The disclosure relates generally to a system and method for cryptography and block chain systems.
In order for Blockchain based smart contracts to take action based on real-world inputs or have real-world side-effects (resource actions) there must exist a mechanism to verify the authenticity of smart contract inputs and data accessed in third party systems by a smart contract.
This system and method specifically deals with methodologies concerning Cryptographically Verified Blockchain-based Contract Data Inputs and Off-chain Side-effects. In order for Blockchain based smart contracts to take action based on real-world inputs or have real-world side-effects (resource actions) there must exist a mechanism to verify the authenticity of smart contract inputs and data accessed in third party systems by a smart contract. Given this capability smart contracts which include third-party system inputs and side-effects can then be processed and later verified, thereby maintaining the integrity of the distributed ledger system of the requisite Blockchain-based smart contract.
In the system 100 in
The off-chain system 104 may be implemented using one or more processors, memory, such as DRAM or SRAM, one or more persistent storage devices, such as flash memory or a hard disk drive, one or more databases, connectivity circuits, etc. that allow the off-chain system 104 to store data and host applications and communicate with the blockchain system 102 over a communications path and interact with the smart contract 106. As shown in
In the system 100, each of the blockchain system 102 and off-chain host system 104 may, in one embodiment, have at least one processor that may be used to execute a plurality of instructions or computer code that implement the methods described below with reference to
The system and method provides a deterministic and cryptographically verifiable chain of transactions, recorded on a blockchain (distributed ledger) system. This system provides an irrefutable public accounting of the transactions involved in incorporating on-chain contract execution with off-chain data and side-effects (resource actions). Thus, the system and method provide a system and method for interaction of smart contracts with off-chain resources as described below.
In implementing both the registration processes 300 in
As shown in
As part of the registration process shown in
In the registration method shown in
In the invocation process, the smart contract 106 may publish a transaction targeted to the off-chain host system (as shown in
Once the off-chain host system 104 has verified that the request is valid, the off-chain host system 104 may satisfy the data request or execute the desired side-effect/action (as shown in
Once the response is received by the smart-contract 106, it may verify that the signature (responseData.data_signature) corresponds to the data (responseData.response_data) and the correlation identifier of the request (responseData.request.correlation_id) and was signed by the key associated with the on-chain wallet address of the off-chain host system (as shown in
Use Cases
The above described system and method may have many different uses. For example, the system and method may be used for a consumer wallet for personal healthcare information, a provider wallet for healthcare interactions and healthcare ASC X12N 5010 transactions that are each described below in more detail with reference to
Consumer Wallet for Personal HealthCare Information
A consumer wallet—smart contract on the blockchain—can be built which inherits from OffChainResourceContract class (an example of which is shown in
Provider Wallet for HealthCare Interactions
A provider wallet can be built which inherits from OffChainResourceContract class. This wallet can be used by the provider to interact with consumer wallet for authorization to access consumer personal health information records, communications and referrals.
HealthCare ASC X12N 5010 Transactions
The above system and method may be used to process various healthcare ASC X12N 5010 transactions.
1. Eligibility—The 270/271 transaction set can be processed off-chain and a resource id to the off-chain private information is returned along with other public details of the transaction such as payer details and response times.
2. Claims—The 837 transaction can be processed off-chain and a resource id to the off-chain private information is returned along with other public details of the transaction such as payer details and response times.
3. Enrollment—private and public data controlled through a consumer wallet can be used by third party smart contracts that process real-time healthcare insurance plan enrollment and use this data to accurately calculate risk and match a consumer to an appropriate health insurance plan resulting in an off-chain 834 transaction.
4. Authorization and Referral—using and off-chain 278 transaction and private and public data controlled through a consumer wallet, third party smart contracts that process real-time authorization based on public preferences added to the consumer wallet by the consumer and provider requirements added to the consumer wallet by the referring provider (given consumer consent).
5. Payments and Financing—given the enrollment and claims scenarios above payment can be facilitated by providing public data of the payment and potential funding needs of a consumer for a transaction whereby third-party smart contracts could present loan offers to the consumer wallet for execution by the consumer.
The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosure and various embodiments with various modifications as are suited to the particular use contemplated.
The system and method disclosed herein may be implemented via one or more components, systems, servers, appliances, other subcomponents, or distributed between such elements. When implemented as a system, such systems may include an/or involve, inter alia, components such as software modules, general-purpose CPU, RAM, etc. found in general-purpose computers. In implementations where the innovations reside on a server, such a server may include or involve components such as CPU, RAM, etc., such as those found in general-purpose computers.
