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Data masking

Data masking or data obfuscation is the process of modifying sensitive data in such a way that it is of no or little value to unauthorized intruders while still being usable by software or authorized personnel. Data masking can also be referred as anonymization, or tokenization, depending on different context.

Different types, Techniques & Background

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Explore the main themes, entities and connections around Data masking. Start with the topic map, then use the sections below for research and deeper semantic analysis.

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Overview

Background

Techniques

Different types

Advanced semantic analysis

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Map overview Semantic statistics

Data masking

Nodes36
Edges35
Triples60
Avg. degree1.94
Density0.055556
Components1

How this topic connects Entity context

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Data masking

Top relations

related to background · 12
Data masking → Accordingly, Additional, Applications, Data, For, HR System, If, Social Security Number, The, Theoretically, This, Where
related to Encryption · 10
Data masking → Advanced Encryption Standard, AES, Encryption, New, NIST, Old, Recently, The, These, This
related to Data masking and the cloud · 8
Data masking → Data, Dynamic Data Masking, In, PII, SDLC, SLAs, The, There
related to On-the-fly data masking · 8
Data masking → Dynamic Data Masking, Having, In, On-the-fly, Organizations, The, This, Thus
related to Substitution · 6
Data masking → For, If, It, Substitution, There, Using
related to Dynamic data masking · 4
Data masking → Dynamic, Europe, Privacy, Singapore Monetary Authority
related to Nulling out or deletion · 4
Data masking → In, It, Sometimes, The
related to Statistical data obfuscation · 3
Data masking → DataSifter, Examples, There
related to Different types · 2
Data masking → Data, Two
related to Static data masking · 2
Data masking → In DB, Static

Important terminology Word statistics

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Important terminology

data masking also database masked applied production applications application dynamic method value information test security set may databases systems environments

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
payrollinstance ofa method utilising this manner of masking can still leave a meaningful range in a financial data set0.80text
Data maskingrelated to backgroundData0.60section
Data maskingrelated to backgroundThe0.60section
Data maskingrelated to backgroundFor0.60section
Data maskingrelated to backgroundSocial Security Number0.60section
Data maskingrelated to backgroundIf0.60section
Data maskingrelated to backgroundHR System0.60section
Data maskingrelated to backgroundTheoretically0.60section
Data maskingrelated to backgroundAccordingly0.60section
Data maskingrelated to backgroundApplications0.60section
Data maskingrelated to backgroundThis0.60section
Data maskingrelated to backgroundAdditional0.60section

Related concept clusters Concept neighborhoods

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    Connections between topic areas Semantic bridges

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    Min side: 3
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