Abstract. Real world healthcare systems are generally large and overly complex systems. Designing privacy-friendly protocols for such systems is a challenging task. In this paper we present a privacy-preserving protocol for the Belgian healthcare system. The proposed protocol protects the patients' privacy throughout the prescription handling process, while complying with most aspects of the current Belgian healthcare practise. The presented protocol relies on standard privacy-preserving credential systems, and verifiable public key cryptography, which makes it readily fit for implementation.

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Abstract. Advances in communication technology have opened a myriad of new possibilities for the remote delivery of healthcare. This new form of service delivery, not only contributes to the democratization of healthcare, by reaching far-away populations, but also makes it possible for elderly and chronically-ill patients to have their health monitored while in the comfort of their homes. Despite all of these advantages, however, patients are still resisting the idea of medical telemonitoring. One of the main obstacles facing the adoption of medical telemonitoring, is the concern among patients that their privacy may not be properly protected. We address this concern, and propose a privacy-preserving telemonitoring protocol for healthcare. Our protocol allows patients to selectively disclose their identity information, and guarantees that no health data is sent to the monitoring centre without the patients' prior approval. The approval process can be automated, and requires only an initial configuration by the patient.

Abstract. With the digitization of society and the continuous migration of services to the electronic world, individuals have lost significant control over their data. In this paper, we consider the problem of protecting personal information subjects. More specifically, we propose a new primitive allowing a data subject to decide when, how, and by whom his data can be accessed, without the database manager learning anything about his identity, at the time the data is retrieved. The proposed solution, which we call Accredited SPIR, combines symmetrically private information retrieval and privacy-preserving digital credentials. We present three constructions based on the discrete logarithm and RSA problems. Despite the added privacy safeguards, the extra cost incurred by our constructions is negligeable compared to that of the underlying building blocks.

Pipeline systems are an essential component of the oil and gas supply chain today. Although considered among the safest transportation methods, pipelines are still prone to failure due to corrosion and other types of defects. Such failures can lead to serious accidents resulting in big losses to life and the environment. It is therefore crucial for pipeline operators to reliably detect pipeline defects in an accurate and timely manner. Because of the size and complexity of pipeline systems, however, relying on human operators to perform the inspection is not possible. Automating the inspection process has been an important goal for the pipeline industry for a number of years.Significant progress has been made in that regard, and available techniques combine analytical modeling, numerical computations, and machine learning. This paper presents a survey of state of-the-art methods used to assess the safety of the oil and gas pipelines. The paper explains the principles behind each method, highlights the setting where each method is most effective, and shows how several methods can be combined to achieve a higher level of accuracy.