Computer Science
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ISSN 1508-2806
e-ISSN: 2300-7036
Issue Date
2019
Volume
Vol. 20
Number
No. 2
Description
Reviewed by: Krzysztof Wajda, Piotr Dziurzanski, Daniela Milosevic, Samed Jukic, Sead Masovic, Piotr Arabas, Aleksander Byrski, Jerzy Pejas, Manuj Darbari, Marcin Kurdziel, Daniela Zaharie, Jerzy Domzal, Piotr Nawrocki
Journal Volume
Computer Science
Vol. 20 (2019)
Projects
Pages
Articles
Flow caching effectiveness in packet forwarding applicati
(Wydawnictwa AGH, 2019) Czekaj, Maciej; Jamro, Ernest
Routing algorithms are known to be potential bottlenecks for packet processing. Network ow caching can function as a general acceleration technique for packet processing workloads. The goal of this article is to evaluate the effectiveness of packet ow caching techniques in high-speed networks. The area of focus is the data distribution characteristics that lead to the effectiveness of caching network ows (connections). Based on a statistical analysis and simulations, the article sets the necessary conditions for the effective use of caches in packet forwarding applications. Public domain network traces were examined and measured for data locality. Software simulations show a strong correlation between the ow packet distance metrics and the cache hit rate.
Installation and testing the lofar software on ACC Cyfronet cluster Prometheus
(Wydawnictwa AGH, 2019) Kuligowska, Elżbieta; Czuchry, Maciej; Chyży, Krzysztof; Kundera, Tomasz; Roskowiński, Carole; Dziełak, Marta A.
We present the actual status and the most important issues related to the installation of the data reduction LOFAR software on high power computer Prometheus located in ACC Cyfronet. We refer to the software itself as well its practical use cases in the context of the scientific tool and the detailed installation/testing methodology. We address most typical challenges and problems that occurred during our attempts to set up the complete and ready-to-use LOFAR environment (including not only programs, but also libraries, scripts and other additional tools) on non-standard (cluster-type) computing system. The result of these works is then briey summarized. We also discuss the is- sues related to LOFAR documentation, maintenance, distribution and further development. Finally, we propose some future improvements.
A client-based encryption model for secure data storing in publicly available storage systems
(Wydawnictwa AGH, 2019) Retinger, Marek
This document presents a conceptual model of a system for protecting thedata stored in publicly available data storage systems. The main idea was toapply encryption on both the client and server sides that would consequentlyhave a significant impact on data security. The compatibility with existingsystems allows us to deploy the solution fast and at a low cost. The testsconducted on a simplified implementation have confirmed the solution’s validity,and they have shown some possible performance issues as compared to theclassical system (which can be easily bypassed).
Memoization method for storing of minimum-weight triangulation of a convex polygon
(Wydawnictwa AGH, 2019) Selimi, Aybeyan; Krrabaj, Samedin; Saračević, Muzafer; Pepić, Selver
This study presents a practical view of dynamic programming, specifically in the context of the application of finding the optimal solutions for the polygon triangulation problem. The problem of the optimal triangulation of polygon is considered to be as a recursive substructure. The basic idea of the constructed method lies in finding to an adequate way for a rapid generation of optimal triangulations and storing - them in as small as possible memory space. The upgraded method is based on a memoization technique, and its emphasis is in storing the results of the calculated values and returning the cached result when the same values again occur. The significance of the method is in the generation of the optimal triangulation for a large number of n. All the calculated weights in the triangulation process are stored and performed in the same table. Results processing and implementation of the method was carried out in the Java environment and the experimental results were compared with the square matrix and Hurtado-Noy method.
Sensor based cyber attack detections in critical infrastructures using deep learning algorithms
(Wydawnictwa AGH, 2019) Yilmaz, Murat; Catak, Ferhat Ozgur; Gul, Ensar
The technology that has evolved with innovations in the digital world has also caused an increase in many security problems. Day by day the methods and forms of the cyberattacks began to become complicated, and therefore their detection became more difficult. In this work we have used the datasets which have been prepared in collaboration with Raymond Borges and Oak Ridge National Laboratories. These datasets include measurements of the Industrial Control Systems related to chewing attack behavior. These measurements include synchronized measurements and data records from Snort and relays with the simulated control panel. In this study, we developed two models using this datasets. The first is the model we call the DNN Model which was build using the latest Deep Learning algorithms. The second model was created by adding the AutoEncoder structure to the DNN Model. All of the variables used when developing our models were set parametrically. A number of variables such as activation method, number of hidden layers in the model, the number of nodes in the layers, number of iterations were analyzed to create the optimum model design. When we run our model with optimum settings, we obtained better results than related studies. The learning speed of the model has 100\% accuracy rate which is also entirely satisfactory. While the training period of the dataset containing about 4 thousand different operations lasts about 90 seconds, the developed model completes the learning process at the level of milliseconds to detect new attacks. This increases the applicability of the model in real world environment.