公开(公告)号：WO2013066573A1

公开(公告)日：2013-05-10

申请号：PCT/US2012/059302

申请日：2012-10-09

申请人： THOMSON LICENSING ,  IOANNIDIS, Stratis ,  FAWAZ, Nadia ,  DANDEKAR, Pranav

发明人： IOANNIDIS, Stratis ,  FAWAZ, Nadia ,  DANDEKAR, Pranav

IPC分类号： G06Q30/02

CPC分类号： G06Q50/265 ,  G06Q30/01 ,  G06Q30/0201 ,  G06Q30/0207

摘要： A consumer electronic device hosts a media application that obtains media content use data for a user. The media application interfaces with a server that analyzes the media content use-related data based on a budget-constrained DCLEF and/or a distortion-constrained DCLEF mechanism. The user is then compensated for their disclosed use data based on the severity of the privacy incursion.

摘要翻译： 消费者电子设备托管获得用户的媒体内容使用数据的媒体应用。 媒体应用程序与基于预算约束的DCLEF和/或失真约束DCLEF机制分析媒体内容使用相关数据的服务器进行接口。 然后根据隐私侵入的严重程度来补偿用户公开的使用数据。

公开(公告)号：WO2015026384A1

公开(公告)日：2015-02-26

申请号：PCT/US2013/071284

申请日：2013-11-21

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

发明人： FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

IPC分类号： G06F21/62

CPC分类号： G06F21/6245

摘要： The present principles focus on the privacy-utility tradeoff encountered by a user who wishes to release some public data (denoted by X) to an analyst, that is correlated with his private data (denoted by S), in the hope of getting some utility. The public data is distorted before its release according to a probabilistic privacy preserving mapping mechanism, which limits information leakage under utility constraints. In particular, this probabilistic privacy mechanism is modeled as a conditional distribution, P_(Y|X), where Y is the actual released data to the analyst. The present principles design utility-aware privacy preserving mapping mechanisms against inference attacks, when only partial, or no, statistical knowledge of the prior distribution, P_(S,X), is available. Specifically, using maximal correlation techniques, the present principles provide a separability result on the information leakage that leads to the design of the privacy preserving mapping.

摘要翻译： 本原理侧重于希望向分析师发布一些公共数据（由X表示）的用户遇到的隐私 - 应用程序折中，这与他的私人数据（由S表示）相关，希望获得一些实用程序 。 根据概率隐私保护映射机制，公开数据在发布前会发生扭曲，这种机制限制了公用事业限制下的信息泄露。 特别地，这个概率隐私机制被建模为条件分布P_（Y | X），其中Y是到分析者的实际发布数据。 目前的原理设计实用意识隐私保护映射机制针对推理攻击，只有部分或不存在先验分布P_（S，X）的统计知识可用。 具体来说，使用最大相关技术，本原理提供信息泄漏的可分离性结果，导致隐私保护映射的设计。

公开(公告)号：WO2014031551A1

公开(公告)日：2014-02-27

申请号：PCT/US2013/055628

申请日：2013-08-19

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  CALMON, Flavio, Du Pin

发明人： FAWAZ, Nadia ,  CALMON, Flavio, Du Pin

IPC分类号： G06F21/62

CPC分类号： G06F21/6245

摘要： A method for generating a privacy-preserving mapping commences by characterizing an input data set Y with respect to a set of hidden features S. Thereafter, the privacy threat is modeled to create a threat model, which is a minimization of an inference cost gain on the hidden features S. The minimization is then constrained by adding utility constraints to introduce a privacy/accuracy trade-off. The threat model is represented with a metric related to a self-information cost function. Lastly, the metric is optimized to obtain an optimal mapping, in order to provide a mapped output U, which is privacy-preserving.

