Credit and debit card data theft is one of the earliest forms of cybercrime. Still, it is one of the most common nowadays. Attackers often aim at stealing such customer data by targeting the Point of Sale (for short, PoS) system, i.e. the point at which a retailer first acquires customer data. Modern PoS systems are powerful computers equipped with a card reader and running specialized software. Increasingly often, user devices are leveraged as input to the PoS. In these scenarios, malware that can steal card data as soon as they are read by the device has flourished.

The increasing need for performing expensive computations has motivated outsourced computing, as in crowdsourced applications leveraging worker cloud nodes. However, these outsourced computing nodes can potentially misbehave or fail. Exploiting the redundancy of nodes can help guaranteeing correctness and availability of results. This entails that reliable distributed computing can be achieved at the expense of convenience.

Graphics processing units (GPUs) are increasingly common on desktops, servers, and embedded platforms. In this article, we report on new security issues related to CUDA, which is the most widespread platform for GPU computing. In particular, details and proofs-of-concept are provided about novel vulnerabilities to which CUDA architectures are subject. We show how such vulnerabilities can be exploited to cause severe information leakage. As a case study, we experimentally show how to exploit one of these vulnerabilities on a GPU implementation of the AES encryption algorithm.

A new algorithm for the solution of free surface flows with large front deformation and fragmentation is presented. The algorithm is obtained by coupling a classical Finite Volume (FV) approach, that discretizes the Navier-Stokes equations on a block structured Eulerian grid, with an approach based on the Smoothed Particle Hydrodynamics (SPH) method, implemented in a Lagrangian framework.

The identification of the basic mechanisms responsible for cardiovascular diseases stands as one of the most challenging problems in modern medical research including various mechanisms which encompass a broad spectrum of space and time scales. Major implications for clinical practice and pre-emptive medicine rely on the onset and development of intraluminal thrombus in which effective clinical therapies require synthetic risk predictors/indicators capable of informing real-time decision-making protocols.

In [Comm. Appl. Math. Comput. Sci., 4 (2009), pp. 153-175], Barenblatt presents a model for partial laminarization and acceleration of shear flows by the presence of suspended particles of different sizes, and provides a formal asymptotic analysis of the resulting velocity equation. In the present paper we revisit the model. In particular we allow for a continuum of particle sizes, rewrite the velocity equation in a form which involves the Laplace transform of a given function or measure, and provide several rigorous asymptotic expansions for the velocity.

Eugenio Elia Levi (1883-1917) fu uno dei più grandi matematici italiani del 900, come del resto il fratello Beppo. La sua produzione scientifica fu tanto profonda quanto differenziata, venne immediatamente apprezzata negli ambienti matematici internazionali e, a distanza di un secolo, conserva grande attualità in diversi campi della matematica. Momento importantissimo per la sua formazione fu la permanenza nella Scuola Normale Superiore di Pisa.

Bioventing is a clean-up technology essentially used to remove hydrocarboon from polluted subsoil by the action of microorganism. The model is based on the theory of fluid flows in porous media and on the mathematical description of population dynamics. The numerical results of a simplified model will be described.