Additionally, the system and method herein may be achieved via implementations with disparate or entirely different software, hardware and/or firmware components, beyond that set forth above. With regard to such other components (e.g., software, processing components, etc.) and/or computer-readable media associated with or embodying the present inventions, for example, aspects of the innovations herein may be implemented consistent with numerous general purpose or special purpose computing systems or configurations. Various exemplary computing systems, environments, and/or configurations that may be suitable for use with the innovations herein may include, but are not limited to: software or other components within or embodied on personal computers, servers or server computing devices such as routing/connectivity components, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, consumer electronic devices, network PCs, other existing computer platforms, distributed computing environments that include one or more of the above systems or devices, etc.
In some instances, aspects of the system and method may be achieved via or performed by logic and/or logic instructions including program modules, executed in association with such components or circuitry, for example. In general, program modules may include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular instructions herein. The inventions may also be practiced in the context of distributed software, computer, or circuit settings where circuitry is connected via communication buses, circuitry or links. In distributed settings, control/instructions may occur from both local and remote computer storage media including memory storage devices.
The software, circuitry and components herein may also include and/or utilize one or more type of computer readable media. Computer readable media can be any available media that is resident on, associable with, or can be accessed by such circuits and/or computing components. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and can accessed by computing component. Communication media may comprise computer readable instructions, data structures, program modules and/or other components. Further, communication media may include wired media such as a wired network or direct-wired connection, however no media of any such type herein includes transitory media. Combinations of the any of the above are also included within the scope of computer readable media.
In the present description, the terms component, module, device, etc. may refer to any type of logical or functional software elements, circuits, blocks and/or processes that may be implemented in a variety of ways. For example, the functions of various circuits and/or blocks can be combined with one another into any other number of modules. Each module may even be implemented as a software program stored on a tangible memory (e.g., random access memory, read only memory, CD-ROM memory, hard disk drive, etc.) to be read by a central processing unit to implement the functions of the innovations herein. Or, the modules can comprise programming instructions transmitted to a general purpose computer or to processing/graphics hardware via a transmission carrier wave. Also, the modules can be implemented as hardware logic circuitry implementing the functions encompassed by the innovations herein. Finally, the modules can be implemented using special purpose instructions (SIMD instructions), field programmable logic arrays or any mix thereof which provides the desired level performance and cost.
As disclosed herein, features consistent with the disclosure may be implemented via computer-hardware, software and/or firmware. For example, the systems and methods disclosed herein may be embodied in various forms including, for example, a data processor, such as a computer that also includes a database, digital electronic circuitry, firmware, software, or in combinations of them. Further, while some of the disclosed implementations describe specific hardware components, systems and methods consistent with the innovations herein may be implemented with any combination of hardware, software and/or firmware. Moreover, the above-noted features and other aspects and principles of the innovations herein may be implemented in various environments. Such environments and related applications may be specially constructed for performing the various routines, processes and/or operations according to the invention or they may include a general-purpose computer or computing platform selectively activated or reconfigured by code to provide the necessary functionality. The processes disclosed herein are not inherently related to any particular computer, network, architecture, environment, or other apparatus, and may be implemented by a suitable combination of hardware, software, and/or firmware. For example, various general-purpose machines may be used with programs written in accordance with teachings of the invention, or it may be more convenient to construct a specialized apparatus or system to perform the required methods and techniques.
Aspects of the method and system described herein, such as the logic, may also be implemented as functionality programmed into any of a variety of circuitry, including programmable logic devices (“PLDs”), such as field programmable gate arrays (“FPGAs”), programmable array logic (“PAL”) devices, electrically programmable logic and memory devices and standard cell-based devices, as well as application specific integrated circuits. Some other possibilities for implementing aspects include: memory devices, microcontrollers with memory (such as EEPROM), embedded microprocessors, firmware, software, etc. Furthermore, aspects may be embodied in microprocessors having software-based circuit emulation, discrete logic (sequential and combinatorial), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types. The underlying device technologies may be provided in a variety of component types, e.g., metal-oxide semiconductor field-effect transistor (“MOSFET”) technologies like complementary metal-oxide semiconductor (“CMOS”), bipolar technologies like emitter-coupled logic (“ECL”), polymer technologies (e.g., silicon-conjugated polymer and metal-conjugated polymer-metal structures), mixed analog and digital, and so on.
