CA2400199A1 - A system and method to determine the validity of an interaction on a network - Google Patents

A system and method to determine the validity of an interaction on a network

Info

Publication number
CA2400199A1
CA2400199A1 CA 2400199 CA2400199A CA2400199A1 CA 2400199 A1 CA2400199 A1 CA 2400199A1 CA 2400199 CA2400199 CA 2400199 CA 2400199 A CA2400199 A CA 2400199A CA 2400199 A1 CA2400199 A1 CA 2400199A1
Authority
CA
Grant status
Application
Patent type
Prior art keywords
data
interactions
method
models
including
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CA 2400199
Other languages
French (fr)
Other versions
CA2400199C (en )
Inventor
Stephan Doliov
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Excalibur IP LLC
Original Assignee
Overture Services, Inc.
Stephan Doliov
Goto.Com, Inc.
Yahoo! Inc.
Excalibur Ip, Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Family has litigation

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/22Tracking the activity of the user
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor ; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor ; File system structures therefor in structured data stores
    • G06F17/30587Details of specialised database models
    • G06F17/30595Relational databases
    • G06F17/30598Clustering or classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor ; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/552Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/57Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
    • G06F21/577Assessing vulnerabilities and evaluating computer system security
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/067Business modelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0242Determination of advertisement effectiveness
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/04Billing or invoicing, e.g. tax processing in connection with a sale
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L61/00Network arrangements or network protocols for addressing or naming
    • H04L61/20Address allocation
    • H04L61/2007Address allocation internet protocol [IP] addresses
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/12Applying verification of the received information
    • H04L63/126Applying verification of the received information the source of the received data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416Event detection, e.g. attack signature detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/02Network-specific arrangements or communication protocols supporting networked applications involving the use of web-based technology, e.g. hyper text transfer protocol [HTTP]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/14Network-specific arrangements or communication protocols supporting networked applications for session management
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/16Service discovery or service management, e.g. service location protocol [SLP] or Web services
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2135Metering
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441Countermeasures against malicious traffic
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00Application independent communication protocol aspects or techniques in packet data networks
    • H04L69/30Definitions, standards or architectural aspects of layered protocol stacks
    • H04L69/32High level architectural aspects of 7-layer open systems interconnection [OSI] type protocol stacks
    • H04L69/322Aspects of intra-layer communication protocols among peer entities or protocol data unit [PDU] definitions
    • H04L69/329Aspects of intra-layer communication protocols among peer entities or protocol data unit [PDU] definitions in the application layer, i.e. layer seven
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99931Database or file accessing
    • Y10S707/99939Privileged access
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99942Manipulating data structure, e.g. compression, compaction, compilation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99943Generating database or data structure, e.g. via user interface
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99944Object-oriented database structure
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99944Object-oriented database structure
    • Y10S707/99945Object-oriented database structure processing

Abstract

The method and system of the invention utilize limited data to yield information about the validity of any given interaction with a website. Once validity information is available, an operator can determine whether or not to continue offering interactions to a given user. The operator collects data (200), insets data as values into determined mathematical equations (204), accesses risk value for each interaction (206). The determination could also relate to whether to report website interaction statistics based on undesired interactions, how to handle billing or payment for such undesired interactions, and what type of content to send to users who are interacting with the webside in an undesirable manner.

Claims (43)

1. A method of identifying illegitimate interactions of a presumed user on a network, the method comprising:
collecting data from user interactions on a network, the data including aggregate measure data and unique feature data about the presumed user;
storing the data in a database;
building predictive models with the aggregate measure and unique feature data to identify illegitimate interactions with the network;
and identifying the illegitimate interactions in the database using the predictive models.
2. The method of claim 1 further including:
applying a mathematical model of interactions derived from at least one probabilistic approach;
applying a mathematical model of interactions based on at least one stochastic approach; and determining the legitimacy of the interactions using the stochastic and probabilistic mathematical equations.
3. The method of claim 2 where the at least one probabilistic approach includes logistic regression.
4. The method of claim 2 where the at least one stochastic approach includes linear discriminant analysis.
5. The method of claim 2 further including:
assigning a classification to the value created by the probabilistic and stochastic derived mathematical models of interaction;
computing values of the probabilistic and stochastic derived mathematical models of interaction;
for the probabilistic mathematical models, placing an interaction into a class based on a computed probability of belonging to that class; and for the stochastic mathematical models, placing an interaction into the class with the highest computed value.
6. The method of claim 5 further including:
periodically reassessing the probabilistic and stochastic mathematical models against a standard;
applying a retrospective validating process; and applying a prospective validating process.
7. The method of claim 1 further comprising:
evaluating multiple network interactions;
creating a classification table; and determining a model of legitimate and illegitimate interactions from the classification table.
8. The method of claim 1 further including:
creating a database of illegitimate interactions.
9. The method of claim 8 further including:
evaluating the database to ensure that the probabilistic and stochastic derived mathematical models of interaction are reliable; and discarding unreliable probabilistic and stochastic mathematical models of interaction.
10. The method of claim 9 further including:
collecting additional aggregate measure and unique feature data; and deriving new probabilistic and stochastic derived mathematical models of interaction based on existing collected data and the additional collected aggregate measure and unique feature data.
11. The method of claim 1 where the collection of aggregate measure data comprises:

