Jusletter IT

Data Protection Management System

A Useful Step Further to Protect Intellectual Capital?

  • Authors: Philipp E. Fischer / Ricardo Morte Ferrer
  • Category: Articles
  • Region: Germany
  • Field of law: Data Protection
  • Collection: Conference Proceedings IRIS 2015
  • Citation: Philipp E. Fischer / Ricardo Morte Ferrer, Data Protection Management System, in: Jusletter IT 26 February 2015
Within the validity of the current data protection legislation and the proposed General Data Protection Regulation, an organization which processes personal data, has to give proof that its business processes do not affect people´s personal data in an unacceptable way. To furnish proof of this will be increasingly difficult because of the ever-increasing amount whilst collection, processing and use of personal data in the future economy. The future level of data protection in such cases will therefore increasingly depend on a more structural approach. To solve this problem, this contribution suggests the setting up of a Data Protection Management System (DPMS) based on the principles of an Information Management System (ISMS) and explained in detail by a practical example of an accurate Data Governance.

Table of contents

  • 1. Background
  • 1.1. Interdependences between Data Protection and Corporate Processes
  • 1.2. Business drivers for a Data Protection Management System
  • 1.2.1. Personal Data, Information Lifecycle and Privacy by Design / Default principles
  • 1.2.2. Intellectual Capital
  • 1.2.3. Conceptualization
  • 1.3. Business drivers for Data Governance
  • 2. Relationship between DPMS and Data Governance as part of an ISMS
  • 2.1. Supportive and opposing principles
  • 2.2. How to combine different approaches
  • 3. Achieving conformance with laws, guidelines and principles
  • 3.1. German Data Protection Law (BDSG)
  • 3.2. International laws, guidelines and principles
  • 4. Example: Whitebox Security’s WhiteOPS™ Data Governance 
  • 4.1. Define Unstructured Data
  • 4.2. Securing Unstructured Data
  • 4.3. Structured & Unstructured Data Eco-Systems
  • 4.4. Requirements for an effective solution
  • 5. Conclusion
  • 6. Literatur

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