It should also be noted that the various logic and/or functions disclosed herein may be enabled using any number of combinations of hardware, firmware, and/or as data and/or instructions embodied in various machine-readable or computer-readable media, in terms of their behavioral, register transfer, logic component, and/or other characteristics. Computer-readable media in which such formatted data and/or instructions may be embodied include, but are not limited to, non-volatile storage media in various forms (e.g., optical, magnetic or semiconductor storage media) though again does not include transitory media. Unless the context clearly requires otherwise, throughout the description, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in a sense of “including, but not limited to.” Words using the singular or plural number also include the plural or singular number respectively. Additionally, the words “herein,” “hereunder,” “above,” “below,” and words of similar import refer to this application as a whole and not to any particular portions of this application. When the word “or” is used in reference to a list of two or more items, that word covers all of the following interpretations of the word: any of the items in the list, all of the items in the list and any combination of the items in the list.
Although certain presently preferred implementations of the invention have been specifically described herein, it will be apparent to those skilled in the art to which the invention pertains that variations and modifications of the various implementations shown and described herein may be made without departing from the spirit and scope of the invention. Accordingly, it is intended that the invention be limited only to the extent required by the applicable rules of law.
While the foregoing has been with reference to a particular embodiment of the disclosure, it will be appreciated by those skilled in the art that changes in this embodiment may be made without departing from the principles and spirit of the disclosure, the scope of which is defined by the appended claims.
This application claims the benefit under 35 USC 119(e) to and priority under 35 USC 120 to U.S. Provisional Patent Application Ser. No. 62/354,561, filed on Jun. 24, 2016 and entitled “System and Method for Cryptographically Verified Data Driven Contracts”, the entirety of which is incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
5872021 | Matsumoto et al. | Feb 1999 | A |
6546428 | Baber et al. | Apr 2003 | B2 |
7386565 | Singh et al. | Jun 2008 | B1 |
7917378 | Fitzgerald et al. | Mar 2011 | B2 |
7917515 | Lemoine | Mar 2011 | B1 |
7970802 | Ishizaki | Jun 2011 | B2 |
7992153 | Ban | Aug 2011 | B2 |
8073801 | Von Halle et al. | Dec 2011 | B1 |
8095975 | Boss et al. | Jan 2012 | B2 |
8103667 | Azar et al. | Jan 2012 | B2 |
8103952 | Hopp | Jan 2012 | B2 |
8203562 | Alben et al. | Jun 2012 | B1 |
8229808 | Heit | Jul 2012 | B1 |
8286191 | Amini et al. | Oct 2012 | B2 |
8359298 | Schacher et al. | Jan 2013 | B2 |
8364501 | Rana et al. | Jan 2013 | B2 |
8417755 | Zimmer | Apr 2013 | B1 |
8495108 | Nagpal et al. | Jul 2013 | B2 |
8515777 | Rajasenan | Aug 2013 | B1 |
8817665 | Thubert et al. | Aug 2014 | B2 |
8984464 | Mihal et al. | Mar 2015 | B1 |
9165045 | Mok et al. | Oct 2015 | B2 |
9208284 | Douglass | Dec 2015 | B1 |
20020022973 | Sun et al. | Feb 2002 | A1 |
20020038233 | Shubov et al. | Mar 2002 | A1 |
20020165738 | Dang | Nov 2002 | A1 |
20030055668 | Saran et al. | Mar 2003 | A1 |
20030097359 | Ruediger | May 2003 | A1 |
20030171953 | Narayanan et al. | Sep 2003 | A1 |
20030217159 | Schramm-Apple et al. | Nov 2003 | A1 |
20030233252 | Haskell et al. | Dec 2003 | A1 |
20040143446 | Lawrence | Jul 2004 | A1 |
20050010452 | Lusen | Jan 2005 | A1 |
20050071189 | Blake et al. | Mar 2005 | A1 |
20050102170 | Lefever et al. | May 2005 | A1 |
