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CTA 5203

Cybersecurity Threats and Security Controls for Machine Learning Based Systems
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The scope of this whitepaper is confined to the cybersecurity challenges specific to ML-based systems. It provides an overview of unique cybersecurity threats and security controls practices and processes that should be considered when developing ML systems, with the caveat that threat landscapes are constantly evolving and mitigations can be application specific, depending on results of threat modelling and the architecture of the ML model being evaluated. This whitepaper does not present an exhaustive discussion of every cybersecurity threat or identify every possible cybersecurity vulnerability that may affect an ML system, but rather, it intends to raise awareness on the importance of cybersecurity of ML-based systems. For example, denial of service attacks are outside the scope of this document. It is assumed that the reader has an understanding of the general concepts of cybersecurity and the basic principles of securing systems. The reader is referred to external publications to gain an understanding of these concepts.
SDO CTA: Consumer Technology Association
Document Number 5203
Publication Date April 1, 2022
Language en - English
Page Count 15
Revision Level
Supercedes
Committee
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