Millions of shipping containers filled with goods move around the world every day. Before such a container may enter a trade bloc, the customs agency of the goods’ destination country must ensure that it does not contain illegal or mislabeled goods. Due to the high volume of containers, customs agencies make a selection of containers to audit through a risk analysis procedure. Customs agencies perform risk analysis using data sourced from a centralized system that is potentially vulnerable to manipulation and malpractice. Therefore we propose an alternative: DEFenD, a decentralized system that stores data about goods and containers in a secure and privacy-preserving manner. In our system, economic operators make claims to the network about goods they insert into or remove from containers, and encrypt these claims so that they can only be read by the destination country’s customs agency. Economic operators also make unencrypted claims about containers with which they interact. Unencrypted claims can be validated by the entire network of customs agencies. Our key contribution is a data partitioning scheme and several protocols that enable such a system to utilize blockchain and its powerful validation principle, while also preserving the privacy of the involved economic operators. Using our protocol, customs agencies can improve their risk analysis and economic operators can get through customs with less delay. We also present a reference implementation built with Hyperledger Fabric and analyze to what extent our implementation meets the requirements in terms of privacy-preservation, security, scalability, and decentralization.@en

In the new Digital Economy, massive computer systems, often grouped in datacenters, serve as factories "producing" cloud services with massive consumption. However, to afford cloud services globally, we must address new research challenges in designing, operating, and using modern datacenters. We must also address challenges in educating and training the next generation of datacenter engineers. Addressing such challenges, in this work we present our vision on OpenDC: we envision the exploration of various datacenter concepts and technologies, using existing and new scientific methods, enabling new education practices and topics, and leading to the creation of new software and data artifacts. We present the datacenter concepts and technologies we are currently planning to explore using OpenDC. We identify the scientific methods we want to use, and explain our vision of education practices. We present the architecture and open-source program underlying the OpenDC software, and the format and open-access data we use for datacenter experiments. We conclude with an open invitation for the community to join our effort.@en