20050137912 | Rao et al. | Jun 2005 | A1 |
20050152520 | Logue | Jul 2005 | A1 |
20050182780 | Forman et al. | Aug 2005 | A1 |
20050222912 | Chambers | Oct 2005 | A1 |
20060036478 | Aleynikov et al. | Feb 2006 | A1 |
20060074290 | Chen et al. | Apr 2006 | A1 |
20060089862 | Anandarao et al. | Apr 2006 | A1 |
20060129428 | Wennberg | Jun 2006 | A1 |
20060136264 | Eaton et al. | Jun 2006 | A1 |
20070113172 | Behrens et al. | May 2007 | A1 |
20070118399 | Avinash et al. | May 2007 | A1 |
20070156455 | Tarino et al. | Jul 2007 | A1 |
20070174101 | Li et al. | Jul 2007 | A1 |
20070180451 | Ryan et al. | Aug 2007 | A1 |
20070214133 | Liberty et al. | Sep 2007 | A1 |
20070233603 | Schmidgall et al. | Oct 2007 | A1 |
20070260492 | Feied et al. | Nov 2007 | A1 |
20070276858 | Cushman et al. | Nov 2007 | A1 |
20070288262 | Sakaue et al. | Dec 2007 | A1 |
20080013808 | Russo et al. | Jan 2008 | A1 |
20080082980 | Nessland et al. | Apr 2008 | A1 |
20080091592 | Blackburn et al. | Apr 2008 | A1 |
20080126264 | Tellefsen et al. | May 2008 | A1 |
20080133436 | Di Profio | Jun 2008 | A1 |
20080288292 | Bi et al. | Nov 2008 | A1 |
20080295094 | Korupolu et al. | Nov 2008 | A1 |
20080319983 | Meadows | Dec 2008 | A1 |
20090083664 | Bay | Mar 2009 | A1 |
20090125796 | Day et al. | May 2009 | A1 |
20090192864 | Song et al. | Jul 2009 | A1 |
20090198520 | Piovanetti-Perez | Aug 2009 | A1 |
20090300054 | Fisher et al. | Dec 2009 | A1 |
20090307104 | Weng | Dec 2009 | A1 |
20090313045 | Boyce | Dec 2009 | A1 |
20100076950 | Kenedy et al. | Mar 2010 | A1 |
20100082620 | Jennings, III et al. | Apr 2010 | A1 |
20100088108 | Machado | Apr 2010 | A1 |
20100088119 | Tipirneni | Apr 2010 | A1 |
20100138243 | Carroll | Jun 2010 | A1 |
20100217973 | Kress et al. | Aug 2010 | A1 |
20100228721 | Mok et al. | Sep 2010 | A1 |
20100295674 | Hsieh et al. | Nov 2010 | A1 |
20100332273 | Balasubramanian et al. | Dec 2010 | A1 |
20110015947 | Erry et al. | Jan 2011 | A1 |
20110055252 | Kapochunas et al. | Mar 2011 | A1 |
20110071857 | Malov et al. | Mar 2011 | A1 |
20110137672 | Adams et al. | Jun 2011 | A1 |
20110218827 | Kennefick et al. | Sep 2011 | A1 |
20110270625 | Pederson et al. | Nov 2011 | A1 |
20120011029 | Thomas | Jan 2012 | A1 |
20120035984 | Srinivasa et al. | Feb 2012 | A1 |
20120078940 | Kolluri et al. | Mar 2012 | A1 |
20120130736 | Dunston et al. | May 2012 | A1 |
20120158429 | Murawski et al. | Jun 2012 | A1 |
20120158750 | Faulkner et al. | Jun 2012 | A1 |
20120173279 | Nessa et al. | Jul 2012 | A1 |
20120245958 | Lawrence et al. | Sep 2012 | A1 |
20120246727 | Elovici et al. | Sep 2012 | A1 |
20120290320 | Kurgan et al. | Nov 2012 | A1 |
20120290564 | Mok et al. | Nov 2012 | A1 |
20130030827 | Snyder et al. | Jan 2013 | A1 |
20130044749 | Eisner et al. | Feb 2013 | A1 |
20130085769 | Jost et al. | Apr 2013 | A1 |
20130138554 | Nikankin et al. | May 2013 | A1 |
20130166552 | Rozenwald et al. | Jun 2013 | A1 |
20130204940 | Kinsel et al. | Aug 2013 | A1 |
20130304903 | Mick et al. | Nov 2013 | A1 |
20140046931 | Mok et al. | Feb 2014 | A1 |
20140056243 | Pelletier et al. | Feb 2014 | A1 |
20140059084 | Adams et al. | Feb 2014 | A1 |
20140088981 | Momita | Mar 2014 | A1 |
20140136233 | Atkinson et al. | May 2014 | A1 |
20140222482 | Gautam et al. | Aug 2014 | A1 |
20140244300 | Bess et al. | Aug 2014 | A1 |
20140278491 | Weiss | Sep 2014 | A1 |
20140358578 | Ptachcinski | Dec 2014 | A1 |
20140358845 | Mundlapudi et al. | Dec 2014 | A1 |
20150095056 | Ryan et al. | Apr 2015 | A1 |
20150112696 | Kharraz Tavakol | Apr 2015 | A1 |
20150142464 | Rusin et al. | May 2015 | A1 |
20150199482 | Corbin et al. | Jul 2015 | A1 |
20150332283 | Witchey | Nov 2015 | A1 |
20160028552 | Spanos | Jan 2016 | A1 |
20160055205 | Jonathan et al. | Feb 2016 | A1 |
20160253679 | Venkatraman et al. | Sep 2016 | A1 |
