When, in 2008, Satoshi Nakamoto envisioned the first distributed database management system that relied on cryptographically secured chain of blocks to store data in an immutable and tamper-resistant manner, his primary use case was the introduction of a digital currency. Owing to this use case, the blockchain system was geared towards efficient storage of data, whereas the processing of complex queries, such as provenance analyses of data history, is out of focus. The increasing use of Internet of Things technologies and the resulting digitization in many domains, however, have led to a plethora of novel use cases for a secure digital ledger. For instance, in the healthcare sector, blockchain systems are used for the secure storage and sharing of electronic health records, while the food industry applies such systems to enable a reliable food-chain traceability, e.g., to prove compliance with cold chains. In these application domains, however, querying the current state is not sufficient—comprehensive history queries are required instead. Due to these altered usage modes involving more complex query types, it is questionable whether today’s blockchain systems are prepared for this type of usage and whether such queries can be processed efficiently by them. In our paper, we therefore investigate novel use cases for blockchain systems and elicit their requirements towards a data store in terms of query capabilities. We reflect the state of the art in terms of query support in blockchain systems and assess whether it is capable of meeting the requirements of such more sophisticated use cases. As a result, we identify future research challenges with regard to query processing in blockchain systems.
A large number of food scandals (e. g., falsely declared meat or non-compliance with hygiene regulations) are causing considerable concern to consumers. Although Internet of Things (IoT) technologies are used in the food industry to monitor production (e. g., for tracing the origin of meat or monitoring cold chains), the gathered data are not used to provide full transparency to the consumer. To achieve this, however, three aspects must be considered: a) The origin of the data must be verifiable, i. e., it must be ensured that the data originate from calibrated sensors. b) The data must be stored tamper-resistant, immutable, and open to all consumers. c) Despite this openness, the privacy of affected data subjects (e. g., the carriers) must still be protected. To this end, we introduce the SHEEPDOG architecture that "shepherds" products from production to purchase to enable a trustworthy, secure, and privacy-aware food monitoring. In SHEEPDOG, attribute-based credentials ensure trustworthy data acquisition, blockchain technologies provide secure data storage, and finegrained access control enables privacy-aware data provision.
The ability to capture and quantify any aspect of daily life via sensors, enabled by the Internet of Things ( IoT ), data have become one of the most important resources of the 21 st century. However, the high value of data also renders data an appealing target for criminals. Two key protection goals when dealing with data are therefore to maintain their permanent availability and to ensure their integrity. Blockchain technology provides a means of data protection that addresses both of these objectives. On that account, blockchains are becoming increasingly popular for the management of critical data. As blockchains are operated in a decentralized manner, they are not only protected against failures, but it is also ensured that neither party has sole control over the managed data. Furthermore, blockchains are immutable and tamper-proof data stores, whereby data integrity is guaranteed. While these properties are preferable from a data security perspective, they also pose a threat to privacy and confidentiality, as data cannot be concealed, rectified, or deleted once they are added to the blockchain. In this paper, we therefore investigate which features of the blockchain pose an inherent privacy threat when dealing with personal or confidential data. To this end, we consider to what extent blockchains are in compliance with applicable data protection laws, namely the European General Data Protection Regulation ( GDPR ). Based on our identified key issues, we assess which concepts and technical measures can be leveraged to address these issues in order to create a privacy-by-design blockchain system.
eHealth provides great relief for patients and physicians. This means, patients au- tonomously monitor their condition via IoT medical devices and make these data available to physicians for analyses. This requires a data platform that takes care of data acquisition, management, and provisioning. As health data are highly sensitive, there are major concerns regarding data security with respect to confidentiality, integrity, and authenticity. To this end, we present a blueprint for constructing a trustworthy health data platform called SEAL. It provides a lightweight attribute-based authentication mechanism for IoT devices to validate all involved data sources, there is a fine-grained data provisioning system to enable data provision according to actual requirements, and a verification procedure ensures that data cannot be manipulated.
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