Background: Newly approved immunotherapeutic agents, like CTLA-4 inhibitors and antibodies against PD-1, are a promising therapeutic option in cancer therapy.
Case presentation: A 74-year-old man, with a history of advanced stage melanoma and treatment with ipilimumab, pembrolizumab and nivolumab, was admitted to the hospital due to respiratory failure with hypoxemia and dyspnoea. He rapidly developed severe acute respiratory distress syndrome (ARDS), which required treatment in the intensive care unit which included mechanical ventilation and extracorporeal membrane oxygenation (ECMO). Computed tomographic imaging (CT) showed signs of a pneumonitis, with an ARDS pattern related to the use of PD-1 antibodies. Treating the patient with high-dose immunosuppressive steroids led to an overall improvement. He was transferred to a rehabilitation hospital and subsequently to his home.
Discussion and conclusion: This is a unique case report of a patient suffering a grade 4 adverse event under nivolumab who survived having been treated with ECMO. It highlights the possibility of associated adverse reactions as well as the use of ECMO in palliative care patients. ECMO can be of great success even in patients with malignancies, but careful decision making should be done on a case by case basis.
The Stable Matching (SM) algorithm has been deployed in many real-world scenarios including the National Residency Matching Program (NRMP) and financial applications such as matching of suppliers and consumers in capital markets. Since these applications typically involve highly sensitive information such as the underlying preference lists, their current implementations rely on trusted third parties. This paper introduces the first provably secure and scalable implementation of SM based on Yao’s garbled circuit protocol and Oblivious RAM (ORAM). Our scheme can securely compute a stable match for 8k pairs four orders of magnitude faster than the previously best known method. We achieve this by introducing a compact and efficient sub-linear size circuit. We even further decrease the computation cost by three orders of magnitude by proposing a novel technique to avoid unnecessary iterations in the SM algorithm. We evaluate our implementation for several problem sizes and plan to publish it as open-source.
Private set intersection (PSI) is a cryptographic technique that is applicable to many privacy-sensitive scenarios. For decades, researchers have been focusing on improving its efficiency in both communication and computation. However, most of the existing solutions are inefficient for an unequal number of inputs, which is common in conventional client-server settings. In this paper, we analyze and optimize the efficiency of existing PSI protocols to support precomputation so that they can efficiently deal with such input sets. We transform four existing PSI protocols into the precomputation form such that in the setup phase the communication is linear only in the size of the larger input set, while in the online phase the communication is linear in the size of the smaller input set. We implement all four protocols and run experiments between two PCs and between a PC and a smartphone and give a systematic comparison of their performance. Our experiments show that a protocol based on securely evaluating a garbled AES circuit achieves the fastest setup time by several orders of magnitudes, and the fastest online time in the PC setting where AES-NI acceleration is available. In the mobile setting, the fastest online time is achieved by a protocol based on the Diffie-Hellman assumption.
Decision trees and random forests are widely used classifiers in machine learning. Service providers often host classification models in a cloud service and provide an interface for clients to use the model remotely. While the model is sensitive information of the server, the input query and prediction results are sensitive information of the client. This motivates the need for private decision tree evaluation, where the service provider does not learn the client’s input and the client does not learn the model except for its size and the result.
In this work, we identify the three phases of private decision tree evaluation protocols: feature selection, comparison, and path evaluation. We systematize constant-round protocols for each of these phases to identify the best available instantiations using the two main paradigms for secure computation: garbling techniques and homomorphic encryption. There is a natural tradeoff between runtime and communication considering these two paradigms: garbling techniques use fast symmetric-key operations but require a large amount of communication, while homomorphic encryption is computationally heavy but requires little communication. Our contributions are as follows: Firstly, we systematically review and analyse state-of-the-art protocols for the three phases of private decision tree evaluation. Our methodology allows us to identify novel combinations of these protocols that provide better tradeoffs than existing protocols. Thereafter, we empirically evaluate all combinations of these protocols by providing communication and runtime measures, and provide recommendations based on the identified concrete tradeoffs.
The Border Gateway Protocol (BGP) computes routes between the organizational networks that make up today’s Internet. Unfortunately, BGP suffers from deficiencies, including slow convergence, security problems, a lack of innovation, and the leakage of sensitive information about domains’ routing preferences. To overcome some of these problems, we revisit the idea of centralizing and using secure multi-party computation (MPC) for interdomain routing which was proposed by Gupta et al. (ACM HotNets’12). We implement two algorithms for interdomain routing with state-of-the-art MPC protocols. On an empirically derived dataset that approximates the topology of today’s Internet (55 809 nodes), our protocols take as little as 6 s of topology-independent precomputation and only 3 s of online time. We show, moreover, that when our MPC approach is applied at country/region-level scale, runtimes can be as low as 0.17 s online time and 0.20 s pre-computation time. Our results motivate the MPC approach for interdomain routing and furthermore demonstrate that current MPC techniques are capable of efficiently tackling real-world problems at a large scale.
In January 2014, the first ever comprehensive winter census of the Whitetailed Eagle Haliaeetus albicilla along the Danube River was conducted, using mostly point and transect counts. Altogether, 550-700 eagles were counted. The upper range of the estimate may in fact be more realistic because 615 km of the Danube were not surveyed. Birds were observed in every country along the Danube. Hotspots of occurrences were (1) the Central Danube floodplains - the area encompassing the lower Hungarian section (Danube- Drava National Park), Kopački rit Nature Park (Croatia), and the Gornje Podunavlje Special Nature Reserve (Serbia); and (2) the Danube Delta Biosphere Reserve. According to the Action Plan for the conservation of the White-tailed Eagle along the Danube, future winter counts should be made regularly, and lower variation in the resulting eagle numbers achieved by a higher degree of synchronization between individual countries. This study reinforces the importance of protected areas along the Danube as a backbone for the conservation of White-tailed Eagles and biodiversity.