We apply model learning on three SSH implementations to infer state machine models, and then use model checking to verify that these models satisfy basic security properties and conform to the RFCs. Our analysis showed that all tested SSH server models satisfy the stated security properties, but uncovered several violations of the standard.

Abstract Fluid animations in computer graphics show interactions with various kinds of objects. However, fluid flowing through a granular material such as sand is still not possible within current frameworks. In this paper, we present the simulation of fine granular materials interacting with fluids. We propose a unified Smoothed Particle Hydrodynamics framework for the simulation of both fluid and granular material. The granular volume is simulated as a continuous material sampled by particles. By incorporating previous work on porous flow in this simulation framework we are able to fully couple fluid and sand. Fluid can now percolate between sand grains and influence the physical properties of the sand volume. Our method demonstrates various new effects such as dry soil transforming into mud pools by rain or rigid sand structures being eroded by waves.

This paper presents the simulation of a fluid flowing through a porous deformable material. We introduce the physical principles governing porous flow, expressed by the Law of Darcy, into the Smoothed Particle Hydrodynamics (SPH) framework for simulating fluids and deformable objects. Contrary to previous SPH approaches, we simulate porous flow at a macroscopic scale, making abstraction of individual pores or cavities inside the material. Thus, the number of computational elements is kept low, while at the same time realistic simulations can be achieved. Our algorithm models the changing behavior of the wet material as well as the full two-way coupling between the fluid and the porous material. This enables various new effects, such as the simulation of sponge-like elastic bodies and water-absorbing sticky cloth.