Data Privacy and Data Security: Understanding the difference | Part One

Updated: Sep 3

Unauthorised access to personally identifiable information is one of the most pressing concerns facing both consumers and businesses in 2021.


With data breaches presenting an array of consequences to businesses, and data subjects continuing to disperse sensitive data across the internet - the importance of protecting data is well and truly realised.


As businesses continue to install strategies to prevent unauthorised access, as well as maintaining compliance with data protection laws, the topics of data privacy and data security continue to be ever-present.


However, with no clear universal definition of data privacy - even within the European Union’s General Data Protection Regulation (GDPR) law, these two terms are often substituted for one another – leading to confusion, ambiguity, and waste of resources.


In this two-part series, we examine the differences between data privacy and data security, as well as the core techniques currently employed in data security measures, the challenges that data privacy faces, and how our DataSecOps platform can help.

Data Security vs Privacy: The fundamental differences.

While data privacy and data security both serve the same goals – protecting sensitive and personally identifiable information – they both achieve this in distinctly different ways. Data privacy ensures that sensitive information is correctly interacted with, managed, retained, removed, and stored under data protection laws.


Data security, on the other hand, ensures that sensitive data resides in secure locations. With security systems and techniques in place such as data masking and encryption. In doing so, data security strategies aim to reduce the chances of damaging cyber attacks and breaches occurring. Understanding data security

Data security primarily aims to protect the personal data of subjects from any unauthorised access, attack, or exploitation. It accomplishes this by introducing other strategies and techniques to a business’s architecture. Many data security measures strive to eliminate the possibility of human error providing unwanted entry points into a secure framework - weaknesses that attacks such as phishing emails seek to exploit. In 2021, human error is responsible for an estimated 88% of data breaches, therefore limiting this potential is a necessity to businesses of any size. Some examples of these measures include:

  • User Entity Behavioural Analysis

  • Access controls

  • Biometric protection

  • Encrypted data

  • Multi-factor authentication

These techniques are being realised as increasingly necessary as cyber attacks continue to target businesses of any size with equal intent. Last year, the probability of a small business being targeted by a cyber attack rose to 47%, while the average global cost of a data breach continued to rise to GBP 2.78 million.

This emphasis on integrating additional security measures defines the role of data security within an organisation as being entirely separate from the role of data privacy.

Learn more

In our second part, we’ll examine more closely the role of data privacy, as well as the current challenges affecting the data privacy landscape and how our DataSecOps platform can help.


To learn more, why not visit our blog for the latest insights and discussions on pressing data privacy issues.

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