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Database Privacy
Data Matching
Data Matching
Building a profile by combining data from different networks
Tax
Credit card records
Bank records
Phone records
Internet history
Email
Texts
Data Mining
Finding hidden patterns and trends in large databases
Recommendations
Profiling
Facebook
email
Facebook Data
How do we protect privacy?
Concent
Terms of Services
Purpose
Distribution
Length of Storage
Security
Privacy Policy / Data Poicy
Opt-in / Opt-out
Largest Databases
Amazon
ChoicePoint
Sprint
Google User Data
Security
Authorized access to Data
Remotely Stored
In transit
Local
Ways to Protect data
Passwords
Two step authentication
Encryption
Security settings.
Hackers will access data in different ways.
in transit
brute force access
Data Integrity
Making sure that data is correct, relevant and up to date
Errors in data can have serious consequences
How can data be wrong?
Out of Date
Entered incorrectly
Transferred from another database (badly)
Changed accidentally
Changed deliberately
Incomplete
Totally missing
Database Privacy and Security
By Victor Castro
Made with Slides.com
Database Privacy and Security
detabase privacy
529
Victor Castro
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Victor Castro