Abstract
The orchestration of high performance computing (HPC) services to build scientific applications is based on complex workflows. A challenging task consists of improving the reliability of such workflows, avoiding faulty behaviors that can lead to bad consequences in practice. This paper introduces a certifier component for certifying scientific workflows in a certification framework proposed for HPC Shelf, a cloud-based platform for HPC in which different kinds of users can design, deploy and execute scientific applications. This component is able to inspect the workflow description of a parallel computing system of HPC Shelf and check its consistency with respect to a number of safety and liveness properties specified by application designers and component developers.

Abstract

Abstract
This note revisits layered logics from a coalgebraic point of view, and proposes a naturality condition to express the typical hierarchical requirement under which all abstract transitions should be traceable in more specialised layers. © Springer International Publishing AG 2018.

Abstract
This lecture discusses the impact of digital transformation of governance mechanisms as a tool to promote sustainable development and more inclusive societies, in the spirit of the United Nations 2030 Agenda. Three main challenges are addressed: the pursuit of inclusiveness, trustworthiness of software infrastructures, and the mechanisms to enforce more transparent and accountable public institutions.

Abstract
In privacy-preserving processing of outsourced data a Cloud server stores data provided by one or multiple data providers and then is asked to compute several functions over it. We propose an efficient methodology that solves this problem with the guarantee that a honest-but-curious Cloud learns no information about the data and the receiver learns nothing more than the results. Our main contribution is the proposal and efficient instantiation of a new cryptographic primitive called Labeled Homomorphic Encryption (labHE). The fundamental insight underlying this new primitive is that homomorphic computation can be significantly accelerated whenever the program that is being computed over the encrypted data is known to the decrypter and is not secret—previous approaches to homomorphic encryption do not allow for such a trade-off. Our realization and implementation of labHE targets computations that can be described by degree-two multivariate polynomials. As an application, we consider privacy preserving Genetic Association Studies (GAS), which require computing risk estimates from features in the human genome. Our approach allows performing GAS efficiently, non interactively and without compromising neither the privacy of patients nor potential intellectual property of test laboratories.

Abstract
In this paper we show how Isolated Execution Environments (IEE) offered by novel commodity hardware such as Intel’s SGX provide a new path to constructing general secure multiparty computation (MPC) protocols. Our protocol is intuitive and elegant: it uses code within an IEE to play the role of a trusted third party (TTP), and the attestation guarantees of SGX to bootstrap secure communications between participants and the TTP. The load of communications and computations on participants only depends on the size of each party’s inputs and outputs and is thus small and independent from the intricacies of the functionality to be computed. The remaining computational load– essentially that of computing the functionality – is moved to an untrusted party running an IEE-enabled machine, an attractive feature for Cloud-based scenarios. Our rigorous modular security analysis relies on the novel notion of labeled attested computation which we put forth in this paper. This notion is a convenient abstraction of the kind of attestation guarantees one can obtain from trusted hardware in multi-user scenarios. Finally, we present an extensive experimental evaluation of our solution on SGX-enabled hardware. Our implementation is open-source and it is functionality agnostic: it can be used to securely outsource to the Cloud arbitrary off-the-shelf collaborative software, such as the one employed on financial data applications, enabling secure collaborative execution over private inputs provided by multiple parties.