Privacy, Confidentiality, and Security

Context: FIT1043_MOC · the protection concerns of data governance · three distinct ideas often confused · links to datafication

Quick Revision

  • 🎯 Objective: separate three protection concepts ➔ privacy (control of self), confidentiality (info about you), security (protecting the data).
  • 📦 Core Components: privacy | confidentiality | security | implicit vs explicit data.
  • ⚡ Key Constraint: implicit data — facts inferred from your data (not given) — is the sneaky threat to confidentiality (pregnancy from purchases, traits from “likes”).

📝 How It Works

1. The Three Concepts

  • Privacy ➔ having control over how one shares oneself with others (e.g. closing the blinds in your living room).
  • Confidentialityinformation privacy — how information about an individual is treated/shared (e.g. excluding others from your search/browse history).
  • Security ➔ the protection of data, preventing improper use (e.g. stopping hackers stealing credit-card data).

2. Implicit vs Explicit Data

  • Explicit data ➔ information a consumer actively provides (name, gender, email, home address — e.g. at signup).
  • Implicit datanot explicitly stored but inferred with reasonable precision from available data.

3. Loss of Confidentiality (social media)

  • Prediction ➔ retailers predicting pregnancy from purchases; many traits inferred from Facebook “likes” (“curly fry conundrum”).
  • Consumer control ➔ often you must accept a data-sharing policy or can’t fully use a service; ideally an agent asks “share your health data with company X?“.

⚖️ Core Decision Matrix

TermProtectsExample
Privacycontrol of self-disclosureclosing the blinds
Confidentialityinformation about youhiding browse history
Securitythe data itselfblocking a hacker

When It Flips: the three chain together — security failures (a breach) expose confidential information, which erodes privacy; and implicit inference can breach confidentiality even with no explicit data leaked.

🧠 Active Recall