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Memory Reduction of Stateful Network Traffic Processing
Hlaváček, Martin ; Puš, Viktor (referee) ; Kořenek, Jan (advisor)
This master thesis deals with the problems of memory reduction in the stateful network traffic processing. Its goal is to explore new possibilities of memory reduction during network processing. As an introduction this thesis provides motivation and reasons for need to search new method for the memory reduction. In the following part there are theoretical analyses of NetFlow technology and two basic methods which can in principle reduce memory demands of stateful processing. Later on, there is described the design and implementation of solution which contains the application of these two methods to NetFlow architecture. The final part of this work summarizes the main properties of this solution during interaction with real data.
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Optimization of network flow monitoring
Žádník, Martin ; Lhotka,, Ladislav (referee) ; Matoušek, Radomil (referee) ; Sekanina, Lukáš (advisor)
The thesis deals with optimization of network flow monitoring. Flow-based network traffic processing, that is, processing packets based on some state information associated to the flows which the packets belong to, is a key enabler for a variety of network services and applications. The number of simultaneous flows increases with the growing number of new services and applications. It has become a challenge to keep a state per each flow in a network device processing high speed traffic. A flow table, a structure with flow states, must be stored in a memory hierarchy. The memory closest to the processing is known as a flow cache. Flow cache management plays an important role in terms of its effective utilization, which affects the performance of the whole system. This thesis focuses on an automated design of cache replacement policy optimized to a deployment on particular networks. A genetic algorithm is proposed to automate this process. The genetic algorithm generates and evaluates evolved replacement policies by a simulation on obtained traffic traces. The proposed algorithm is evaluated by designing replacement policies for two variations of the cache management problem. The first variation is an evolution of the replacement policy with an overall low number of state evictions from the flow cache. The second variation represents an evolution of the replacement policy with a low number of evictions belonging to large flows only. Optimized replacement policies for both variations are found while experimenting with various encoding of the replacement policy and genetic operators. The newly evolved replacement policies achieve better results than other tested policies. The evolved replacement policy lowers the overall amount of evictions by ten percent in comparison with the best compared policy. The evolved replacement policy focusing on large flows lowers the amount of their evictions two times. Moreover, no eviction occurs for most of the large flows (over 90%). The evolved replacement policy offers better resilience against flooding the flow cache with large amount of short flows which are typical side effects of scanning or distributed denial of service activities. An extension of the replacement policy is also proposed. The extension complements the replacement policy with an additional information extracted from packet headers. The results show further decrease in the number of evictions when the extension is used.
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Profiling of Network Entities to Improve Situational Awareness
Bolf, René ; Tisovčík, Peter (referee) ; Žádník, Martin (advisor)
Having a good situational awareness is an important part of computer security. Knowing what is connected to the network, where it is located, and who is communicating can help make better and faster decisions when security incidents occur. This thesis is focusing on the profiling of network entities at the device level. More specifically, it focuses on the passive identification of operating systems. Every packet transferred in the network carries a specific information in its packet header that reflects the initial settings of a host's operating system. The set of these information is called the "fingerprint" of an operating system. In the thesis, there is described an implementation of a machine learning classifier using the decision tree method, which uses features from TCP and IP headers. The classifier was evaluated on a data set containing data from real network traffic and has achieved accuracy of 96 % when classifying into 9 classes of operating systems.
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Self Test of FlowMon Probe
Kříž, Blažej ; Kaštil, Jan (referee) ; Kořenek, Jan (advisor)
This thesis deals with development of built-in self-test for FlowMon probe, device for monitoring network traffic based on IP flows. At the begining, both NetFlow technology and the FlowMon probe are described and related terms are summarized. The development itself consists of requirements specification and analysis, design of general testing technique, desing of particular tests, their implementation and solution review.
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Software Architecture for Flow Based Monitoring Probe
Špringl, Petr ; Kořenek, Jan (referee) ; Martínek, Tomáš (advisor)
This thesis deals with design and implementation of software architecture for Flexible FlowMon probe, accessories for monitoring high speed computer networks based on IP flows. The probe has been developed in project named Liberouter. There is described flow based monitoring and export formats NetFlow version 5, NetFlow version 9 and IPIFX, which are very widely used. The thesis contains description of hardware part of Flexible FlowMon probe including its requirements for software, which are the base of the whole software architecture. There is detailed description of that part of software architecture which was implemented during the work on this thesis.
