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Access status: Open Access ,
A cellular automata models of evolution of transportation networks
(Wydawnictwa AGH, 2002) Topa, Paweł; Paszkowski, Mariusz
We present a new approach to modelling of transportation networks. Supply of resources and their influence on the evolution of the consuming environment is a principal problem considered. We present two concepts, which are based on cellular automata paradigm. In the first model SCAMAN (Simple Cellular Automata Model of Anastomosing Network), the system is represented by a 2D mesh of elementary cells. The rules of interaction between them are introduced for modelling of the waterflow and other phenomena connected with anastomosing river. Due to limitations of SCAMAN model, we introduce a supplementary model. The MANGraCA (Model of Anastomosing Network with Graph of Cellular Automata) model beside the classical mesh of automata, introduces an additional structure: the graph of cellular automata, which represents the network pattern. Finally we discuss the prospective applications of the models. The concepts of future implementation are also presented.
Access status: Open Access ,
Using shared memory as a cache in cellular automata water flow simulations on GPUs
(Wydawnictwa AGH, 2013) Topa, Paweł; Młocek, Paweł
Graphics processors (GPU – Graphic Processor Units) recently have gained a lot of interest as an efficient platform for general-purpose computation. Cellular Automata approach which is inherently parallel gives the opportunity to implement high performance simulations. This paper presents how shared memory in GPU can be used to improve performance for Cellular Automata models. In our previous works, we proposed algorithms for Cellular Automata model that use only a GPU global memory. Using a profiling tool, we found bottlenecks in our approach. With this paper, we will introduce modifications that takes an advantage of fast shared memory. The modified algorithm is presented in details, and the results of profiling and performance test are demonstrated. Our unique achievement is comparing the efficiency of the same algorithm working with a global and shared memory.
Access status: Open Access ,
Toward RAM forensics supported by machine-learning methods
(Wydawnictwa AGH, 2025) Jurczyk, Kamil; Topa, Paweł; Faber, Łukasz
In this article, we propose an enhancement to the computer forensics technique of using Machine-Learning tools to analyze the contents of RAM in order to extract information that is potentially useful during an investigation. In the specific case presented, the use of the extracted information to generate moreoptimal dictionaries for dictionary cryptanalysis is considered. Increasing user awareness is making cryptanalysis of passwords increasingly difficult for law enforcement. Long and complex passwords are impossible to crack – even when high-performance computing platforms are available. A sensible method of optimization is to look for hints to use a dictionary that contains text phrases more likely to be used in the specific case under attack. Such a hint could be an analysis of RAM taken from a suspect computer. Machine-learning methods can significantly facilitate this task. In this article, we also explore the effectiveness of such an approach and its usefulness in practical applications. We also consider applications of the proposed approach for other purposes, such as OSINT.

Topa, Paweł

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