contact data validation in fred
play

Contact data validation in FRED Jaromir Talir - PowerPoint PPT Presentation

Dec 11, 2023 •95 likes •282 views

Contact data validation in FRED Jaromir Talir jaromir.talir@nic.cz 18.11.2013 Agenda FRED To validate or not to validate Other approaches Our way Keeping contacts data valid Conclusion FRED Open source

  1. Contact data validation in FRED Jaromir Talir • jaromir.talir@nic.cz • 18.11.2013

  2. Agenda ● FRED ● To validate or not to validate ● Other approaches ● Our way ● Keeping contacts data valid ● Conclusion

  3. FRED ● Open source registry software from CZ.NIC in development since 2007 ● Used by CZ, AO, TZ, CR, FO, EE, AL ● Runs on Linux ● Installation packages for Ubuntu and Fedora ● Full featured - EPP, ENUM, DNSSEC, IDN, WHOIS, ... ● http://fred.nic.cz

  4. To validate or not to validate ● Registry is not for anonymous entities ● Major reasons for accurate data: ● Resolution of legal issues ● Resolution of technical issues (spam etc..) ● Securing domains by notifying owners about events ● But there is a cost associated with validation

  5. SAC058 ● SSAC Report on Domain Name Registration Data Validation (March 2013) ● Reasons for validation ● Taxonomy ● Syntactical validation ● Operational validation ● Identity validation ● What attributes are subject of validation

  6. Validation by registrars ● Registrars are responsible for contact data ● According contract, they should provide sufficient effort for validation of data. ● New RAA for ICANN accredited registrars ● Mandatory requirements for validation ● Hardly applicable to our registrars ● Registry could be better place for validation

  7. Different approaches ● Presentations from TechDay in Costa Rica: ● Turkey ● Registrants send documents via web portal ● Estonia ● For locals - integration with local eID and governmental registries ● For foreigners – after receiving money, registrars send bank account identity embedded in EPP

  8. Our way ● Two complementary approaches ● Voluntary and automated ● Send one-time codes to email, phone and postal address ● Selective and manual ● Pro-active seeking of suspicious contacts and manual verification procedure

  9. Voluntary ● Two phase procedure ● Registrant enters handle of contact and codes are sent to him via email and sms ● After collecting 2 codes, contact receives 1 st grade of validation and other code is sent via snail mail to postal address ● After entering this code, contact receives 2 nd grade of validation

  10. Voluntary ● For sms/letter delivery, we use third party web services – customizable by shell script ● Website for this process can be personalized by logo of registrar ● Level of validation is visible in EPP and WHOIS ● Contacts loose validation upon change

  11. Voluntary ● Voluntary service must be marketed ● Marketing to registrants ● Possibility to hide address in WHOIS ● Small gifts (flash drive, etc..) ● Marketing to registrars ● Level of participation of registry in co-marketing program depends on number of validated contacts

  12. Selective ● System periodically randomly selects a group of contacts ● Each contact is first automatically checked for: ● Syntactical correctness of data ● Domain name of email exists and has MX records ● Look up in available registries for streets and cities to check postal address ● Failed checks go into queue for manual checking by our helpdesk operators

  13. Selective ● List of individual automatic checks is extensible ● Part of manual checking is written request to contact to correct data ● According registration rules, failure in manual checking may lead to dropping registration of all domains of this contact

  14. Keeping contact data valid ● Generally hard, we try to support it by fighting with duplicities in contact data ● More contacts user has, more probably he will forget to update them all ● We had ~ 15% of full duplicates ● Reasons? Could be simplicity of registrar interfaces

  15. Keeping contact data valid ● New operation in registry – merge contact ● Look up for full duplicates ● Changing all linked objects to one contact ● Delete second contact ● Registrars/registrants are informed about result of merge operation ● Such “cleanup” is supposed to be done periodically

  16. Conclusion ● Registry is suitable place to do validation of contact data ● Registry software can help a lot and FRED has wide support for validation, but some customization is needed ● Integration with SMS / snail mail services ● Features and versions ● Voluntary validation and merging – FRED-2.16 ● Selective validation – FRED-2.17 – later this year

  17. Thank You Jaromir Talir • jaromir.talir@nic.cz

Recommend

Update on aircraft validation efforts; T/q retrieval validation using ARM data Dave Tobin, Leslie

Update on aircraft validation efforts; T/q retrieval validation using ARM data Dave Tobin, Leslie

Update on aircraft validation efforts; T/q retrieval validation using ARM data Dave Tobin, Leslie Moy, Bob Knuteson, Hank Revercomb, Fred Best, Joe Taylor CIMSS / SSEC / UW-Madison AIRS Science Team Meeting Pasadena, CA 27-30 March 2007

425 views • 30 slides
Occams Razor Sampling Bias : generate the data carefuly Data Snooping : handle the data

Occams Razor Sampling Bias : generate the data carefuly Data Snooping : handle the data

recap: Validation and Cross Validation Validation Cross Validation D ( N ) D 1 D 2 D N D train Learning From Data D ( N K ) g 1 g 2 g N Lecture 14 ( x 1 , y 1 ) ( x 2 , y 2 ) ( x N , y N ) Three Learning Principles D

