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Featured researches published by Petr Velan.


Meeting of the European Network of Universities and Companies in Information and Communication Engineering | 2013

Design and Evaluation of HTTP Protocol Parsers for IPFIX Measurement

Petr Velan; Tomáš Jirsík; Pavel Čeleda

In this paper we analyze HTTP protocol parsers that provide a web traffic visibility to IP flow. Despite extensive work, flow meters generally fall short of performance goals due to extracting application layer data. Constructing effective protocol parser for in-depth analysis is a challenging and error-prone affair. We designed and evaluated several HTTP protocol parsers representing current state-of-the-art approaches used in today’s flow meters. We show the packet rates achieved by respective parsers, including the throughput decrease (performance implications of application parser) which is of the utmost importance for high-speed deployments. We believe that these results provide researchers and network operators with important insight into application visibility and IP flow.


availability, reliability and security | 2015

Security Monitoring of HTTP Traffic Using Extended Flows

Martin Husák; Petr Velan; Jan Vykopal

In this paper, we present an analysis of HTTP traffic in a large-scale environment which uses network flow monitoring extended by parsing HTTP requests. In contrast to previously published analyses, we were the first to classify patterns of HTTP traffic which are relevant to network security. We described three classes of HTTP traffic which contain brute-force password attacks, connections to proxies, HTTP scanners, and web crawlers. Using the classification, we were able to detect up to 16 previously undetectable brute-force password attacks and 19 HTTP scans per day in our campus network. The activity of proxy servers and web crawlers was also observed. Symptoms of these attacks may be detected by other methods based on traditional flow monitoring, but detection using the analysis of HTTP requests is more straightforward. We, thus, confirm the added value of extended flow monitoring in comparison to the traditional method.


autonomous infrastructure management and security | 2014

Next Generation Application-Aware Flow Monitoring

Petr Velan; Pavel Čeleda

Deep packet inspection (DPI) and IP flow monitoring are frequently used network monitoring approaches. Although the DPI provides application visibility, detailed examination of every packet is computationally intensive. The IP flow monitoring achieves high performance by processing only packet headers, but provides less details about the traffic itself. Application-aware flow monitoring is proposed as an attempt to combine DPI accuracy and IP flow monitoring performance. However, the impacts, benefits and disadvantages of application flow monitoring have not been studied in detail yet. The work proposed in this paper attempts to rectify this lack of research. We also propose a next generation flow measurement for application monitoring. The flows will represent events within the application protocol, e.g., web page download, instead of packet stream. Finally, we will investigate the performance of different approaches to application classification and application parsing with a computational complexity in mind.


network operations and management symposium | 2016

Network traffic characterisation using flow-based statistics

Petr Velan; Jana Medková; Tomáš Jirsík; Pavel Čeleda

Performing research on live network traffic requires the traffic to be well documented and described. The results of such research are heavily dependent on the particular network. This paper presents a study of network characteristics, which can be used to describe the behaviour of a network. We propose a number of characteristics that can be collected from the networks and evaluate them on five different networks of Masaryk University. The proposed characteristics cover IP, transport and application layers of the network traffic. Moreover, they reflect strong day-night and weekday patterns that are present in most of the networks. Variation in the characteristics between the networks indicates that they can be used for the description and differentiation of the networks. Furthermore, a weak correlation between the chosen characteristics implies their independence and contribution to network description.


Journal of Network and Systems Management | 2015

Report on the 8th International Conference on Autonomous Infrastructure, Management, and Security (AIMS 2014)

Anna Sperotto; Guillaume Doyen; Steven Latré; Marinos Charalambides; Jeroen Famaey; Petr Velan; Pavel Čeleda

AbstractThis article is a report of the IFIP AIMS 2014, which was held at Masaryk University, Czech Republic from June 30 to July 3, 2014. AIMS 2014 focused on the theme “Monitoring and Securing Virtualized Networks and Services”. The focus of the 2014 edition of the AIMS conference series was re-defined in comparison with earlier editions. AIMS 2014 positions itself in the network management community as an educational venue for Ph.D. students and young researchers. The AIMS program included hands-on tutorials and labs, a keynote, technical sessions and Ph.D. Workshop sessions, but also an educational session for training young academics on transversal topics. The highlights on each of the parts of the AIMS 2014 program are summarized in this article.


International Journal of Network Management | 2015

A survey of methods for encrypted traffic classification and analysis

Petr Velan; Milan Čermák; Pavel Čeleda; Martin Drašar


integrated network management | 2013

Large-scale geolocation for NetFlow

Pavel Čeleda; Petr Velan; Martin Rábek; Rick Hofstede; Aiko Pras


network operations and management symposium | 2018

Improving network flow definition: Formalization and applicability

Petr Velan


network operations and management symposium | 2018

Rapid prototyping of flow-based detection methods using complex event processing

Petr Velan; Martin Husák; Daniel Tovarnak


2018 Network Traffic Measurement and Analysis Conference (TMA) | 2018

Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets

Milan Čermák; Tomáš Jirsík; Petr Velan; Jana Komárková; Stanislav Spacek; Martin Drašar; Tomáš Plesník

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