Fuzzified advanced robust hashes for identification of digital and physical objects

Abstract

With the rising numbers for IoT objects, it is becoming easier to penetrate counterfeit objects into the mainstream market by adversaries. Such infiltration of bogus products can be addressed with third-party-verifiable identification. Generally, state-of-the-art identification schemes do not guarantee that an identifier e.g. barcodes or RFID itself cannot be forged. This paper introduces identification patterns representing the objects intrinsic identity by robust hashes and not only by generated identification patterns. Inspired by these two notions, a collection of uniquely identifiable attributes called quasi-identifiers (QI) can be used to identify an object. Since all attributes do not contribute equally towards an object's identity, each QI has a different contribution towards the identifier. A robust hash developed utilising the QI has been named fuzzified robust hashes (FaR hashes), which can be used as an object identifier. Although the FaR hash is a single hash string, selected bits change in response to the modification of QI. On the other hand, other QIs in the object are more important for the object's identity. If these QIs change, the complete FaR hash is going to change. The calculation of FaR hash using attributes should allow third parties to generate the identifier and compare it with the current one to verify the genuineness of the object.