Equivalent business data can have different textual forms. Hashing and signing need a shared representation to avoid ambiguity and false rejection.
Evaluation approach
Specify ordering, numbers, nulls and character encoding. Apply the same canonicalization rules on both sides.
Application example
Do not casually equate textual amounts with floating-point values. Define currency and precision explicitly.
Limits and considerations
Canonicalization makes representations comparable; it does not establish business legitimacy.
Representing numeric fields
Use stable protocol representation for financial values with explicit currency and precision. Compare boundary cases instead of relying on ad hoc floating-point conversion.
Checks and decisions
- Define number types
- Test Unicode
- Compare implementations
Sources
The primary references above provide the technical basis. Example workflows and evaluation suggestions are this publication’s explanations, not independent test results for a particular product.