Anonos Inc.

Ften, Inc.

Anonos IP LLC

Ted N Myerson

Malcolm Gary LaFever

Steven Mason

Douglas Guy Kittelsen

Anandan Murali Prasad

Corby Drake Angle

Lee A Cole

Howard Kaushansky

Samantha L Hampton

Mark Little

Colin W Wetherbee

Malcolm Gary Lafever

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity and security by enabling subjects to which data pertains to remain 'dynamically anonymous,' i.e., anonymous for as long as is desired—and to the extent that is desired—are disclosed herein. Embodiments include systems that create, access, use, store and/or erase data with increased privacy, anonymity, and security—thereby facilitating the availability of more qualified and accurate information. When personal data is authorized by data subjects to be shared with third parties, embodiments described herein may facilitate the sharing of information in a dynamically-controlled manner that also enables the delivery of temporally-, geographically-, and/or purpose-limited information to the receiving party. In one example, the disclosed techniques may be used to functionally separate geospatial information, such that it remains “dynamically anonymous,” i.e., anonymous for as long as is desired—and to the extent or degree that is desired.

Systems and methods for dynamic de-identification and anonymity for user input to artificial intelligence (AI)-based models

Systems, program storage devices, and methods for improving data privacy/trust/anonymity/pseudonymity and data value, wherein data related to a Data Subject can be used and stored, while minimizing re-identification risk by unauthorized parties and enabling data related to the Data Subject to be disclosed to an authorized party by granting access only to the data relevant to that authorized party's purpose, time, place, and/or other criterion via the obfuscation of specific data values. The techniques described herein maintain this level of privacy/trust/anonymity/pseudonymity, while empowering Data Subjects, e.g., consumers or customers of such authorized parties, by enabling protection of data at the desired level of engagement with various business entities. The techniques described herein also allow Data Controllers to perform General Data Protection Regulation (GDPR) and Schrems II-compliant (and surveillance-proof) data processing, via the functional separation of heterogeneous data (e.g., via the use of 'Variant Twins') from embedded trust and privacy controls.

Systems and methods for functionally separating heterogeneous data for analytics, artificial intelligence, and machine learning in global data ecosystems

Systems, computer-readable media, and methods for improving data privacy/anonymity and data value, wherein data related to a data subject can be used and stored, while minimizing re-identification risk by unauthorized parties and enabling data related to the data subject to be disclosed to an authorized party by granting access only to the data relevant to that authorized party's purpose, time period, place, and/or other criterion via the obfuscation of specific data values. The techniques described herein maintain this level of privacy/anonymity, while still empowering Data Subjects, e.g., consumers or customers of such authorized parties, by enabling them to request or specify their desired level of engagement with various business entities. Data Subjects may then receive privacy-respectful, trusted communication, e.g., advertising materials, based on their inclusion in dynamically changing and/or temporally-limited cohorts or microsegments ('MSegs') of individuals sharing similar characteristics and having a sufficient size to satisfy anonymity, e.g., 'k-anonymity,' requirements.

Systems and methods for enforcing privacy-respectful, trusted communications

Data transaction-specific data packets transmitted over a data communications network from a plurality of source computer nodes are processed. A first data packet communication session is established between one source computer node and one destination computer node to transport data transaction specific data packets over a first path through the data communications network. A second alternative data packet communication session is established between the one source computer node and the one destination computer node to transport data transaction specific data packets over a second path that is different from and bypasses the first path. When a condition based on the data transaction-specific data packets is identified, electronic processing circuitry initiates an alteration of the first data packet communication session. After that, the electronic processing circuitry determines whether any data transaction specific data packets associated with the second alternative data packet communication session continue to travel from the one source computer node to the one destination computer node over the second path.

Processing over alternate communication sessions between a source node and a destination node having different paths in a communications network

Systems, computer-readable media, and methods for improving data privacy/anonymity and data value, wherein data related to a data subject can be used and stored, while minimizing re-identification risk by unauthorized parties and enabling data related to the data subject to be disclosed to an authorized party by granting access only to the data relevant to that authorized party's purpose, time period, place and/or other criterion via the obfuscation of specific data values. The techniques described herein maintain this level of privacy/anonymity, while still empowering Data Subjects, e.g., consumers or customers of such authorized parties, e.g., business entities, by enabling them to request or specify their desired level of engagement with such business entities. Data Subjects may then receive privacy-respectful, trusted communication, e.g., advertising materials, based on their inclusion in dynamically changing cohorts or microsegments ('MSegs') of individuals sharing similar characteristics and having a sufficient size to satisfy, e.g., 'k-anonymity' requirements.

Example embodiments include a method and system for managing intraday risk conditions. Data transaction specific data messages transmitted over a data communications network from a plurality of source nodes trading an article of trade with a plurality of destination nodes are processed. The messages include account parameter information. Intraday risk condition data is associated in memory with entity identification data associated with an entity. Using the entity identification data, account parameter information included in the processed data transaction specific data messages is identified that matches the intraday risk condition data for the entity. In response to an identified match, a data transaction involving the entity submitted via a communication session to a corresponding one of the plurality of destination nodes is modified to reduce intraday risk for the entity associated with the data transaction.

