5110 results about "Privacy protection" patented technology

A method executed by a computer includes receiving an image from a client device. A facial recognition technique is executed against an individual face within the image to obtain a recognized face. Privacy rules are applied to the image, where the privacy rules are associated with privacy settings for a user associated with the recognized face. A privacy protected version of the image is distributed, where the privacy protected version of the image has an altered image feature.

An individual is identified in a photograph. A portion of the photograph is temporarily blurred to prevent the individual from being recognized. Once consent is received for the tag, the blur is removed. However, if consent is not received, the blur remains.

The invention provides a method and system for privacy protection of block chain transaction. The method comprises: a transaction group is established between nodes of a block chain system, a user establishes an account at a node, and the node generates public and private key information of the account and then joining of a group is carried out; a transaction request node encrypts transaction information by using a broadcast encryption algorithm, carries out group signature processing on the encrypted transaction information, and then broadcasts the transaction information after broadcast encryption and group signature processing; a common non-account-recording node verifies the transaction information and then broadcasts the transaction information, an account-recording node decrypts thetransaction information and performs an intelligent contract to carry out account recording, broadcast encryption is carried out and then the information is recorded into a public account book, wherein the stored data are only allowed to be opened by the account-recording node, the transaction request node and an administration node. With the broadcast encryption algorithm and group signature technology, a privacy protection problem in the block chain system is solved and the traceability of the transaction is ensured.

The invention discloses a blockchain data processing method, device and system. The blockchain data processing method comprises that a first node identifies whether received block information needs privacy protection processing; if the received block information needs privacy protection processing, a secret key of a plaintext encryption algorithm is generated, the block information is encrypted by means of the plaintext encryption algorithm employing the secret key, and encrypted block information is generated; the secret key is encrypted in a stipulated way, a secret key ciphertext is generated, the stipulated way comprises an algorithm through which a second node associated with the first node in the first node and the blockchain encrypts and decrypts the secret key ciphertext according to a preset mode; and data including the encrypted block information and the secret key ciphertext is stored a corresponding block of the blockchain as blockchain data. According to each embodiment of the invention, information data stored in the blockchain can be encrypted, so that only specific members can decrypt and check the information data, and the aim of carrying out privacy protection on special transaction information is achieved.

A method for operating a building management system includes: identifying a movement-pattern from a sensed attribute at a first sensor; determining a behavior-pattern at the first sensor when the movement-pattern matches a template-pattern; transmitting the behavior-pattern and the sensed attribute from the first sensor to a second sensor; and tracking the sensed attribute at the second sensor for displaying on a device.

A security system which is nonintrusive of personal privacy of a person in a space comprises at least a first localization sensor subsystem, if any, in the possession of the person; a video surveillance subsystem arranged and configured to collect visual data related to the person in the space; and a computer subsystem coupled to the localization sensor subsystem and video surveillance subsystem to associate a predetermined privacy level with the localization sensor subsystem, and to provide an access control privilege with the localization sensor subsystem, the computer subsystem determining how to present, store and/or retrieve the visual data while meeting predetermined the privacy level associated with the person.

A privacy-preserving index system addresses the problem of providing a privacy-preserving search over distributed access-controlled content. Indexed documents can be readily reconstructed from inverted indexes used in the search. The privacy-preserving index system builds a centralized privacy-preserving index in conjunction with a distributed access-control enforcing search protocol. The privacy-preserving index utilizes a randomized algorithm for constructing a privacy-preserving index. The privacy-preserving index is strongly resilient to privacy breaches. The privacy-preserving index system allows content providers to maintain complete control in defining access groups and ensuring its compliance, and further allows system implementors to retain tunable knobs to balance privacy and efficiency concerns for their particular domains.

The invention discloses an electronic medical record storage and sharing model and method based on the blockchains and solves problems of patient's rights of access to personal medical data and insecure storage and sharing of sensitive medical data in the prior art. The model is characterized by comprising data creators, data owners, cloud storage, federated blockchains and data consumers, whereinthe blockchain is a control center. The method comprises steps that system initialization is performed; medical data are acquired, and data storage with intercepted signatures is employed; data publishing with the improved DPOS consensus mechanism is employed; data sharing based on smart contracts is performed. The method is advantaged in that security, reliability, privacy protection and securestorage are achieved, in combination with the cloud storage technology and the interceptable signature technology, in the federated blockchains, users can set sharing conditions through the smart contracts, safe and effective data sharing and access can be realized, and strong practicality is achieved.

The invention discloses a block chain information archiving and privacy protection method. The block chain information archiving and privacy protection method comprises the steps of adding random number generation Hash values to information needing archiving; then signing by an interest-related person or a eyewitness and generating Hash values; and finally recording at a block chain. Some information needing archiving is formatting and separable formatting information and self-filling information respectively stored and subjected to Hash verification, such as gap-filling information, selection information, postscript information, random number information (for preventing brute force attack). Data which are encrypted by using a public key only can be decrypted by a relevant person who knows the original information by using a private key; a third party verifies true and false of the information; and the encrypted information can be disclosed for a judicial institution if judiciary involvement is needed.

