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ISO/IEC 27045


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ISO/IEC 27045 — Information technology — Big data security and privacy — Processes [DRAFT]

 

Abstract

Defines process reference, assessment and maturity models for the domain of big data security and privacy. These models are focused on process architecture and the processes used to achieve big data security and privacy, most specifically on the maturity of those processes.
[Source: SC27 Standing Document 11 (2021)]
 

Introduction

This standard will offer guidance to organizations on the data security and privacy aspects relating to big data processing systems.

 

Scope & purpose

The 2021 Preliminary Work Item (an initial draft) says:

“The purpose of this document is to provide guidelines for organizations to apply security measures for building their big data management framework. The security measures defined in this document can help to defend the risks caused by big data characteristics described in ISO/IEC 20547-4.”

 

Content

TBA

 

Status

Having run off the rails, the drafting project was re-started in 2021.

 

Personal comments

Aug update The currently-adopted definition of ‘big data’ in the draft standard does not (in my personal, rather jaundiced and cynical opinion) reflect its widespread use in the IT industry at present, mostly because of the vagueness of ‘extensive’ which is essentially synonymous with, and adds little clarity to, plain ‘big’.  ‘Big data’ is defined as:

“Extensive datasets - primarily in the characteristics of volume, variety, velocity, and/or variability - that require a scalable architecture for efficient storage, manipulation, and analysis. [Source: ISO/IEC 20546]”

Wikipedia is more helpful e.g.:

“Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.

For me, one of the defining characteristics of big data is that typical (these days mostly relational) database management systems struggle or are unable to cope with the complexity and dynamics/volatility of truly massive data sets. Beyond the limits of their scalability, conventional architectures experience constraints and failures, no matter how much raw CPU power is thrown at the problems. That implies the need for fundamentally different approaches and I rather suspect entails novel information risks and hence security/privacy controls. However, it remains to be seen what this standard will actually address in practice: this is cutting-edge stuff.

Hopefully this standard will refer to others for the low-level and relatively conventional data security and privacy controls that apply to small and medium data, focusing instead on the high-level and novel aspects and processes that are unique to big data e.g.:

  • Strategic management of big data sets, big data systems etc., including governance arrangements to monitor and control the management and operational activities as a whole (e.g. overall programme as well as individual project management) and the business/strategy aspects and requirements (e.g. enormous financial investment in huge systems implies enormous expected returns);
  • Architecture and design of big data systems - specifically the data security and privacy aspects including information risk assessment, compliance, ethics, data aggregation, inference, interconnectivity (both within and without the organization), access controls, metadata management and security, resilience etc.;
  • Operation and use of big data systems e.g. how to classify and segregate data and functions, how to determine/define and assign access rights/permissions, what privacy and security roles and responsibilities might be appropriate;
  • Maintenance and support of big data systems, including their security and privacy aspects;
  • Capacity and performance management including the dynamics and challenges arising;
  • Incident management, change management and so on (adapting conventional processes for the big data environment).

Potentially, the standard could get into advanced/cutting-edge data/system security controls and privacy approaches involving artificial intelligence, instrumentation, anomaly and fraud detection, automated responses etc. ... but I suspect the standard’s initial release will be more basic, and it appears to be focused on the processes rather than techologies (we’ll see how that turns out in practice!).

 

 

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