Secure data interchange

a data exchange and data technology, applied in the field of secure data exchange, can solve the problems of user's desire for controlled personalization, large corpus of data extrapolation, and inability to be desirable, and achieve the effect of avoiding loss of privacy, facilitating bilateral exchange of profiles/preferences, and facilitating the exchange of information

Inactive Publication Date: 2009-10-08
STRIPE INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0031]Interesting variations of SDI place data in different distributed locations, and move the control of information access between a central SDI server and distributed client-side SDI proxy agents. This allows different tradeoffs between privacy and information sharing. It also has implications for bandwidth and computational requirements within SDI. One role of a client-side SDI data warehouse is to provide the same functionality as the central shared SDI database, but with processing only performed on information provided by that agent. This can allow greater privacy by allowing a user to retain absolute control over his / her data on his / her local machine without even releasing data to the shared database.
[0032]In an application to personalized on-line interactions, we describe a client-side SDI proxy which manages a user's interactions with the on-line sites of vendors and also manages a user's interactions with the central SDI data warehouse, i.e. providing profile information and controlling profile access. The client-side SDI proxy for an agent that represents an individual browsing the Internet can manage that user's profiles in interactions with other agents, for example representing vendors and content providers. The client-side SDI proxy can also handle decisions about what types of information to submit to the server, and manages query execution on behalf of the agent. The client-side SDI proxy agent can also push information about a user's on-line activities to the central SDI data-warehouse in real time. This enables a system of “time-of-purchase-competition”system, in which a user can request competitive counteroffers from other vendors before making a purchase.
[0033]The system addresses the fundamental conflict that exists between rights of privacy and efficiency gains from better bilateral exchange of profile / preference information. SDI as applied to B2C e-commerce allows consumers to receive targeted information about products and services, but without the loss-of-privacy that can easily occur in the current on-line profiling “free-for-all”. The cookie technology provided by Netscape to supported personalized sessions with a single vendor on-line has been used by advertising network providers such as DoubleClick to track users across multiple sites, often without either the consent or knowledge of that individual [New York Times, Feb. 7, 2000].

Problems solved by technology

The problem is that a user wants controlled personalization, in the sense that it might not be desirable for information about every on-line transaction that a user performs, every on-line document that a user reads, and every web page that a user visits, and demographic information, to be available to every business that the user interacts with, in the virtual and physical world.
The problem—as before, is to acquire and leverage information about the preferences and interests of a user, within a system that protects user privacy (i.e. controls the collection and exchange of information about users, and controls the use that is made of that information).
A further problem is to extrapolate information from a large corpus of data about an individual user.
Consumer B meets the criteria, but is only listed for business A if A also meets criteria specified by B, for example if A will provide information about new products and services that are interesting to B. In an application to the profiling of users on-line, the problem is that users want to receive the benefits of targeted products and advertisements, but want to avoid the abuse of profile information and control vendors' access to that information.
The problem with this exchange of information (that can include swaps, sells, and rental access) is that businesses need to (a) protect the privacy of their customers; (b) prevent information release to competitors, either directly or through third-parties.
The problem is to provide information that enables matches, without allowing bad matches and abuse of information—i.e. within an environment of secure data interchange.
The problem is to manage certificates within a system where users can maintain multiple identities, and to protect the release of certificates without suitable provisions for terms-of-use and criteria for request.

Method used

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Examples

Experimental program
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case 1

[0628] All Customers Use a Single Pseudonym, and Appear in all Databases Considered.[0629]This is the simplest situation to handle. Since all customers appear in all the databases, the customer vectors' fields are essentially scattered across several locations, but can be easily reconstructed. For each customer, we define a new data vector that concatenates that customer's representation from across the different databases.

[0630]Hence, if we are considering databases A, B, . . . , Z, and customer i appears in each one, we define a new vector ci=(cAi, cBi, . . . , cZi), where cAi is customer i's vector in database A. We then proceed as usual, making inferences with these augmented customer vectors.

case 2

[0631] Most Customers Use a Unique Pseudonym, and Frequently Appear in Different Databases.[0632]In this situation, although we see some connections between the databases, many pseudonyms appear in only a single location. Using Bayesian techniques, however, we can still make predictions for customer vectors across databases.[0633]Suppose we have a set of databases, A, B, . . . , Z. Taking each database in turn, we cluster it using all available data. Thus, using every record in database A, we group A's customers into clusters A1, A2, . . . , An. Taking database B, we create clusters using all of B's information, creating customer clusters B1, B2, . . . , Bm, and so forth.[0634]Now, scan both databases for common pseudonyms (representing those customers who have interacted with both vendors under the same pseudonym) and create count variables wij to represent the number of pseudonyms that appear jointly in Ai and Bj.[0635]We can now produce the probability that a pseudonym appearing ...

case 3

[0640] All Customers Use Several Pseudonyms, and None Appear in Different Databases[0641]In this situation, there are no common customer codes that can be used to create links across the databases. However, the mere fact that several databases have been brought together for analysis should imply that there are semantic commonalties in the data.[0642]Although each database contains different fields, it may be the case that those fields deal with related subjects. A human expert, knowledgeable in the content of the databases, the subtleties of the domain, and the overall goal of the analysis (e.g. the creation of recommendations), will be in a position to create a “common-information profile” that spans the databases. In essence, the common-information profile defines a format that allows vectors from different databases to share a common coordinate space.[0643]The idea is this: the expert designs a high-level vector format that embodies the content deemed important for the project go...

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Abstract

A secure data interchange system enables information about bilateral and multilateral interactions between multiple persistent parties to be exchanged and leveraged within an environment that uses a combination of techniques to control access to information, release of information, and matching of information back to parties. Access to data records can be controlled using an associated price rule. A data owner can specify a price for different types and amounts of information access.

Description

RELATED APPLICATIONS[0001]This application is a continuation of and claims priority under 35 U.S.C. §120 to U.S. application Ser. No. 09 / 699,098 entitled “Secure Data Interchange,” filed on Oct. 27, 2000, which claims the benefit of U.S. Provisional Application No. 60 / 161,640, filed Oct. 29, 1999, titled Secure Data Interchange, and Provisional Application No. 60 / 206,538, filed May 23, 2000, titled Secure Data Interchange, all of which are incorporated herein by reference in their entirety.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]The Secure Data Interchange invention describes a system to allow a privacy-protected market for data exchange between multiple self-interested parties. The system presents a general infrastructure for the exchange of information within a safe privacy-protected environment, between multiple self-interested parties. We propose a central data warehouse that maintains data submitted by different users, and executes queries and programs o...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): G06F17/00G06Q10/00
CPCG06Q10/10H04L63/20G06Q30/0603G06Q30/02G06F16/337Y10S707/99932Y10S707/99939
Inventor HERZ, FREDERICK S. M.LABYS, WALTER PAULPARKES, DAVID C.KANNAN, SAMPATHEISNER, JASON M.
Owner STRIPE INC
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