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Design of Methods for Encrypted Traffic Visualization
Hlučková, Pavla ; Martinásek, Zdeněk (referee) ; Malina, Lukáš (advisor)
This thesis deals with design of methods for encrypted traffic visualization. It generally describes selected encrypted traffic protocols, whose data samples were collected later on to form a dataset. Furthermore, it focuses on the topic of IP flow monitoring and decribes the means of carrying out such monitoring. An important part of this thesis is the dataset created from the samples of mentioned protocols and the visualizations of different statistics and metadata gatherable from (extended) IP flows of these protocols. The designed methods of visualization are implemented using the Python programming language and the Jupyter Notebook technology.
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Profiling of Network Entities to Improve Situational Awareness
Bolf, René ; Tisovčík, Peter (referee) ; Žádník, Martin (advisor)
Having a good situational awareness is an important part of computer security. Knowing what is connected to the network, where it is located, and who is communicating can help make better and faster decisions when security incidents occur. This thesis is focusing on the profiling of network entities at the device level. More specifically, it focuses on the passive identification of operating systems. Every packet transferred in the network carries a specific information in its packet header that reflects the initial settings of a host's operating system. The set of these information is called the "fingerprint" of an operating system. In the thesis, there is described an implementation of a machine learning classifier using the decision tree method, which uses features from TCP and IP headers. The classifier was evaluated on a data set containing data from real network traffic and has achieved accuracy of 96 % when classifying into 9 classes of operating systems.
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Design of Methods for Encrypted Traffic Visualization
Hlučková, Pavla ; Martinásek, Zdeněk (referee) ; Malina, Lukáš (advisor)
This thesis deals with design of methods for encrypted traffic visualization. It generally describes selected encrypted traffic protocols, whose data samples were collected later on to form a dataset. Furthermore, it focuses on the topic of IP flow monitoring and decribes the means of carrying out such monitoring. An important part of this thesis is the dataset created from the samples of mentioned protocols and the visualizations of different statistics and metadata gatherable from (extended) IP flows of these protocols. The designed methods of visualization are implemented using the Python programming language and the Jupyter Notebook technology.
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Optimization of network flow monitoring
Žádník, Martin ; Lhotka,, Ladislav (referee) ; Matoušek, Radomil (referee) ; Sekanina, Lukáš (advisor)
The thesis deals with optimization of network flow monitoring. Flow-based network traffic processing, that is, processing packets based on some state information associated to the flows which the packets belong to, is a key enabler for a variety of network services and applications. The number of simultaneous flows increases with the growing number of new services and applications. It has become a challenge to keep a state per each flow in a network device processing high speed traffic. A flow table, a structure with flow states, must be stored in a memory hierarchy. The memory closest to the processing is known as a flow cache. Flow cache management plays an important role in terms of its effective utilization, which affects the performance of the whole system. This thesis focuses on an automated design of cache replacement policy optimized to a deployment on particular networks. A genetic algorithm is proposed to automate this process. The genetic algorithm generates and evaluates evolved replacement policies by a simulation on obtained traffic traces. The proposed algorithm is evaluated by designing replacement policies for two variations of the cache management problem. The first variation is an evolution of the replacement policy with an overall low number of state evictions from the flow cache. The second variation represents an evolution of the replacement policy with a low number of evictions belonging to large flows only. Optimized replacement policies for both variations are found while experimenting with various encoding of the replacement policy and genetic operators. The newly evolved replacement policies achieve better results than other tested policies. The evolved replacement policy lowers the overall amount of evictions by ten percent in comparison with the best compared policy. The evolved replacement policy focusing on large flows lowers the amount of their evictions two times. Moreover, no eviction occurs for most of the large flows (over 90%). The evolved replacement policy offers better resilience against flooding the flow cache with large amount of short flows which are typical side effects of scanning or distributed denial of service activities. An extension of the replacement policy is also proposed. The extension complements the replacement policy with an additional information extracted from packet headers. The results show further decrease in the number of evictions when the extension is used.
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Self Test of FlowMon Probe
Kříž, Blažej ; Kaštil, Jan (referee) ; Kořenek, Jan (advisor)
This thesis deals with development of built-in self-test for FlowMon probe, device for monitoring network traffic based on IP flows. At the begining, both NetFlow technology and the FlowMon probe are described and related terms are summarized. The development itself consists of requirements specification and analysis, design of general testing technique, desing of particular tests, their implementation and solution review.
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