GiViP: A Visual Profiler for Distributed Graph Processing Systems

Analyzing large-scale graphs provides valuable insights in different application scenarios. While many graph processing systems working on top of distributed infrastructures have been proposed to deal with big graphs, the tasks of profiling and debugging their massive computations remain time consuming and error-prone. This paper presents GiViP, a visual profiler for distributed graph processing systems based on a Pregel-like computation model. GiViP captures the huge amount of messages exchanged throughout a computation and provides an interactive user interface for the visual analysis of the collected data. We show how to take advantage of GiViP to detect anomalies related to the computation and to the infrastructure, such as slow computing units and anomalous message patterns.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Cascade feed forward neural network-based model for air pollutants evaluation of single monitoring stations in urban areas

In this paper, air pollutants concentrations for N O2 , N O, N Ox and P M 10 in a single monitoring station are predicted using the data coming from other different monitoring stations located nearby. A cascade feed forward neural network based modeling is proposed. The main aim is to provide a methodology leading to the introduction of virtual monitoring station points consistent with the actual stations located in the city of Catania in Italy.

Introduction on intrusion detection systems : focus on hierarchical analysis

In today\u27s fast paced computing world security is a main concern. Intrusion detection systems are an important component of defensive measures protecting computer systems and networks from abuse. This paper will examine various intrusion detection systems. The task of intrusion detection is to monitor usage of a system and detect and malicious activity, therefore, the architecture is a key component when studying intrusion detection systems. This thesis will also analyze various neural networks for statistical anomaly intrusion detection systems. The thesis will focus on the Hierarchical Intrusion Detection system (HIDE) architecture. The HIDE system detects network based attack as anomalies using statistical preprocessing and neural network classification. The thesis will conclude with studies conducted on the HIDE architecture. The studies conducted on the HIDE architecture indicate how the hierarchical multi-tier anomaly intrusion detection system is an effective one

BUDOWA SYSTEMÓW WYKRYWANIA ATAKÓW NA PODSTAWIE METOD INTELIGENTNEJ ANALIZY DANYCH

Nowadays, with the rapid development of network technologies and with global informatization of society problems come to the fore ensuring a high level of information system security. With the increase in the number of computer security incidents, intrusion detection systems (IDS) started to be developed rapidly.Nowadays the intrusion detection systems usually represent software or hardware-software solutions, that automate the event control process, occurring in an information system or network, as well as independently analyze these events in search of signs of security problems. A modern approach to building intrusion detection systems is full of flaws and vulnerabilities, which allows, unfortunately, harmful influences successfully overcome information security systems. The application of methods for analyzing data makes it possible identification of previously unknown, non-trivial, practically useful and accessible interpretations of knowledge necessary for making decisions in various spheres of human activity. The combination of these methods along with an integrated decision support system makes it possible to build an effective system for detecting and counteracting attacks, which is confirmed by the results of imitation modeling.W chwili obecnej szybki rozwój technologii sieciowych i globalnej informatyzacji społeczeństwa uwypukla problemy związane z zapewnieniem wysokiego poziomu bezpieczeństwa systemów informacyjnych. Wraz ze wzrostem liczby incydentów komputerowych związanych z bezpieczeństwem nastąpił dynamiczny rozwój systemów wykrywania ataków. Obecnie systemy wykrywania włamań i ataków to zazwyczaj oprogramowanie lub sprzętowo-programowe rozwiązania automatyzujące proces monitorowania zdarzeń występujących w systemie informatycznym lub sieci, a także samodzielnie analizujące te zdarzenia w poszukiwaniu oznak problemów bezpieczeństwa. Nowoczesne podejście do budowy systemów wykrywania ataków na systemy informacyjne jest pełne wad i słabych punktów, które niestety pozwalają szkodliwym wpływom na skuteczne pokonanie systemów zabezpieczania informacji. Zastosowanie metod inteligentnej analizy danych pozwala wykryć w danych nieznane wcześniej, nietrywialne, praktycznie użyteczne i dostępne interpretacje wiedzy niezbędnej do podejmowania decyzji w różnych sferach ludzkiej działalności. Połączenie tych metod wraz ze zintegrowanym systemem wspomagania decyzji umożliwia zbudowanie skutecznego systemu wykrywania i przeciwdziałania atakom, co potwierdzają wyniki modelowania

Operation of EMEP ‘supersites’ in the United Kingdom. Annual report for 2008.