The invention belongs to the technical field of artificial intelligence, and relates to a combined deep learning training method based on a privacy protection technology. The efficient combined deep learning training method based on the privacy protection technology is achieved. In the invention, each participant first trains a local model on a private data set to obtain a local gradient, then performs Laplace noise disturbance on the local gradient, encrypts the local gradient and sends the encrypted local gradient to a cloud server; The cloud server performs aggregation operation on all thereceived local gradients and the ciphertext parameters of the last round, and broadcasts the generated ciphertext parameters; And finally, the participant decrypts the received ciphertext parameters and updates the local model so as to carry out subsequent training. According to the method, a homomorphic encryption scheme and a differential privacy technology are combined, a safe and efficient deep learning training method is provided, the accuracy of a training model is guaranteed, and meanwhile a server is prevented from inferring model parameters, training data privacy and internal attacksto obtain private information.

Techniques for providing privacy protection are provided. A query is received. Privacy policy information, extracted knowledge and optional information about available public information are determined. Information about the knowledge extraction transformations applied to create the extracted knowledge and the source data is determined. Privacy protecting transformations are determined and applied to transform the extracted knowledge based on the selected privacy policy, optional information about available public information, the characteristics of the applied knowledge extractions transformations, the source data and optional previous user queries.

A method for using a location-based service while preserving anonymity includes receiving a location associated with a mobile node, receiving an anonymity level associated with the mobile node, computing a region containing the location of the mobile node and a number of footprints based on the anonymity level, wherein each of the footprints from a different user, and providing the region to a location-based service to thereby preserve anonymity of the mobile node. A method also allow a mobile device or its user to specify the anonymity level by selecting a public region consistent with a user's feelings towards desired privacy.

The invention discloses a blockchain-based digital asset processing method and device. The method comprises the following steps: receiving private ciphertext for a digital asset circulated from a sending end to a receiving end through a blockchain, and a preset public key; and obtaining a sharing public key for sharing the private ciphertext based on the preset public key, so that when the private ciphertext and the sharing public key are broadcast in the blockchain, blockchain nodes on the blockchain can share the private ciphertext based on the sharing public key and reach a blind consensus on the shared private ciphertext, and after the consensus on the private ciphertext is reached, the private ciphertext can be decrypted by at least one of three parties, i.e., the sending end, the receiving end and a monitoring end, based on a preset private key to obtain plaintext of the digital asset. The method and device provided by the embodiment of the invention has the advantages that the privacy right of a user is protected; under the premise of privacy protection, the single general digital asset can be smoothly circulated within one blockchain or among multiple blockchains, and a total currency amount remains unchanged; and a monitoring party other than the transaction parties can monitor transaction information at any time.

A database has a plurality of entries and a plurality of attributes common to each entry, where each entry corresponds to an individual. A query q is received from a querying entity query q and is passed to the database, and an answer a is received in response. An amount of noise e is generated and added to the answer a to result in an obscured answer o, and the obscured answer o is returned to the querying entity. Thus, a level of protection of privacy is provided to each individual represented within the database.

The invention discloses a multi-center block chain transaction privacy protection system and method. The system comprises an alliance control module, an amount verification module, a range verification module, an encryption module, a decryption module and a block chain system transaction module, wherein the alliance control module is used for generating alliance parameters by multiple participants; the amount verification module is used for verifying that input and output of an encrypted ciphertext amount in a transaction are equal; the range verification module is used for verifying that theencrypted ciphertext amount in the transaction is in a specific interval and is constantly positive; the encryption module and the decryption module are used for carrying out homomorphic encryption and decryption on the amount in transmission and reception processes; and the block chain system transaction module is used for complete bitcoin-like digital currency transaction systems, and has a complete transaction process which comprises transmission, reception, broadcasting and block confirmation. The system is capable of enhancing general structures through block chain transaction privacies under a multi-center supervision mode, so as to realize privacy protection for trapdoor parameters under joint control of multiple parties and transaction metadata in transaction process, and effectively strengthen the safety of plaintext amounts in multi-center block chain system transaction process.

A personal online information management system allows users to monitor, manage, retrieve, and utilize their personal online behaviors such as browsing, searching, editing/commenting, discussion, shopping, and peer to peer communications. The system provides personalized service with explicitly self-controlled privacy protection. The system enables an anonymous or identified user to easily switch between a monitored mode and an un-monitored mode.

An image processing device includes a face detector configured to detect a face based on a taken image, and an output processor configured to have a function to execute privacy-mask processing for privacy protection for an image of a face detected by the face detector or an image of a background of the face. The output processor includes a function to separately output an image of a face detected by the face detector and an image of a background of the face which are each subjected to or not subjected to the privacy-mask processing.

The invention discloses a user data reconstruction attack method oriented to deep federal learning, which can reconstruct private data of a specific user and consider that attacks are implemented by amalicious server, so that negative effects are prevented from being introduced into an original shared model compared with a conventional attack method which can only reconstruct category representation data. Furthermore, the method introduces a multi-task generative adversarial model to simulate the distribution of user data, and the model is used for training the authenticity and category of aninput sample and the identification of the user identity to which the model belongs, so that the quality of the generated sample is improved. In order to better distinguish different users, the method introduces an optimized user data representative calculation method to describe user characteristics participating in federal learning, and the method is used for supervising training of a generative adversarial model. For an existing federal learning architecture concerning privacy protection, privacy leakage can be caused by a data reconstruction attack based on a multi-task generative adversarial model provided by the invention.