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Enhancing Security Monitoring with AI-Enabled Log Collection and NLP Modules on a Unified Open Source Platform
Safonov, Yehor ; Zernovic, Michal
The number of computer attacks continues to increasedaily, posing significant challenges to modern securityadministrators to provide security in their organizations. Withthe rise of sophisticated cyber threats, it is becoming increasinglydifficult to detect and prevent attacks using traditional securitymeasures. As a result, security monitoring solutions such asSecurity Information and Event Management (SIEM) have becomea critical component of modern security infrastructures. However,these solutions still face limitations, and administrators areconstantly seeking ways to enhance their capabilities to effectivelyprotect their cyber units. This paper explores how advanced deeplearning techniques can help boost security monitoring capabilitiesby utilizing them throughout all stages of log processing. Thepresented platform has the potential to fundamentally transformand bring about a significant change in the field of securitymonitoring with advanced AI capabilities. The study includes adetailed comparison of modern log collection platforms, with thegoal of determining the most effective approach. The key benefitsof the proposed solution are its scalability and multipurposenature. The platform integrates an open source solution andallows the organization to connect any event log sources or theentire SIEM solution, normalize and filter data, and use thisdata to train and deploy different AI models to perform differentsecurity monitoring tasks more efficiently.
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Application for collecting security event logs from computer infrastructure
Žernovič, Michal ; Dobiáš, Patrik (referee) ; Safonov, Yehor (advisor)
Computer infrastructure runs the world today, so it is necessary to ensure its security, and to prevent or detect cyber attacks. One of the key security activities is the collection and analysis of logs generated across the network. The goal of this bachelor thesis was to create an interface that can connect a neural network to itself to apply deep learning techniques. Embedding artificial intelligence into the logging process brings many benefits, such as log correlation, anonymization of logs to protect sensitive data, or log filtering for optimization a SIEM solution license. The main contribution is the creation of a platform that allows the neural network to enrich the logging process and thus increase the overall security of the network. The interface acts as an intermediary step to allow the neural network to receive logs. In the theoretical part, the thesis describes log files, their most common formats, standards and protocols, and the processing of log files. It also focuses on the working principles of SIEM platforms and an overview of current solutions. It further describes neural networks, especially those designed for natural language processing. In the practical part, the thesis explores possible solution paths and describes their advantages and disadvantages. It also analyzes popular log collectors (Fluentd, Logstash, NXLog) from aspects such as system load, configuration method, supported operating systems, or supported input log formats. Based on the analysis of the solutions and log collectors, an approach to application development was chosen. The interface was created based on the concept of a REST API that works in multiple modes. After receiving the records from the log collector, the application allows saving and sorting the records by origin and offers the user the possibility to specify the number of records that will be saved to the file. The collected logs can be used to train the neural network. In another mode, the interface forwards the logs directly to the AI model. The ingestion and prediction of the neural network are done using threads. The interface has been connected to five sources in an experimental network.
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Mikrotik RouterOS Module for IBM QRadar
Sysel, Václav ; Polčák, Libor (referee) ; Hranický, Radek (advisor)
The goal of this work is to design and implement an extension for the IBM QRadar system. It is a security system that detects cyber attacks by collecting information from the computer network. The purpose of the extension is to enable the collection, processing and visualization of information from MikroTik RouterOS operating system. The designed software provides administrators of networks with MikroTik elements with a better awareness of what is happening in the protected network and a comprehensive overview of the security situation.
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Suricata Module for IBM QRadar
Kozák, Martin ; Žádník, Martin (referee) ; Hranický, Radek (advisor)
This work integrates the Suricata program into the QRadar system. The main objective of this work is to design and implement a DSM module in QRadar system that can analyze the records from Suricata. The events can then be investigated in the QRadar system environment. Another objective is to design an application that displays the data detected by the Suricata program. The application can be installed in the QRadar environment and used with other built-in components. The application is programmed in the Flask library using Jinja2 templates. The application includes two tabs that display events in different graphs and table.
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Tool for mapping computer infrastructure assets and designing SIEM correlation rules for security monitoring
Hrabálek, Matěj ; Caha, Tomáš (referee) ; Safonov, Yehor (advisor)
With the growing popularity of the SOC service, which often uses SIEM tools, new challenges arise regarding the implementation of these tools into individual infrastructures that can face cyber attacks. SIEM tools can detect cyber attacks only if they are configured correctly, i.e. they collect the right logs. This bachelor’s thesis is used for the facilitation of the process of implementing SIEM into the internal infrastructure. They discuss the appropriate categorization of log sources and correlation rules, the naming of correlation rules, and a system for mapping log sources to relevant correlation rules is proposed, which facilitates the implementation of SIEM into the infrastructure. All knowledge is then implemented into a web application, which is the practical output of this bachelor’s thesis. The web application allows the user, who is going to implement a SIEM service into their own infrastructure, to enter data about the infrastructure, especially log sources that can be generated in the infrastructure, and offers suitable correlation rules, including their naming, to the respective log sources. In addition to logs, SIEM technology and correlation rules, the theoretical part also discusses general knowledge from cyber security and describes the Security Operations Center.
