B1
    • 2013-07-02
    • US13314748
    • 2011-12-08
    • Manas Ashok PathakRichard ChowRunting ShiCong Wang
    • Manas Ashok PathakRichard ChowRunting ShiCong Wang
    • G06F7/00G06F17/30
    • G06Q10/101G06Q30/0282
    • A recommender system can generate a predicted item rating for one user by performing collaborative filtering on item ratings from other users. The recommender system can include a client device that interfaces with a server to obtain a predicted item rating for a local user. The client device can generate a standardized ratings vector for the user, and computes a group identifier for the user based on the standardized ratings vector. The system also generates a noisy ratings vector for the local user, and sends a user-ratings snapshot to a recommendation server that includes the group identifier and the noisy ratings vector. The recommender system can also include the recommendation server that generates a predicted item rating for the user by performing collaborative filtering on ratings vectors from a plurality of other users that belong to the same ratings group.
    • 推荐系统可以通过对来自其他用户的商品评级进行协作过滤来为一个用户生成预测商品评级。 推荐系统可以包括与服务器接口以获得本地用户的预测项目评级的客户端设备。 客户端设备可以为用户生成标准化的等级向量,并且基于标准化的等级向量来计算用户的组标识符。 该系统还为本地用户生成噪声评估矢量,并将用户评级快照发送到包括组标识符和噪声评级矢量的推荐服务器。 推荐系统还可以包括通过对来自属于相同评级组的多个其他用户的评级矢量进行协同过滤来为用户生成预测项目评级的推荐服务器。
    • 5. 发明申请
    • PRIVACY-PRESERVING COLLABORATIVE FILTERING
    • 隐私保护协同过滤
    • US20130151540A1
    • 2013-06-13
    • US13314748
    • 2011-12-08
    • Manas Ashok PathakRichard ChowRunting ShiCong Wang
    • Manas Ashok PathakRichard ChowRunting ShiCong Wang
    • G06F17/30
    • G06Q10/101G06Q30/0282
    • A recommender system can generate a predicted item rating for one user by performing collaborative filtering on item ratings from other users. The recommender system can include a client device that interfaces with a server to obtain a predicted item rating for a local user. The client device can generate a standardized ratings vector for the user, and computes a group identifier for the user based on the standardized ratings vector. The system also generates a noisy ratings vector for the local user, and sends a user-ratings snapshot to a recommendation server that includes the group identifier and the noisy ratings vector. The recommender system can also include the recommendation server that generates a predicted item rating for the user by performing collaborative filtering on ratings vectors from a plurality of other users that belong to the same ratings group.
    • 推荐系统可以通过对来自其他用户的商品评级进行协作过滤来为一个用户生成预测商品评级。 推荐系统可以包括与服务器接口以获得本地用户的预测项目评级的客户端设备。 客户端设备可以为用户生成标准化的等级向量,并且基于标准化的等级向量来计算用户的组标识符。 该系统还为本地用户生成噪声评估矢量,并将用户评级快照发送到包括组标识符和噪声评级矢量的推荐服务器。 推荐系统还可以包括通过对来自属于相同评级组的多个其他用户的评级矢量进行协同过滤来为用户生成预测项目评级的推荐服务器。
    • 6. 发明授权
    • Implicit authentication
    • 隐式认证
    • US08312157B2
    • 2012-11-13
    • US12504159
    • 2009-07-16
    • Bjorn Markus JakobssonMark J. GrandcolasPhilippe J. P. GolleRichard ChowRunting Shi
    • Bjorn Markus JakobssonMark J. GrandcolasPhilippe J. P. GolleRichard ChowRunting Shi
    • G06F15/16
    • H04L63/102G06F21/316H04L63/0892H04L67/22H04L67/306
    • Embodiments of the present disclosure provide a method and system for implicitly authenticating a user to access controlled resources. The system receives a request to access the controlled resources. The system then determines a user behavior score based on a user behavior model, and recent contextual data about the user. The user behavior score facilitates identifying a level of consistency between one or more recent user events and a past user behavior pattern. The recent contextual data, which comprise a plurality of data streams, are collected from one or more user devices without prompting the user to perform an action explicitly associated with authentication. The plurality of data streams provide basis for determining the user behavior score, but a data stream alone provides insufficient basis for the determination of the user behavior score. The system also provides the user behavior score to an access controller of the controlled resource.