486 views • 15 slides
Data Mining II Model Validation Heiko Paulheim Why Model Validation? We have seen so far

Data Mining II Model Validation Heiko Paulheim Why Model Validation? We have seen so far

Data Mining II Model Validation Heiko Paulheim Why Model Validation? We have seen so far Various metrics (e.g., accuracy, F-measure, RMSE, ) Evaluation protocol setups Split Validation Cross Validation Special

1.04k views • 55 slides
Best Practices for Irregular Warfare (IW) Data Quality Control Jeff Appleget & Fred Cameron

Best Practices for Irregular Warfare (IW) Data Quality Control Jeff Appleget & Fred Cameron

Best Practices for Irregular Warfare (IW) Data Quality Control Jeff Appleget & Fred Cameron 29 th ISMOR August 2012 Agenda Irregular Warfare (IW) Background Physics-Based Combat Modeling IW Modeling Validation Best Practices

680 views • 23 slides
Learning From Data Lecture 13 Validation and Model Selection The Validation Set Model Selection

Learning From Data Lecture 13 Validation and Model Selection The Validation Set Model Selection

Learning From Data Lecture 13 Validation and Model Selection The Validation Set Model Selection Cross Validation M. Magdon-Ismail CSCI 4100/6100 recap: Regularization Regularization combats the effects of noise by putting a leash on the

349 views • 31 slides
Statistical Methods for Infectious Disease Using Validation Sets for Outcomes in Vaccine Studies

Statistical Methods for Infectious Disease Using Validation Sets for Outcomes in Vaccine Studies

Outline Validation Sets Final Value Time-to-event Sensitivity Analysis Other Statistical Methods for Infectious Disease Using Validation Sets for Outcomes in Vaccine Studies M. Elizabeth Halloran Fred Hutchinson Cancer Research Center and

624 views • 58 slides
Learning From Data Lecture 14 Three Learning Principles Occams Razor Sampling Bias Data

Learning From Data Lecture 14 Three Learning Principles Occams Razor Sampling Bias Data

Learning From Data Lecture 14 Three Learning Principles Occams Razor Sampling Bias Data Snooping M. Magdon-Ismail CSCI 4100/6100 recap: Validation and Cross Validation Validation Cross Validation D ( N ) D 1 D 2 D N D train D

1.01k views • 58 slides
Data validation and exploration Data validation and exploration Abhijit Dasgupta Abhijit

Data validation and exploration Data validation and exploration Abhijit Dasgupta Abhijit

Data validation and exploration Data validation and exploration Abhijit Dasgupta Abhijit Dasgupta Fall, 2019 Fall, 2019 1 BIOF339, Fall, 2019 Plan today Dynamic exploration of data Data validation Missing data evaluation 2 BIOF339,

570 views • 27 slides
Forms and Validation Topics: Sending data to the server forms HTML 5 validation

Forms and Validation Topics: Sending data to the server forms HTML 5 validation

Forms and Validation Topics: Sending data to the server forms HTML 5 validation Server side <form> element Forms allow us to submit data to the server There are two ways of handling information submitted with a

644 views • 14 slides
Measurement Data on AS_SET and AGGREGATOR: Implications for {Prefix, Origin} Validation

Measurement Data on AS_SET and AGGREGATOR: Implications for {Prefix, Origin} Validation

Measurement Data on AS_SET and AGGREGATOR: Implications for {Prefix, Origin} Validation Algorithms NIST BGP Security Team July 2010 National Institute of Standards and Technology National Institute of Standards and Technology Contact:

103 views • 7 slides
!"#$!#!%& Critical thinking Validation = critical assessment How good is my

!"#$!#!%& Critical thinking Validation = critical assessment How good is my

!"#$!#!%& EMBO Course on SAS, EMBL-HH, 2 November 2014 Applied common sense The why, what and how of validation Gerard J. Kleywegt Protein Data Bank in Europe (pdbe.org) EMBL-EBI, Cambridge, UK Validation according to the dictionary

407 views • 19 slides
The Importance of Healthcare Data Cleansing and Validation NAHDO October 28, 2015 The Spinach

The Importance of Healthcare Data Cleansing and Validation NAHDO October 28, 2015 The Spinach

The Importance of Healthcare Data Cleansing and Validation NAHDO October 28, 2015 The Spinach Myth 2 IQSC Data Integrity Goals Reduce Costly Data Errors Save Time and Precious Resources Provide a data analysis tool that assist

614 views • 6 slides
Form Validation 1 CS380 What is form validation? 2 validation: ensuring that form's values

Form Validation 1 CS380 What is form validation? 2 validation: ensuring that form's values

Form Validation 1 CS380 What is form validation? 2 validation: ensuring that form's values are correct some types of validation: preventing blank values (email address) ensuring the type of values integer, real number,

284 views • 24 slides
EDRN BIOMARKER DEVELOPMENT Sam Hanash Fred Hutchinson Cancer Research Center CONTENTS 1- Two