摘要翻译： 通过对一组隐藏特征S表征输入数据集Y，开始生成隐私保护映射的方法。此后，对隐私威胁进行建模以创建威胁模型，该威胁模型是推理成本增益的最小化 隐藏特征S.然后，通过增加效用约束来限制最小化以引入隐私/精确度权衡。 威胁模型用与自我信息成本函数相关的指标表示。 最后，该度量被优化以获得最佳映射，以便提供保护隐私的映射输出U。

公开(公告)号：WO2014200472A1

公开(公告)日：2014-12-18

申请号：PCT/US2013/045343

申请日：2013-06-12

申请人： THOMSON LICENSING ,  BHAMIDIPATI, Sandilya ,  FAWAZ, Nadia

发明人： BHAMIDIPATI, Sandilya ,  FAWAZ, Nadia

IPC分类号： H04N21/2547 ,  H04N21/258 ,  H04N21/262 ,  H04N21/2665 ,  H04N21/2668 ,  H04N21/81 ,  G06F17/30 ,  G06Q30/02

CPC分类号： H04N21/4667 ,  G06F17/30029 ,  G06Q30/02 ,  G06Q30/0242 ,  G06Q30/0269 ,  G06Q30/0275 ,  H04N21/252 ,  H04N21/2547 ,  H04N21/25891 ,  H04N21/26258 ,  H04N21/2665 ,  H04N21/2668 ,  H04N21/812 ,  H04N21/8133

摘要： A method and system of recommending content and targeting advertisements for one or more users is provided. The system includes an aggregator that is connected to the one or more users and collects rich user data therefrom. The method includes collecting rich user data from one or more users; building one or more user profiles corresponding to the one or more users; storing the one or more user profiles in a memory database; requesting one or more content profiles from one or more providers; receiving the one or more content profiles; determining whether one of the user profiles is a target user profile for one of the content profiles based on the rich user data associated with the target user profile; and delivering content programs associated with the content profiles to the target user.

摘要翻译： 提供了为一个或多个用户推荐内容和定向广告的方法和系统。 该系统包括连接到一个或多个用户并从其收集丰富的用户数据的聚合器。 该方法包括从一个或多个用户收集丰富的用户数据; 构建与所述一个或多个用户对应的一个或多个用户简档; 将所述一个或多个用户简档存储在存储器数据库中; 从一个或多个提供者请求一个或多个内容简档; 接收一个或多个内容简档; 基于与所述目标用户简档相关联的所述富用户数据，确定所述用户简档之一是否是所述内容简档之一的目标用户简档; 以及将与所述内容简档相关联的内容节目传送给所述目标用户。

公开(公告)号：WO2015026385A1

公开(公告)日：2015-02-26

申请号：PCT/US2013/071287

申请日：2013-11-21

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

发明人： FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

IPC分类号： G06F21/62

CPC分类号： G06F21/6245

摘要： The present embodiments focus on the privacy-utility tradeoff encountered by a user who wishes to release some public data to an analyst, which is correlated with his private data, in the hope of getting some utility. When multiple data are released to one or more analyst, we design privacy preserving mappings in a decentralized fashion. In particular, each privacy preserving mapping is designed to protect against the inference of private data from each of the released data separately. Decentralization simplifies the design, by breaking one large joint optimization problem with many variables into several smaller optimizations with fewer variables.

摘要翻译： 本实施例侧重于希望将一些公共数据发布给与他的私人数据相关联的分析者的用户遇到的隐私 - 应用程序折中，以期获得某种效用。 当一个或多个分析师发布多个数据时，我们以分散的方式设计隐私保护映射。 特别地，每个隐私保护映射被设计为分别防止每个发布的数据对私人数据的推断。 权力下放简化了设计，通过将许多变量的一个大联合优化问题分解成具有较少变量的几个较小优化。

公开(公告)号：WO2014124175A1

公开(公告)日：2014-08-14

申请号：PCT/US2014/015159

申请日：2014-02-06

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  SALAMATIAN, Salman ,  CALMON, Flavio, Du Pin ,  BHAMIDIPATI, Subrahmanya, Sandilya ,  OLIVEIRA, Pedro, Carvalho ,  TAFT, Nina, Anne ,  KVETON, Branislav