collecting data on a number of clicks per internet protocol address for a given time period;
collecting data on a number of unique queries per user session;
collecting data on a number of network clicks for a given time period; and collecting data on a number of distinct referral partners who could access the network.
12. The method of claim 1 where the collection of unique feature data comprises:
collecting data on an origin of the presumed user;~
collecting data on a time of the interactions;
collection data on a type of the interactions; and collecting data on presumed measures of uniqueness of the presumed user.
13. A method for creating reports according to website interactions after determining the validity of the website interactions, the method comprising:
collecting aggregate measure data and unique feature data about the website interaction;
building predictive models with the aggregate measure and unique feature data to identify undesirable interactions with the website; and removing the undesirable interactions from the reports, once identified.
14. The method of claim 13 further including:
applying statistical data analysis techniques to identify undesirable interactions with the website before removing the undesirable interactions from the reports.
15. The method of claim 14 wherein the statistical data analysis is used to create predictive models of undesirable interactions.
16. The method of claim 15 wherein the predictive models are used to produce at least one of a probability value and a behavior group.
17. The method of claim 16 further including:
formulating a business rule about which probability value or behavior group constitutes undesirable interactions with the Website.
18. The method of claim 15 further including:
creating a database of undesirable interactions.
19. The method of claim 18 further including:
evaluating the database to ensure that the predictive models are reliable; and discarding unreliable predictive models.
20. The method of claim 19 further including:
collecting additional aggregate measure and unique feature data; and deriving new predictive models based on existing collected data and the additional collected data.
21. The method of claim 13, wherein the predictive model is biased in favor of a customer.
22. A system for creating reports according to website interactions after determining the validity of the website interactions, the method comprising:
a first processor to collect aggregate measure data and unique feature data about a website user;
a second processor to create predictive models with the aggregate measure and unique feature data to identify undesirable interactions with the website, wherein the undesirable interactions are removed from the reports, once identified.
23. The system of claim 22 wherein statistical data analysis techniques are used to identify undesirable interactions with the website before removing the undesirable interactions from the reports.
24. The system of claim 23 wherein the statistical data analysis is used to create predictive models of undesirable interactions.
25. The system of claim 24 wherein the predictive models are used to produce at least one of a probability value and a behavior group.
26. The system of claim 25 wherein a business rule is formulated about which probability value or behavior group constitutes undesirable interactions with the Website.
27. The system of claim 24 wherein a database is created of undesirable interactions.
28. The system of claim 27 wherein the database is evaluated to ensure that the predictive models are reliable and unreliable predictive models are discarded.
29. The system of claim 28 wherein new data is collected and new predictive models are derived based on existing collected data and the new collected data.
30. The system of claim 22 wherein the predictive model is biased in favor of a customer.
31. A method of rating user interactions on a network, the method comprising:
collecting data from user interactions on a network, the data including aggregate measure data and unique feature data about the user;
storing the data in a database; and building predictive models with the aggregate measure and unique feature data to rate the interactions with the network.
32. The method of claim 31 further including identifying illegitimate interactions on the network.
33. The method of claim 31 further including identifying invalid interactions on the network.
34. The method of claim 31 further including identifying unauthorized interactions on the network.
35. The method of claim 31 further including:~
applying a probabilistic approach to mathematical modeling of the interactions;
applying a stochastic approach to derive mathematical models of the interaction; and identifying interactions on the network using the probabilistic and stochastic mathematical models of interaction.
36. The method of claim 35 further including:
assigning a class to values computed from the probabilistic and stochastic derived mathematical equations;
computing the values of the probabilistic and the stochastic mathematical models of interaction;
for the probabilistic mathematical models, placing an interaction into a class based on the computed probability of belonging to the class; and for the stochastic models, placing an interaction into the class with the highest computed value.
37. The method of claim 36 further including:
periodically reassessing the probabilistic and stochastic mathematical equations against a standard;
applying a retrospective validating process; and applying a prospective validating process.
38. The method of claim 37 further comprising:

evaluating multiple network interactions;
creating a classification table; and determining a model of interactions from the classification table.
39. The method of claim 35 further including:
creating a database of interactions.
40. The method of claim 39 further including:
evaluating the database to ensure that the probabilistic and the stochastic mathematical models of interaction are reliable; and discarding unreliable probabilistic and stochastic mathematical models of interaction.
41. The method of claim 40 further including:
collecting additional aggregate measure and unique feature data; and deriving new probabilistic and stochastic mathematical models of interaction based on existing collected data and the additional collected data.
42. The method of claim 31 where the collection of aggregate measure data comprises:
collecting data on a number of clicks per internet protocol address for a given time period;
collecting data on a number of unique queries per user session;
collecting data on a number of network clicks for a given time period; and collecting data on a number of distinct referral partners who could access the network.
43. The method of claim 31 where the collection of unique feature data comprises:
collecting data on an origin of the user;
collecting data on a time of the interactions;

collection data on a type of the interactions; and collecting data on presumed measures of uniqueness of the user.
CA 2400199 2000-02-14 2001-02-12 A system and method to determine the validity of an interaction on a network Active CA2400199C (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
US18214700 true 2000-02-14 2000-02-14
US60/182,147 2000-02-14
US09/765,802 2001-01-19
US09765802 US7136860B2 (en) 2000-02-14 2001-01-19 System and method to determine the validity of an interaction on a network
PCT/US2001/004549 WO2001061536A1 (en) 2000-02-14 2001-02-12 A system and method to determine the validity of an interaction on a network

Publications (2)

Publication Number Publication Date
CA2400199A1 true true CA2400199A1 (en) 2001-08-23
CA2400199C CA2400199C (en) 2011-04-12

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Country Status (9)

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US (7) US7136860B2 (en)
EP (1) EP1275053B1 (en)
JP (1) JP2003523578A (en)
KR (1) KR100595786B1 (en)
CN (1) CN1262949C (en)
CA (1) CA2400199C (en)
DE (2) DE60118542D1 (en)
GB (1) GB2376547B (en)
WO (1) WO2001061536A1 (en)

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