EDRN BIOMARKER DEVELOPMENT Sam Hanash Fred Hutchinson Cancer Research Center CONTENTS 1- Two

EDRN BIOMARKER DEVELOPMENT Sam Hanash Fred Hutchinson Cancer Research Center CONTENTS 1- Two studies that progressed from discovery to blinded validation in a context of early detection 2- Collaborative work within and outside of EDRN

734 views • 27 slides
Chapter 5 Analysis: Four Level for Validation Vis/Visual Analytics, Chap 5 Validation 1 CGGM

Chapter 5 Analysis: Four Level for Validation Vis/Visual Analytics, Chap 5 Validation 1 CGGM

Chapter 5 Analysis: Four Level for Validation Vis/Visual Analytics, Chap 5 Validation 1 CGGM Lab., CS Dept., NCTU Jung Hong Chuang Contents Why Validate? Validation Approaches Domain Why is Validation Abstraction

724 views • 47 slides
Introduction to Data Science: Classifier n 1 n 1 k k Suppose you want to compare two

Introduction to Data Science: Classifier n 1 n 1 k k Suppose you want to compare two

Classier evaluation Classier evaluation Leave-one-out Cross-Validation Leave-one-out Cross-Validation Leave-one-out Cross-Validation Classier evaluation Classier evaluation Leave-one-out Cross-Validation Resampled validation set

984 views • 51 slides
AIRS Radiance Validation with the Scanning HIS aircraft instrument Hank Revercomb, David C.

AIRS Radiance Validation with the Scanning HIS aircraft instrument Hank Revercomb, David C.

AIRS Radiance Validation with the Scanning HIS aircraft instrument Hank Revercomb, David C. Tobin, Robert O. Knuteson, Fred A. Best University of Wisconsin-Madison, Space Science and Engineering Center AIRS Science Team Meeting Marriott,

1.1k views • 65 slides
Crisis to Calm: A Story of Data Validation @ Netflix Lavanya Kanchanapalli Rollback data

Crisis to Calm: A Story of Data Validation @ Netflix Lavanya Kanchanapalli Rollback data

Crisis to Calm: A Story of Data Validation @ Netflix Lavanya Kanchanapalli Rollback data Increase capacity Netflix starts to work Root Cause Duplicate objects Apps failed Cascading failures Netflix goes down! Data

778 views • 54 slides
Fred Sam Joe Fred Sam Joe A BRIEF HISTORY OF COMMUNICATIONS SECURITY 6 COMPUTER SECURITY

Fred Sam Joe Fred Sam Joe A BRIEF HISTORY OF COMMUNICATIONS SECURITY 6 COMPUTER SECURITY

THERE AND BACK AGAIN BRIAN CHESS SEPTEMBER 2013 Fred Sam Joe Fred Sam Joe A BRIEF HISTORY OF COMMUNICATIONS SECURITY 6 COMPUTER SECURITY 7 THE PROGRAMMER "Programming is hard" Donald Knuth Programmers not historically

350 views • 21 slides
Data Collection/Data Validation Presented by Dave Joubert CONTENTS Introduction

Data Collection/Data Validation Presented by Dave Joubert CONTENTS Introduction

Data Collection/Data Validation Presented by Dave Joubert CONTENTS Introduction Discussion Conclusion Introduction ATC Background APP and TWR (OR Tambo) Responsible for PBN Implementation in South Africa Report

346 views • 13 slides
approaches Dave Reynolds, Epimorphics Ltd @der42 Validation requirements based on experiences

approaches Dave Reynolds, Epimorphics Ltd @der42 Validation requirements based on experiences

Validation: requirements and approaches Dave Reynolds, Epimorphics Ltd @der42 Validation requirements based on experiences with data.gov.uk Linked Data Most current Linked Data in data.gov.uk is: described using a range of vocabularies

466 views • 7 slides
Todays Agenda VENDOR PRODUCT UPDATE DATA VALIDATION PROGRAM UPDATE DATASHARING

Todays Agenda VENDOR PRODUCT UPDATE DATA VALIDATION PROGRAM UPDATE DATASHARING

Todays Agenda VENDOR PRODUCT UPDATE DATA VALIDATION PROGRAM UPDATE DATASHARING CONTRACTING SCHEDULE FY2020 VPP III RFP KICK OFF January 21, 2020 I-95 Corridor Coalition VPP Validation 1 Update product listing coming

294 views • 18 slides
Capital Quality Validation Webinar Sept. 17, 2020 Agenda Validation Overview

Capital Quality Validation Webinar Sept. 17, 2020 Agenda Validation Overview

Capital Quality Validation Webinar Sept. 17, 2020 Agenda Validation Overview Validation Timeline Authorized Representative Validation Process How to Log In to QuickBase How to Reset Your Password How to

451 views • 43 slides
S Background Data from Thyssen et al., The epidemiology of contact allergy in the general

S Background Data from Thyssen et al., The epidemiology of contact allergy in the general

S Background Data from Thyssen et al., The epidemiology of contact allergy in the general population prevalence and main findings, Contact Dermatitis 2007: 57: 287299. S The proportion of nickel contact allergy prevalence out of

783 views • 29 slides

More recommend