As part of its commitment to the UN-ECE Convention on Long-range Transboundary Air Pollution the United Kingdom operates two ‘supersites’ reporting data to the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP). This report provides the annual summary for 2008, the second full calendar year of operation of the first EMEP ‘supersite’ to be established in the United Kingdom. Detailed operational reports have been submitted to Defra every 3 months, with unratified data. This annual report contains a summary of the ratified data for 2008. The EMEP ‘supersite’ is located in central southern Scotland at Auchencorth (3.2oW, 55.8oN), a remote rural moorland site ~20 km south-west of Edinburgh. Monitoring operations started formally on 1 June 2006. In addition to measurements made specifically under this contract, the Centre for Ecology & Hydrology also acts as local site operator for measurements made under other UK monitoring networks: the Automated Urban and Rural Network (AURN), the UK Eutrophication and Acidification Network (UKEAP), the UK Hydrocarbons Network, and the UK Heavy Metals Rural Network. Some measurements were also made under the auspices of the ‘Air Pollution Deposition Processes’ contract. All these associated networks are funded by Defra. This report summarises the measurements made between January and December 2008, and presents summary statistics on average concentrations. The site is dominated by winds from the south-west, but wind direction data highlight potential sources of airborne pollutants (power stations, conurbations). The average diurnal patterns of gases and particles are consistent with those expected for a remote rural site. The frequency distributions are presented for data where there was good data capture throughout the whole period. Some components (e.g. black carbon) show log-normal frequency distributions, while other components (e.g. ozone) have more nearly normal frequency distributions. A case study is presented for a period in June 2008, showing the influence of regional air pollutants at this remote rural site. All the data reported under the contract are shown graphically in the Appendix

Machine Learning based Traffic Classification using Statistical Analysis

In this paper, Automated system is built which contains processing of captured packets from the network. Machine learning algorithms are used to build a traffic classifier which will classify the packets as malicious or non-malicious. Previously, many traditional ways were used to classify the network packets using tools, but this approach contains machine learning approach, which is an open field to explore and has provided outstanding results till now. The main aim is to perform traffic monitoring, analyze it and govern the intruders. The CTU-13 is a dataset of botnet traffic which is used to develop traffic classification system based on the features of the captured packets on the network. This type of classification will assist the IT administrators to determine the unknown attacks which are broadening in the IT industry

Top-down cracking in Italian motorway pavements: A case study

none4noTop-down cracking (TDC) is a distress affecting asphalt pavements and consists of longitudinal cracks that initiate on the pavement surface and propagate downwards. In general, TDC is more critical in the case of thick pavements with open-graded friction course (OGFC), which are the typical characteristics of Italian motorway pavements. Recent surveys showed the presence of many longitudinal cracks potentially ascribable to TDC on Italian motorways. Within this context, this study has two main objectives: 1) to define reliable identification criteria allowing to distinguish between TDC and the other types of longitudinal cracks observed and 2) based on the developed criteria, to quantify TDC in Italian motorway pavements. In this regard, a 200 km long trial network (400 km considering both directions) was studied, taking into account the effect of several variables (e.g. geometric characteristics, traffic level, wearing layer type and climate). For this purpose, images of the trial network acquired during pavement monitoring were visually analysed and some control cores were taken. Specific criteria (which can be used in a pavement management system, PMS) were developed to distinguish between the main types of longitudinal cracks observed on the trial network, i.e. TDC, cracks due to heavy vehicles tire blowout and construction joints, based on their geometric features on the pavement surface. It was found that TDC can affect up to 20–30 % of the slow traffic lane. Specifically, the highest TDC concentrations were observed for high traffic levels and OGFC, whereas TDC was absent in the case of a dense-graded wearing layer. Finally, surprisingly the concentration of tire blowout cracks was even higher than TDC. This study provides evidence on the fact that, for thick pavements with OGFC, TDC has to be considered a priority problem to be addressed in both pavement design and maintenance.openIngrassia L.P.; Spinelli P.; Paoloni G.; Canestrari F.Ingrassia, L. P.; Spinelli, P.; Paoloni, G.; Canestrari, F

Top-down cracking in Italian motorway pavements: A case study

Abstract Top-down cracking (TDC) is a distress affecting asphalt pavements and consists of longitudinal cracks that initiate on the pavement surface and propagate downwards. In general, TDC is more critical in the case of thick pavements with open-graded friction course (OGFC), which are the typical characteristics of Italian motorway pavements. Recent surveys showed the presence of many longitudinal cracks potentially ascribable to TDC on Italian motorways. Within this context, this study has two main objectives: 1) to define reliable identification criteria allowing to distinguish between TDC and the other types of longitudinal cracks observed and 2) based on the developed criteria, to quantify TDC in Italian motorway pavements. In this regard, a 200 km long trial network (400 km considering both directions) was studied, taking into account the effect of several variables (e.g. geometric characteristics, traffic level, wearing layer type and climate). For this purpose, images of the trial network acquired during pavement monitoring were visually analysed and some control cores were taken. Specific criteria (which can be used in a pavement management system, PMS) were developed to distinguish between the main types of longitudinal cracks observed on the trial network, i.e. TDC, cracks due to heavy vehicles tire blowout and construction joints, based on their geometric features on the pavement surface. It was found that TDC can affect up to 20–30 % of the slow traffic lane. Specifically, the highest TDC concentrations were observed for high traffic levels and OGFC, whereas TDC was absent in the case of a dense-graded wearing layer. Finally, surprisingly the concentration of tire blowout cracks was even higher than TDC. This study provides evidence on the fact that, for thick pavements with OGFC, TDC has to be considered a priority problem to be addressed in both pavement design and maintenance