20160261411 | Yau | Sep 2016 | A1 |
20160328641 | Alsaud et al. | Nov 2016 | A1 |
20160342750 | Alstad et al. | Nov 2016 | A1 |
20160342751 | Alstad et al. | Nov 2016 | A1 |
20170091397 | Shah et al. | Mar 2017 | A1 |
20170103164 | Dunlevy et al. | Apr 2017 | A1 |
20170103165 | Dunlevy et al. | Apr 2017 | A1 |
20170132621 | Miller | May 2017 | A1 |
20170351821 | Tanner et al. | Dec 2017 | A1 |
Number | Date | Country |
---|---|---|
2478440 | Oct 2013 | GB |
WO 2012122065 | Sep 2012 | WO |
Entry |
---|
Ahlswede et al., Network Information Flow, IEEE Transactions on Information Theory, vol. 46, No. 4; Jul. 2000 (13 pgs.). |
Bhattacharya, Indrajit and Getoor, Lise, Entity Resolution in Graphs, Department of Computer Science, University of Maryland (2005) (21 pgs.). |
Chen et al., Adaptive Graphical Approach to Entity Resolution, Jun. 18-23, 2007, Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 204-213 (10 pgs.). |
Christen, Data Matching, Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection, © Springer-Verlag Berlin Heidelberg, 2012 (279 pgs.). |
Cohen et al., A Comparison of String Metrics for Matching Names and Records, ©2003, American Association for Artificial Intelligence (www.aaai.org) (6 pgs.). |
Coleman et al., Medical Innovation—a diffusion study; The Bobbs-Merrill Company, Inc., 1966 (248 pgs.). |
Domingos et al., Mining High-Speed Data Streams, (2000) (10 pgs.). |
Greenhalgh et al., Diffusion of Innovations in Health Service Organisations—a systematic literature review, Blackwell Publishing, 2005 (325 pgs.). |
Jackson et al., The Evolution of Social and Economic Networks, Journal of Economic Theory 106, pp. 265-295, 2002 (31 pgs.). |
Jackson, Matthew O., Social and Economic Networks, Princeton University Press, 2008 (509 pgs.). |
Krempl et al., Open Challenges for Data Stream Mining Research, SIGKDD Explorations, vol. 16, Issue 1, Jun. 2014 (64 pgs.). |
Lin et al., A simplicial complex, a hypergraph, structure in the latent semantic space of document clustering, © Elsevier, 2005 (26 pgs.). |
Mathjax, Naive Bayes Categorisation (with some help from Elasticsearch), blog post dated Dec. 29, 2013 (https://blog.wtf.sg/2013/12/29/naive-bayes-categorisation-with-some-help-from-elasticsearch/). (8 pgs.). |
Newman, Modularity and community structure in networks, PNAS, vol. 103, No. 23, pp. 8581-8582 Jun. 6, 2006 (2 pgs.). |
Rebuge, Business Process Analysis in Healthcare Environments, 2011, Ellsevier Ltd., pp. 99-116 (18 pgs.). |
Titan Database Documentation ©2015 (disclosed at http://s3.thinkaurelius.com/docs/titan/1.0.0/ (printed Sep. 16, 2016) (214 pgs.). |
Wasserman et al., Social Network Analysis: Methods and Applications, Cambridge University Press; 1994 (434 pgs.). |
White et al., Algorithms for Estimating Relative Importance in Networks, Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003 (10 pgs.). |
Webpage: New Health Care Electronic Transactions Standards Versions 5010, D.0, and 3.0, Jan. 2010 CN 903192; http://www.cms.gov/Regulations-and-Guidance/HIPAA-Adminstrative-Simplification/Versions5010and D0/downloads/w5010BasicsFctCht.pdf (4 pgs.). |
Webpage: U.S. Dept. of Health and Human Services, Guidance Regarding Methods for De-identification of Protected Health Information in Accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/De-identification/guidance.html printed Oct. 15, 2015 (14 pgs.). |
Anonymous: “Oauth—Wikipedia”, Sep. 23, 2013. Retrieved from the Internet URL:https://en.wikipedia.org/w/index.php?title+oAuth&oldid+574187532 (3 pages). |
Version 5010 and D.0, Center for Medicare and Medicaid Services (2 pgs.). |
Anonymous: “Oauth” Wikipedia—Retrieved from the Internet URL:https://en.wikipedia.org/wiki/Oauth (8 pgs.). |
Number | Date | Country | |
---|---|---|---|
20170372300 A1 | Dec 2017 | US |
Number | Date | Country | |
---|---|---|---|
62354561 | Jun 2016 | US |