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Web application for development and maintenance of SIEM system correlation rules
Bielik, Oliver ; Mikulec, Marek (referee) ; Safonov, Yehor (advisor)
Today’s world of technology is developing rapidly and constantly. Just as quickly, new risks are forming that threaten this sphere. For this reason, technologies need to be monitored and hazards prevented from entering systems. One of the technologies that helps this protection is a system called SIEM. This system serves as an investigative tool that allows security monitoring and investigations to be carried out. Security monitoring is carried out based on the correlation rules that are developed in security operations centers (SOC). Their task is to look for the potential dangers and report them. The main goal of the presented bachelor thesis is to create a tool that allows developers in SOC to easily develop correlation rules. The aim of the application is to simplify development and ensure a better overview of individual correlation rules. The theoretical part of the bachelor thesis focuses on the issue of security monitoring and explains it to the reader. It describes in more detail the functioning of the system and the work of SOC operators, whose job is the development of correlation rules as well. The practical part of the bachelor thesis is aimed at facilitating the development of these rules. The last part of the bachelor thesis is a conclusion, it briefly describes to the reader the observed facts and processing of the requirements for the bachelor thesis.
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Návrh dílčí části systému pro monitoring bezpečnostních incidentů
Koch, Michael ; Neuwirth, Bernard (referee) ; Novák, Lukáš (advisor)
The thesis focuses on the implementation of a part of the information system for security incident analysis within PwC. The system serves to complement the current solution, which lags behind future and existing requirements. The first part describes the theoretical background to understand the concept of the thesis and the technologies used in the implementation of the system. The following section contains an analysis of the current state of the existing system. The principle on which it works and the shortcomings that caused the necessity to implement a new solution. The third chapter deals with the actual design and implementation of the new solution. In the last part of the thesis an economic evaluation of the costs and benefits of the solution is made.
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Security log anonymization tool focusing on artificial intelligence techniques
Šťastná, Ariela ; Jurek, Michael (referee) ; Safonov, Yehor (advisor)
Systémy SIEM zohrávajú v rámci bezpečnostného monitoringu zásadnú úlohu. Zozbierané záznamy agregujú, normalizujú a filtrujú, čo predstavuje základ pre aplikovanie techník dolovania dát. Týmto spôsobom SIEMy prezentujú výborný zdroj veľkých objemov normalizovaných dát. Tieto dáta nesú potenciál pre dosiahnutie pokroku v bezpečnostnom výskume, dolovaní dát a umelej inteligencii, kde môžu viesť k zlepšeniu existujúcich metód prieskumu, sprehľadneniu skenovania siete a odhaleniu sofistikovanejších vektorov útoku. Avšak jedným z hlavných problémov pre využívanie týchto dát je skutočnosť, že dáta v logových záznamoch sú v mnohých prípadoch citlivé a môžu predstavovať riziko z hľadiska bezpečnosti. Z toho dôvodu bol vytvorený nástroj pre anonymizáciu citlivých údajov v logových záznamoch, ktorý zachováva korelácie medzi dátami. Hlavným cieľom bakalárskej práce je zamerať sa na technické a právne aspekty spracovania logov a anonymizáciu pre umelú inteligenciu. V rámci výskumu bola vykonaná analýza najčastejšie sa vyskytujúcich dát v logoch spolu s vyhodnotením ich rizikovosti, výsledkom čoho je vytvorenie kategórií dát vzhľadom na ich citlivosť. V práci je ďalej prezentovaná analýza súčasných SIEM systémov spolu s meta kľúčmi, ktoré využívajú.
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Web application for generalizing SIEM correlation rules
Matušicová, Viktória ; Mikulec, Marek (referee) ; Safonov, Yehor (advisor)
The risk of attacks on companies by organized crime increases as technology advances. Attacks that focus on modifying data or gaining access to a company's network are constantly developed. The sophisticated nature of advanced threats distinguishes them from broad-based attacks that rely on automated scripts. However, organizations can mitigate this risk by utilizing a combination of appropriate tools. These include network flow monitoring, probes for detecting and preventing attacks, and Security Information and Event Management (SIEM) tools for correlating incidents and events. By leveraging these tools, suspicious behavior in the network can be identified, and measures can be taken to prevent and mitigate the impact of cyber attacks. The main contribution of this thesis is the development of a web application that serves as a general tool for managing correlation rules across various SIEM solutions. Through the use of this web application, publicly available Sigma rules can be managed and converted into target SIEM solutions. Users are given the ability to save these rules to their personal user section, alongside SIEM conversions and visual representations of technique coverage based on categorization by MITRE ATT@CK and LogSource of stored user rules. The theoretical part of the thesis comprises an analysis of security monitoring issues, an explanation of the benefits of the Sigma platform and an analysis of the web application. A use case model is defined, functional and non-functional requirements are specified to describe the resulting system. Additionally, the analysis of available tools for converting Sigma rules is performed. The practical portion of the thesis begins with a focus on the design of the web application, including the architecture of both the server-side and client-side components, as well as an explanation of the core functionalities. The resulting solution is then implemented, with detailed procedures for creating microservices, client-side development, and launching the web application. The final state of the project summarizes the result. The thesis concludes with a testing phase, the client side of the web application is evaluated through functional user interface screenshots. The thesis also includes a demonstration of the process for testing Sigma rules, which involves converting the rules using the web application and subsequently carrying out functional verification using the RSA NetWitness SIEM test solution.
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