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Application of the Complex Event Processing system for anomaly detection and network monitoring

Frankowski G., Jerzak M., Miłostan M., Nowak T., Pawłowski M.

Computer Science

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2015

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Vol. 16 (4)

351--371

EN

Protection of infrastructures for e-science, including grid environments and NREN facilities, requires the use of novel techniques for anomaly detection and network monitoring. The aim is to raise situational awareness and provide early warning capabilities. The main operational problem that most network operators face is integrating and processing data from multiple sensors and systems placed at critical points of the infrastructure. From a scientific point of view, there is a need for the efficient analysis of large data volumes and automatic reasoning while minimizing detection errors. In this article, we describe two approaches to Complex Event Processing used for network monitoring and anomaly detection and introduce the ongoing SECOR project (Sensor Data Correlation Engine for Attack Detection and Support of Decision Process), supported by examples and test results. The aim is to develop methodology that allows for the construction of next-generation IDS systems with artificial intelligence, capable of performing signature-less intrusion detection.

2

Flexibility of Dicer Studied by Implicit Solvent Molecular Dynamics Simulations

Sarzyńska J., Mickiewicz A., Miłostan M., Łukasiak P., Błażewicz J., Figlerowicz M., Kuliński T.

Computational Methods in Science and Technology

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2010

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Vol. 16, No. 1

97-104

EN

Dicer is an enzyme responsible for processing double-stranded RNAs and plays a key role in an RNAi mechanism. Structural insight into the Dicer is provided by the crystal structure of eukaryotic Dicer from Giardia intestinalis. It has been proposed that the structure has three structurally rigid regions that are connected by the flexible hinges. Flexibility of the Dicer is believed to be a critical feature for its function. Spatial arrangement of the RNA-recognition and the catalytic regions is crucial for producing small RNAs of defined length. It has been suggested that in the Giardia Dicer a Platform domain may help in specific arrangement of these regions. To learn more about the role of the Platform domain in Giardia Dicer, we have performed molecular dynamics (MD) simulations of the whole Dicer (WT Dicer) and the Dicer with a deleted platform domain (delta Plf Dicer). The MD simulations were carried out in an implicit solvent model with two implementations of analytic Generalized Born (GB) solvation model in CHARMM: GBMV (Generalized Born using Molecular Volume) and GBSW (Generalized Born with simple Switching). To detect the key global motions of the Dicer, a principal component analysis (PCA) of the obtained MD trajectories has been used. To further explore the motion of the Dicer, we performed a domain motion analysis with the DYNDOM program. The simulations show that both WT Dicer and delta Plf Dicer display flexibility which can be described as a movement of two or three domains. The removal of the Platform substantially changed the flexibility and arrangement of these domains. During the MD simulations of delta Plf Dicer an large movement of the RNA-recognition domain was observed.

3

3D-Judge : a metaserver approach to protein structure prediction

Jaśkowski W., Błażewicz J., Łukasiak P., Miłostan M., Krasnogor N.

Foundations of Computing and Decision Sciences

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2007

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Vol. 32, No. 1

3-14

EN

Analysing arid predicting the detailed three dimensional conformation of protein structures is a critical and important task within structural bioinformatics with impact on other fields, e.g.. drug design and delivery, sensing technologies, etc. Unfortunately, it is hard to identify one methodology that will give the best prediction of the three-dimensional structure for any sequence. That is, some predictors are best suited for some sequences and not for others. In trying to address this drawback of current prediction algorithms the research community introduced the concept of protein prediction metaservers. In this paper we propose a new metaserver method called 3D-Judge that uses an artificial neural network (ANN) to select the best model from among models produced by individual servers. The fundamental innovation we introduce is that the AXN is not only used to decide which models and servers to use as good predictions but, crucially, it is also used to analyse and "remember" the past performances of the servers it has access to. Thus, our method acts as both a kind of majority voting algorithm, by selecting models arising from different servers based on their mutual similarity, and also a reinforced learning method that takes cues from historical data of previously solved structures. We train and evaluate our metaserver based on previous GASP results and we compare SD-Judge with a popular and effective metaserver, namely. 3D-Jury. The obtained results indicate that 3D-Judge is competitive with 3D-Jury, outperforming it on many cases. We also present a discussion on future extensions to 3D-Judge.

4

A tabu search strategy for finding low energy structures of proteins in HP - model

Błażewicz J., Łukasiak P., Miłostan M., Dill K.

Computational Methods in Science and Technology

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2004

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Vol. 10, nr 1

7-19

EN

HP-model is one of the most successful and well-studied simplified lattice models of protein folding. It uses mathematical abstraction of proteins for hiding many aspects of the folding process and works as hypothesis generator. Due to the NP-hardness results of the protein folding problem many approximation algorithms, have been used to solve it. In the paper, the method for finding low energy conformations of proteins, based on the tabu search strategy, has been proposed. The algorithm has been extensively tested and the tests showed its very good performance.