发明人： FAWAZ, Nadia ,  SALAMATIAN, Salman ,  CALMON, Flavio, Du Pin ,  BHAMIDIPATI, Subrahmanya, Sandilya ,  OLIVEIRA, Pedro, Carvalho ,  TAFT, Nina, Anne ,  KVETON, Branislav

IPC分类号： H04L29/06 ,  H04L29/08 ,  G06F21/62

CPC分类号： H04L63/04 ,  G06F17/30598 ,  G06F21/60 ,  G06F21/6254 ,  G06N7/005 ,  H04L63/0407 ,  H04L63/1441 ,  H04L67/306

摘要： A methodology to protect private data when a user wishes to publicly release some data about himself, which is can be correlated with his private data. Specifically, the method and apparatus teach comparing public data with survey data having public data and associated private data. A joint probability distribution is performed to predict a private data wherein said prediction has a certain probability. At least one of said public data is altered or deleted in response to said probability exceeding a predetermined threshold.

摘要翻译： 当用户希望公开发布一些关于自己的数据的方法来保护私人数据，这可以与他的私人数据相关联。 具体地，该方法和装置教导将公共数据与具有公共数据和相关私人数据的调查数据进行比较。 执行联合概率分布以预测其中所述预测具有一定概率的专用数据。 响应于所述概率超过预定阈值，至少一个所述公共数据被改变或删除。

公开(公告)号：WO2014088903A1

公开(公告)日：2014-06-12

申请号：PCT/US2013/072165

申请日：2013-11-27

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  NIKOLOV, Aleksandar Todorov

发明人： FAWAZ, Nadia ,  NIKOLOV, Aleksandar Todorov

IPC分类号： H04L9/00

CPC分类号： G06F21/60 ,  G06F17/14 ,  G06F17/153 ,  G06F21/6245 ,  H04L9/00

摘要： A method and apparatus for ensuring a level of privacy for answering a convolution query on data stored in a database is provided. The method and apparatus includes the activities of determining (402) the level of privacy associated with at least a portion of the data stored in the database and receiving (404) query data, from a querier, for use in performing a convolution over the data stored in the database. The database is searched (406) for data related to the received query data and the data that corresponds to the received query data is retrieved (408) from the database. An amount of noise based on the determined privacy level is generated (410) and added (412) to the retrieved data to create noisy data which is then communicated (414) to the querier.

摘要翻译： 提供了一种用于确保对存储在数据库中的数据进行卷积查询的隐私级别的方法和装置。 该方法和装置包括确定（402）与数据库中存储的数据的至少一部分相关联的隐私级别的活动，以及从查询器接收（404）查询数据，以用于对数据执行卷积 存储在数据库中。 搜索数据库（406）以获得与接收到的查询数据相关的数据，并从数据库检索与接收到的查询数据相对应的数据（408）。 基于确定的隐私级别产生（410）噪声量并将其添加（412）到所检索的数据中，以产生噪声数据，然后将其传送给查询器（414）。

公开(公告)号：WO2013025460A1

公开(公告)日：2013-02-21

申请号：PCT/US2012/050246

申请日：2012-08-10

申请人： THOMSON LICENSING ,  BENTO AYRES PEREIRA, Jose ,  FAWAZ, Nadia ,  MONTANARI, Andrea ,  IOANNIDIS, Stratis

发明人： BENTO AYRES PEREIRA, Jose ,  FAWAZ, Nadia ,  MONTANARI, Andrea ,  IOANNIDIS, Stratis

IPC分类号： G06Q50/00

CPC分类号： G06N7/005 ,  G06F17/30035 ,  G06N99/005 ,  H04N21/441 ,  H04N21/44222 ,  H04N21/4756

摘要： Disclosed are methods and apparatus for identifying users of content. The methods include identifying contextual information of a group of users, gathering user access data of the users on the basis of the contextual information of the group of users, analyzing temporal information of the user access data, and identifying particular users in the group of users on the basis of the analyzed temporal information and the contextual information.

