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Integration of advanced artificial intelligence methods with log management security systems
Sedláček, Jiří ; Mikulec, Marek (referee) ; Safonov, Yehor (advisor)
Cyber security is a very important aspect of everyone’s daily life. With the ever-expanding cyberspace and its growing influence on the real world, the issue of cyber security is all the more important. The theoretical part of the thesis describes the basic aspects of security monitoring. Also, the process of collecting event logs and their management is briefly described. An important means of security monitoring is the management of security information and events. Its advantages, disadvantages and possible improvements with artificial intelligence are discussed. Security orchestration, automation and response functions are also mentioned in the theoretical part. Machine learning techniques such as neural networks and deep learning are also mentioned. This section also focuses on cyber operations centres in terms of improving the efficiency of human ”manual” labour. A survey of possible machine learning techniques for this use case has been conducted, as the lack of human resources is a critical issue within security operations centres. The practical part of the thesis involves setting out a goal (text sequence classification) that could make the work considerably easier in terms of manually categorizing event logs according to their source. For this set task, security monitoring related data was collected from different log sources. In the practical part, the methods for processing this data are also described in detail. Subsequently, a suitable neural network model was selected and its technical description was performed. Finally, the final data processing and the process of training, validating and testing the model are described. Three scenarios were developed for this process, which are then described in detail in the measurement results.
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Integration of advanced artificial intelligence methods with log management security systems
Sedláček, Jiří ; Mikulec, Marek (referee) ; Safonov, Yehor (advisor)
Cyber security is a very important aspect of everyone’s daily life. With the ever-expanding cyberspace and its growing influence on the real world, the issue of cyber security is all the more important. The theoretical part of the thesis describes the basic aspects of security monitoring. Also, the process of collecting event logs and their management is briefly described. An important means of security monitoring is the management of security information and events. Its advantages, disadvantages and possible improvements with artificial intelligence are discussed. Security orchestration, automation and response functions are also mentioned in the theoretical part. Machine learning techniques such as neural networks and deep learning are also mentioned. This section also focuses on cyber operations centres in terms of improving the efficiency of human ”manual” labour. A survey of possible machine learning techniques for this use case has been conducted, as the lack of human resources is a critical issue within security operations centres. The practical part of the thesis involves setting out a goal (text sequence classification) that could make the work considerably easier in terms of manually categorizing event logs according to their source. For this set task, security monitoring related data was collected from different log sources. In the practical part, the methods for processing this data are also described in detail. Subsequently, a suitable neural network model was selected and its technical description was performed. Finally, the final data processing and the process of training, validating and testing the model are described. Three scenarios were developed for this process, which are then described in detail in the measurement results.
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Utilization of SIEM systems for network events monitoring
Kopřiva, Milan ; Čermák, Igor (advisor) ; Habáň, Přemysl (referee)
In the last years we can observe an increasing number of security incidents varying in their focus, motives and success rate. Attacks are often conducted by very skilled organized groups with high knowledge base and they are increasing in their sophistication and efficiency. Because of those reasons information security is now one of the main fields of interest of IT experts. This thesis deals with Security information and Event Management technology and its usage for the detection of potentially harmful activity in a company's internal network. In the first chapter the elementary concepts of security are placed into the context of this thesis. Next chapter deals with security information and event management technology itself, its clear definition and describing the main functionality. The end of the theoretical part is dedicated to the author's view of the future and also to the problems concerning the implementation of SIEM solutions including return on investment calculation which has certain specifics in security field. Main benefit coming from this thesis is a clear description and creation of use cases aimed at the detecting suspicious activity in internal computer networks combined with their deployment in SIEM solution in real environment. The practical part of this thesis is dedicated to the configuration of the chosen device and its connection to the SIEM solution, and the assessment of usability of security events generated by the threat detecting device. Based on this assessment the use cases will be modelled and then deployed in the test environment. This thesis aims to bring on overall view into the security information and event management technology, starting with its definition and base functions. The primary goal of this thesis is use case designing for real time threat detection in a practical environment.
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Company network security monitoring
Kališ, Martin ; Pavlíček, Luboš (advisor) ; Matuška, Miroslav (referee)
Main focus of this work is on computer network security monitoring. In first part basic definitions for the area are formed and it also offers different ways to encompass monitoring into company security. Next part defines main functions of monitoring systems and provides guidelines for its implementation in organization. Practical part consists of defining key conditions for selection of monitoring solution and it also applies them when comparing several products available on the market. Then it presents author's view on future trends and development in this area based on facts from previous chapters. Whole work provides complete approach to security monitoring and offers definition of all key concepts and competencies for monitoring systems.
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