Biblio

Traditional public key infrastructures (PKIs), in particular, X.509 and PGP, is plagued by security and usability issues. As reoccurring incidents show, these are not only of theoretical nature but allow attackers to inflict severe damage. Emerging blockchain technology allows for advances in this area, facilitating a trustless immutable ledger with fast consensus. There have been numerous proposals for utilization of the blockchain in the area of PKI, either as extensions upon existing methods or independent solutions. In this paper, we first study traditional PKI, then proceed with novel approaches, showing how they can improve upon recent issues. We provide a comprehensive evaluation, finding that independent blockchain-based solutions are preferable in the future, mainly due to their stronger security. However, global adoption of these yet requires advances in blockchain development, e.g., concerning scalability.

The use of blockchain technology to track physical assets is not new. However, the state of the art concepts are not applicable due to several limitations. One limitation is the scalability of blockchains with regard to the number of transactions that can be processed by the network. The well-established technology in tracking products is based on RFID chips that can be cloned. This paper provides insights into how objects can be protected and monitored by a varnish with a unique crack pattern, as an example of a Physical Unclonable Function. The perceptual hash of the unique pattern is used to encrypt the associated data to ensure privacy. Instead of logging each event on the blockchain individually, which is not possible due to the limited transaction throughput, OriginStamp is used to preserve data integrity on the blockchain. OriginStamp aggregates events, combines them through hashing and embeds this hash into a Bitcoin transaction. Once the Bitcoin network mines the transaction into a block and confirms it, the timestamp is considered as immutable proof of existence. With this approach, the integrity of tracking data cannot be contested. In the future, the craquelure-based tracking approach could be extended to supply chain integration to secure the origin of products, including prevention of counterfeiting, securing the place of manufacture for trademark law or state surveillance of the agricultural economy.

Mathematical formulae are essential in science, but face challenges of ambiguity, due to the use of a small number of identifiers to represent an immense number of concepts. Corresponding to word sense disambiguation in Natural Language Processing, we disambiguate mathematical identifiers. By regarding formulae and natural text as one monolithic information source, we are able to extract the semantics of identifiers in a process we term Mathematical Language Processing (MLP). As scientific communities tend to establish standard (identifier) notations, we use the document domain to infer the actual meaning of an identifier. Therefore, we adapt the software development concept of namespaces to mathematical notation. Thus, we learn namespace definitions by clustering the MLP results and mapping those clusters to subject classification schemata. In addition, this gives fundamental insights into the usage of mathematical notations in science, technology, engineering and mathematics. Our gold standard based evaluation shows that MLP extracts relevant identifier-definitions. Moreover, we discover that identifier namespaces improve the performance of automated identifier-definition extraction, and elevate it to a level that cannot be achieved within the document context alone.