摘要翻译： 公开了用于识别内容的用户的方法和装置。 所述方法包括识别一组用户的上下文信息，基于用户组的上下文信息收集用户的用户访问数据，分析用户访问数据的时间信息，以及识别用户组中的特定用户 在分析的时间信息和上下文信息的基础上。

公开(公告)号：WO2015026386A1

公开(公告)日：2015-02-26

申请号：PCT/US2013/071290

申请日：2013-11-21

申请人： THOMSON LICENSING ,  FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

发明人： FAWAZ, Nadia ,  KAKHAKI, Abbasali Makhdoumi

IPC分类号： G06F21/62

CPC分类号： G06F21/6245

摘要： The present embodiments focus on the privacy-utility tradeoff encountered by a user who wishes to release some public data (denoted by X) to an analyst, that is correlated with his private data (denoted by S), in the hope of getting some utility. When noise is added as a privacy preserving mechanism, that is, Y=X+N, where Y is the actual released data to the analyst and N is noise, we show that adding Gaussian noise is optimal under l_2-norm distortion for continuous data X. We denote the mechanism of adding Gaussian noise that minimizes the worst-case information leakage by Gaussian mechanism. The parameters for Gaussian mechanism are determined based on the eigenvectors and eigenvalues of the covariance of X. We also develop a probabilistic privacy preserving mapping mechanism for discrete data X, wherein the random discrete noise follows a maximum-entropy distribution.

摘要翻译： 本实施例侧重于希望将一些公共数据（由X表示）的用户遇到的与他的私人数据（由S表示）相关联的分析者遇到的隐私 - 应用程序折衷，以期获得某些实用程序 。 当噪声作为隐私保护机制加入时，即Y = X + N，其中Y是分析人员的实际释放数据，N是噪声，我们表明，在连续数据的l_2范数失真下，增加高斯噪声是最优的 我们表示加高斯噪声的机制，通过高斯机制最小化最坏情况的信息泄漏。 基于X的协方差的特征向量和特征值来确定高斯机制的参数。我们还为离散数据X开发了概率隐私保留映射机制，其中随机离散噪声遵循最大熵分布。

公开(公告)号：WO2014200468A1

公开(公告)日：2014-12-18

申请号：PCT/US2013/045297

申请日：2013-06-12

申请人： THOMSON LICENSING ,  BHAMIDIPATI, Sandilya ,  FAWAZ, Nadia ,  WHITEAKER, Jonathan, Brooks

发明人： BHAMIDIPATI, Sandilya ,  FAWAZ, Nadia ,  WHITEAKER, Jonathan, Brooks

IPC分类号： G06F17/30

CPC分类号： G06F17/30268 ,  G06F17/30247 ,  G06F17/30265 ,  G06F17/3028 ,  G06F17/30377 ,  G06F17/30864 ,  G06F17/30867

摘要： A method comprising receiving an image, the image including associated contextual information; converting the received image into searchable image data, the searchable image data being descriptive of the received image; filtering information from a search database based on the contextual information associated with the received image to create a filtered information set; collecting a plurality of images from the filtered information set to create a seed data set; comparing the received image to the plurality of images from the seed data set using the searchable image data; and determining whether one of the plurality of images is related to the received image.

摘要翻译： 一种方法，包括接收图像，所述图像包括相关联的上下文信息; 将所接收的图像转换成可搜索的图像数据，所述可搜索图像数据描述所接收的图像; 基于与所接收的图像相关联的上下文信息从搜索数据库中过滤信息以创建过滤的信息集; 从所述过滤的信息集合中收集多个图像以创建种子数据集; 使用所述可搜索图像数据将所接收的图像与来自所述种子数据集的所述多个图像进行比较; 以及确定所述多个图像中的一个是否与所接收的图像相关。