Protegrity Corporation

Protegrity US Holding, LLC

Yigal Rozenberg

Ulf Mattsson

Vichai Levy

Rajnish Jain

Raul Ortega

David Clyde Williamson

Jan Boberg

Pierre Burlin

Lingling Yan

Hans Meijer

George Curran

Denis Scherbakov

Fredrik Mörtberg

A gateway device for implementing data security is described herein. The gateway device is coupled between a client device and a server device, and generates a mapping between portions of data received from a client device and interface fields or data elements of the client device. Upon receiving subsequent data from the client device, the gateway device can access the generated mapping to identify portions of the subsequent data corresponding to particular interface fields or data elements of the client device using the mapping, and can encode the identified portions of the subsequent data, for instance based on data protection techniques defined by a security policy. The encoded data can then be outputted by the gateway device to the server device.

Mapping between user interface fields and protocol information

Unicode data can be protected in a distributed tokenization environment. Data to be tokenized can be accessed or received by a security server, which instantiates a number of tokenization pipelines for parallel tokenization of the data. Unicode token tables are accessed by the security server, and each tokenization pipeline uses the accessed token tables to tokenization a portion of the data. Each tokenization pipeline performs a set of encoding or tokenization operations in parallel and based at least in part on a value received from another tokenization pipeline. The outputs of the tokenization pipelines are combined, producing tokenized data, which can be provided to a remote computing system for storage or processing.

Parallel Unicode tokenization in a distributed network environment

A gateway device for implementing data security is described herein. The gateway device is coupled between a client device and a server device, and is configured to receive encoded data and a set of operations from the server device in response to a request for cloud services from the client device. The gateway device is configured to decode the encoded data, and to provide the decoded data and the set of operations to the client device. The client device is configured to perform the set of operations on the decoded data, and to incorporate the operation results into an application or interface corresponding to the requested cloud service. The gateway device is configured to encode the operation result data, and to provide the encoded operation result data to the server device for storage.

Data computation in a multi-domain cloud environment

A gateway device includes a network interface connected to data sources, and computer instructions, that when executed cause a processor to access data portions from the data sources. The processor accesses classification rules, which are configured to classify a data portion of the plurality of data portions as sensitive data in response to the data portion satisfying the rule. Each rule is associated with a significance factor representative of an accuracy of the classification rule. The processor applies each of the set of classification rules to a data portion to obtain an output of whether the data is sensitive data. The output are weighed by significance factors to produce a set of weighted outputs. The processor determines if the data portion is sensitive data by aggregating the set of weighted outputs, and presents the determination in a user interface. Security operations may also be performed on the data portion.

Sensitive data classification

Access to a shared library API is restricted for a customer application by a security system. A profile for each of a plurality of trusted applications is generated and stored in a security database. When a customer application attempts to access the shared library API, the customer application is verified by extracting a customer application profile for the customer application, comparing the customer application profile with each stored trusted application profile, and verifying that the customer application can access the shared library API based on the comparison. Based on the verification, the customer application may be allowed to or access to the shared library API or may be prevented from accessing the shared library API.

Enforcing trusted application settings for shared code libraries

Data can be protected in a centralized tokenization environment. A security value is received by a central server from a client device. The central server accesses a token table corresponding to the client device and generates a reshuffled static token table from the accessed token table based on the received security value. When the client device subsequently provides data to be protected to the central server, the central server tokenizes the provided data using the reshuffled static token table and stores the tokenized data in a multi-tenant database. By reshuffling token tables using security values unique to client devices, the central server can protect and store data for each of multiple tenants such that if the data of one tenant is compromised, the data of each other tenant is not compromised.

Multi-tenant data protection in a centralized network environment

Database entries can be protected by indexing the entries using a plurality of indexes, each associated with a level of access rights. A level of access rights can be determined from a search query, and an index can be selected based on the determined level of access rights. A search key can be generated based on the received query, and the selected index can be searched using the search query. Database entries mapped to the values of the selected index returned in response to the search can be outputted. Each index is associated with a different granularity defining the number and/or ambiguity of search results returned in response to searching an index.

Privacy preserving data search

New tokenization tables are derived at intervals in order to increase the security of tokenized data that is transferred between two endpoints. Generation of the new tokenization tables is based on previous tokenization tables, which advantageously allows the generation process to be performed locally at the two endpoints independently of an external tokenization table provider. New tokenization tables can periodically be distributed to the endpoints as a new starting point for derivation.

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Wilton, CT, United States of America

Yigal Rozenberg