We present an abstraction of the probabilistic semantics of Multiset Rewriting to formally express systems of reactions with uncertain kinetic rates. This allows biological systems modelling when the exact rates are not known, but are supposed to lie in some intervals. On these (abstract) models we perform probabilistic model checking obtaining lower and upper bounds for the probabilities of reaching states satisfying given properties. These bounds are under- and over-approximations, respectively, of the probabilities one would obtain by verifying the models with exact kinetic rates belonging to the intervals.

Email communication is growing as a main method for individuals and organizations to communicate. Sadly, this is also an emerging means of conducting crime in the cyber world, e.g. identity theft, virus attacks etc. The need for improving awareness to these threats amongst employees is evident in media reports. Information security is as much a people issue as a technology one. This paper presents a description and results of an email awareness experiment that was performed amongst staff from a South African university. It is shown how management can use these results to focus and improve ICT awareness.

In this paper, we present a HMM based system that is used to recognize ultra low resolution text such as those frequently embedded in images available on the web. We propose a system that takes specifically the challenges of recognizing text in ultra low resolution images into account. In addition to this, we show in this paper that word models can be advantageously built connecting together sub-HMM-character models and inter-character state. Finally we report on the promising performance of the system using HMM topologies which have been improved to take into account the presupposed minimum length of each character.

We present the problem of enforcing a Digital Rights Management (DRM) system that needs to consider location-dependent licensing policies and operates on top of existing conditional access standards. A major application for location-dependent DRM is Pay-TV broadcasting as rightsholders require different business models in different regions. A global provider’s enduser equipment needs to validate the user location in some way in order to enforce DRM in this scenario. We will depict several solutions to the problem and compare their security qualities. The main result is that trusted computing hardware may not be the most appropriate solution given reasonable conditions.

We consider a private zero-bit watermark (WM) system in which an unauthorized removal of the WM is restricted by a linear filtering of the watermarked message combined with additive noise attack. It is assumed that a WM detector knows both the original cover message (CM) and the pulse (or frequency) response of the attack filter. The formulas to calculate the WM-missing and WM-false alarm probabilities are developed and proved. We conclude that whenever some filtering of the watermarked message is yet acceptable with respect to CM quality then there results in a degradation of the WM system even if the designer of the WM uses an optimal signal. This fact is different than most that can be found at current WM literature. The main properties of a WM system under a filtering and additive noise attack condition are confirmed by simulations of the watermarked images.

In this paper, we present an efficient fixed-size systolic array for Montgomery's modular multiplication. The array is designed by the LPGS (Locally Parallel Globally Sequential) partition method [14] and can perform efficiently modular multiplication for the input data with arbitrary bits. Also, we address a computation pipelining technique, which improves the throughput and minimizes the buffer size used. With the analysis of VHDL simulation, we discuss a gap between a theoretical optimal number of partition and an empirical one.

In this paper a system is presented able to reproduce the actions of multiple moving objects into a 3D model. A multi-camera system is used for automatically detect, track and classify the objects. Data fusion from multiple sensors allows to get a more precise estimation of the position of detected moving objects and to solve occlusions problem. These data are then used to automatically place and animate objects avatars in a 3D virtual model of the scene, thus allowing users connected to this system to receive a 3D guide into the monitored environment.