    • 本公开的实施例提供了用于隐含地认证用户以访问受控资源的方法和系统。 系统接收到访问受控资源的请求。 系统然后基于用户行为模型和关于用户的最近的上下文数据来确定用户行为得分。 用户行为分数有助于识别一个或多个最近用户事件与过去的用户行为模式之间的一致性水平。 包括多个数据流的最近的上下文数据从一个或多个用户设备收集,而不提示用户执行明确地与认证相关联的动作。 多个数据流提供用于确定用户行为得分的基础,但单独的数据流为确定用户行为得分提供了不足的基础。 该系统还向受控资源的访问控制器提供用户行为得分。
    • 7. 发明申请
    • IMPLICIT AUTHENTICATION
    • 隐含认证
    • US20110016534A1
    • 2011-01-20
    • US12504159
    • 2009-07-16
    • Bjorn Markus JakobssonMark J. GrandcolasPhilippe J. P. GolleRichard ChowRunting Shi
    • Bjorn Markus JakobssonMark J. GrandcolasPhilippe J. P. GolleRichard ChowRunting Shi
    • H04L9/32
    • H04L63/102G06F21/316H04L63/0892H04L67/22H04L67/306
    • Embodiments of the present disclosure provide a method and system for implicitly authenticating a user to access controlled resources. The system receives a request to access the controlled resources. The system then determines a user behavior score based on a user behavior model, and recent contextual data about the user. The user behavior score facilitates identifying a level of consistency between one or more recent user events and a past user behavior pattern. The recent contextual data, which comprise a plurality of data streams, are collected from one or more user devices without prompting the user to perform an action explicitly associated with authentication. The plurality of data streams provide basis for determining the user behavior score, but a data stream alone provides insufficient basis for the determination of the user behavior score. The system also provides the user behavior score to an access controller of the controlled resource.
    • 本公开的实施例提供了用于隐含地认证用户以访问受控资源的方法和系统。 系统接收到访问受控资源的请求。 系统然后基于用户行为模型和关于用户的最近的上下文数据来确定用户行为得分。 用户行为分数有助于识别一个或多个最近用户事件与过去的用户行为模式之间的一致性水平。 包括多个数据流的最近的上下文数据从一个或多个用户设备收集,而不提示用户执行明确地与认证相关联的动作。 多个数据流提供用于确定用户行为得分的基础,但单独的数据流为确定用户行为得分提供了不足的基础。 该系统还向受控资源的访问控制器提供用户行为得分。
    • 8. 发明授权
    • Privacy through artificial contextual data generation
    • 通过人工上下文数据生成隐私
    • US08266712B2
    • 2012-09-11
    • US12611684
    • 2009-11-03
    • Richard ChowPhilippe J. P. GolleRunting Shi
    • Richard ChowPhilippe J. P. GolleRunting Shi
    • G06F7/04
    • G06F21/6245
    • Embodiments of the present disclosure provide a method and system for protecting privacy by generating artificial contextual data. The system collects real contextual data related to a user. The system then generates artificial contextual data, based on the collected real contextual data. The system also groups the generated contextual data into one or more groups. Each group of contextual data corresponds to a persona that can be presented as the user's persona. Subsequently, the system transmits the generated contextual data to an entity, thereby allowing the user to obscure the real contextual data related to the user.
    • 本公开的实施例提供了一种通过生成人工上下文数据来保护隐私的方法和系统。 系统收集与用户相关的实际上下文数据。 然后,该系统基于所收集的实际上下文数据生成人工上下文数据。 系统还将生成的上下文数据分组为一个或多个组。 每组上下文数据对应于可以呈现为用户角色的角色。 随后,系统将生成的上下文数据发送到实体,从而允许用户模糊与用户相关的真实上下文数据。
    • 9. 发明申请
    • IMPLICIT AUTHENTICATION
    • 隐含认证
    • US20120137340A1
    • 2012-05-31
    • US12955825
    • 2010-11-29
    • Bjorn Markus JakobssonRichard ChowRunting Shi
    • Bjorn Markus JakobssonRichard ChowRunting Shi
    • G06F21/00
    • G06F21/316H04L63/0815H04L63/102
    • Embodiments of the present disclosure provide a method and system for implicitly authenticating a user to access controlled resources. The system first receives a request to access the controlled resource from a user. Then, the system determines whether the user request is inconsistent with regular user behavior by calculating a user behavior measure derived from historical contextual data of past user events. Next, responsive to the determined inconsistency of the user request, the system collects current contextual data of the user from one or more user devices without prompting the user to perform an explicit action for authentication. The system further updates the user behavior measure based on the collected current contextual data, and provides the updated user behavior measure to an access controller of the controlled resource to make an authentication decision based at least on the updated user behavior measure.
    • 本公开的实施例提供了用于隐含地认证用户以访问受控资源的方法和系统。 系统首先从用户接收到访问受控资源的请求。 然后,系统通过计算从过去用户事件的历史上下文数据导出的用户行为度量来确定用户请求是否与常规用户行为不一致。 接下来,响应于所确定的用户请求的不一致性,系统从一个或多个用户设备收集用户的当前上下文数据,而不提示用户执行用于认证的显式动作。 该系统还基于所收集的当前上下文数据更新用户行为测量,并且将更新的用户行为测量提供给受控资源的访问控制器,以至少基于更新的用户行为度量进行认证决定。