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.

翻译：随着物联网对象数量的增长，攻击者更容易将伪造对象渗透到主流市场中。此类假冒产品的渗透可通过第三方可验证的识别来解决。一般来说，最先进的识别方案无法保证标识符（如条形码或RFID）本身不可伪造。本文提出了一种识别模式，该模式通过鲁棒哈希而非仅通过生成的识别模式来表示对象的固有身份。受这两个概念的启发，一组称为准标识符（QI）的唯一可识别属性可用于识别对象。由于所有属性对对象身份的贡献并不相同，每个准标识符对标识符的贡献也不同。利用准标识符开发的鲁棒哈希被称为模糊化鲁棒哈希（FaR哈希），可用作对象标识符。尽管FaR哈希是一个单一的哈希字符串，但选定的比特会随着准标识符的修改而变化。另一方面，对象中的其他准标识符对对象身份更为重要。如果这些准标识符发生变化，整个FaR哈希将随之改变。使用属性计算FaR哈希应允许第三方生成标识符，并将其与当前标识符进行比较，以验证对象的真实性。