Method and system for processing intraday risk parameters over a communications network

Systems, computer-readable media, and methods for improving both data privacy/anonymity and data value, wherein data related to a data subject can be used and stored, e.g., in a distributed ledger data structure, such as a blockchain, while minimizing re-identification risk by unauthorized parties and enabling data, including quasi-identifiers, related to the data subject to be disclosed to any authorized party by granting access only to the data relevant to that authorized party's purpose, time period, place and/or other criterion via the obfuscation of specific data values, e.g., pursuant to the European Union's General Data Protection Regulation (GDPR) or other similar regulatory schemes. The techniques described herein maintain this level of privacy/anonymity while still satisfying the immutability, auditability, and verification mandated by blockchain and other distributed ledger technologies (DLTs) for the decentralized storage of transactional data. Such systems, media, and methods may be implemented on both classical and quantum computing devices.

Systems and methods for enforcing centralized privacy controls in de-centralized systems

Systems, computer-readable media, and methods for improving both data privacy/anonymity and data value, wherein real-world, synthetic, or other data related to a data subject can be used while minimizing re-identification risk by unauthorized parties and enabling data, including quasi-identifiers, related to the data subject to be disclosed to any authorized party by granting access only to the data relevant to that authorized party's purpose, time period, purpose, place and/or other criterion via the required obfuscation of specific data values, e.g., pursuant to the GDPR or HIPAA, by incorporating a given range of those values into a cohort, wherein only the defined cohort values are disclosed to the given authorized party. Privacy policies may include any privacy enhancement techniques (PET), including: data protection, dynamic de-identification, anonymity, pseudonymity, granularization, and/or obscurity policies. Such systems, media and methods may be implemented on both classical and quantum computing devices.

Systems and methods for enhancing data protection by anonosizing structured and unstructured data and incorporating machine learning and artificial intelligence in classical and quantum computing environments

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity, and security by enabling subjects to which data pertains to remain 'dynamically anonymous,' i.e., anonymous for as long as is desired&#x2014;and to the extent desired&#x2014;are disclosed herein. This concept is also referred to herein as 'anonosizing.' In some embodiments, the anonosizing of data may be implemented by encoding and decoding data under controlled conditions to support specific uses within designated authorized contexts. By anonosizing data controls via &#x201c;identifying&#x201d; and/or &#x201c;associating&#x201d; data elements within a population, data uses may be restricted to only those uses permissioned by a data subject or authorized third party. If new authorized data uses arise, all original data value and utility may be retained to support them&#x2014;to the extent authorized by a data subject or authorized third party&#x2014;but inappropriate, i.e., non-permissioned, uses of identifying information may be prevented.

Systems and methods for anonosizing data

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity, and security by enabling subjects to which data pertains to remain 'dynamically anonymous,' i.e., anonymous for as long as is desired&#x2014;and to the extent that is desired&#x2014;are disclosed herein. This concept is also referred to herein as Just-In-Time-Identity, or 'JITI.' Embodiments include systems that create, access, use, store and/or erase data with increased privacy, anonymity and security&#x2014;thereby facilitating the availability of more qualified information&#x2014;via the use of temporally unique, dynamically changing de-identifiers (&#x201c;DDIDs&#x201d;). In some embodiments, specialized JITI keys may be used to &#x201c;unlock&#x201d; different views of the same DDID (or its underlying value), thereby providing granular control over the level of detail or obfuscation visible to each user based on the context of said user's authorized use of data, e.g., authorized purpose(s), place(s), time(s), or other attributes of the use.

Systems and methods for contextualized data protection

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity and security by enabling subjects to which data pertains to remain 'dynamically anonymous,' i.e., anonymous for as long as is desired&#x2014;and to the extent that is desired&#x2014;are disclosed herein. Embodiments include systems that create, access, use, store and/or erase data with increased privacy, anonymity and security, thereby facilitating the availability of more qualified and accurate information. When data is authorized by subjects to be shared with third parties, embodiments may facilitate sharing information in a dynamically controlled manner that enables delivery of temporally-, geographically-, and/or purpose-limited information to the receiving party. In one example, anonymity measurement scores may be calculated for the shared data elements so that a level of consent/involvement required by the Data Subject before sharing the relevant data elements to third parties may be specified.

Dynamic de-identification and anonymity

In at least one embodiment, a method and system associated with financial articles of trade may include comparing relevant portions of data pertaining to an attempted transaction, wherein the transaction may pertain to one in which an entity is financially liable but unaware. At least one embodiment includes monitoring market transaction activity data to determine when a trading entity has exceeded an aggregated limit, such as one or more trading sub-limits corresponding to one or more custodial prime brokers facilitating trading for the trading entity. At least one embodiment includes a pre-trade gateway to determine if an order violates a pre-trade risk based on information collected by a front-end analyzer. Possible actions include, but are not limited to, placing a null order, terminating a connection associated with the order, modifying the order so as not to violate a pre-trade risk check, and/or notifications to one or more entities.

Intraday risk management data cloud computing system capable of controlling execution of orders

To process financial articles of trade and manage risk, data messages originating from a plurality of sources arranged to trade at least one of securities, commodities, options, futures and derivatives are collected. The collected data including information on submitted transactions and completed transactions of financial articles of trade. The collected data is analyzed against established user criteria to identify select portions of the collected data. If a match is detected a risk alert signal will be transmitted.

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New York, NY, United States of America

Ted N Myerson