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Finding lost persons, collecting information in disturbed communities, efficiently traversing urban areas after a blast or similar catastrophic events have motivated researchers to develop intelligent sensor frameworks to aid law enforcement, first responders, and military personnel with situational awareness. This dissertation consists of a two-part framework for providing situational awareness using both acoustic ground sensors and aerial sensing modalities. Ground sensors in the field of data-driven detection and classification approaches typically rely on computationally expensive inputs such as image or video-based methods [6, 91]. However, the information given by an acoustic signal offers several advantages, such as low computational needs and possible classification of occluded events including gunshots or explosions. Once an event is identified, responding to real-time events in urban areas is difficult using an Unmanned Aerial Vehicle (UAV) especially when GPS is unreliable due to coverage blackouts and/or GPS degradation [10]. Furthermore, if it is possible to deploy multiple in-situ static intelligent acoustic autonomous sensors that can identify anomalous sounds given context, then the sensors can communicate with an autonomous UAV that can navigate in a GPS-denied urban environment for investigation of the event; this could offer several advantages for time-critical and precise, localized response information necessary for life-saving decision-making. Thus, in order to implement a complete intelligent sensor framework, the need for both an intelligent static ground acoustic autonomous unattended sensors (AAUS) and improvements to GPS-degraded localization has become apparent for applications such as anomaly detection, public safety, as well as intelligence surveillance and reconnaissance (ISR) operations. Distributed AAUS networks could provide end-users with near real-time actionable information for large urban environments with limited resources. Com

Understanding the behavior of pedestrians in road transportation is critical to maintain a safe en- vironment. Accidents on road transportation are one of the most common causes of death today. As autonomous vehicles start to become a standard in our society, safety on road transportation becomes increasingly important. Road transportation is a complex system with a lot of dierent factors. Identifying risky behaviors and preventing accidents from occurring requires better under- standing of the behaviors of the dierent persons involved. In this thesis the activities and behavior of a pedestrian is analyzed. Using sensor data from phones, eight dierent events of a pedestrian are classied using machine learning algorithms. Features extracted from phone sensors that can be used to model dierent pedestrian activities are identied. Current state of the art literature is researched to nd relevant machine learning algorithms for a classication model. Two models are implemented using two dierent machine learning algorithms: Articial Neural Network and Hid- den Markov Model. Two dierent experiments are conducted where phone sensor data is collected and classied using the models, achieving a classication accuracy of up to 93%.

Understanding the behavior of pedestrians in road transportation is critical to maintain a safe en- vironment. Accidents on road transportation are one of the most common causes of death today. As autonomous vehicles start to become a standard in our society, safety on road transportation becomes increasingly important. Road transportation is a complex system with a lot of dierent factors. Identifying risky behaviors and preventing accidents from occurring requires better under- standing of the behaviors of the dierent persons involved. In this thesis the activities and behavior of a pedestrian is analyzed. Using sensor data from phones, eight dierent events of a pedestrian are classied using machine learning algorithms. Features extracted from phone sensors that can be used to model dierent pedestrian activities are identied. Current state of the art literature is researched to nd relevant machine learning algorithms for a classication model. Two models are implemented using two dierent machine learning algorithms: Articial Neural Network and Hid- den Markov Model. Two dierent experiments are conducted where phone sensor data is collected and classied using the models, achieving a classication accuracy of up to 93%.

Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method.

Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method.

Developing an appropriate user interface architecture for supporting a system's tasks is critical to the system's overall usability. While there are principles to guide architectural design, confirming that the correct decisions are made can involve the collection and analysis of lots of test data. We are developing a testing environment that will automatically compare and contrast the actual user interaction data against the existing user interface architectural models. This can help a designer more clearly understand how the actual tasks performed relate to the proposed architecture, and enhances feedback between different design artifacts.

Developing an appropriate user interface architecture for supporting a system's tasks is critical to the system's overall usability. While there are principles to guide architectural design, confirming that the correct decisions are made can involve the collection and analysis of lots of test data. We are developing a testing environment that will automatically compare and contrast the actual user interaction data against the existing user interface architectural models. This can help a designer more clearly understand how the actual tasks performed relate to the proposed architecture, and enhances feedback between different design artifacts.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

Event monitoring has been employed in many applications such as network monitoring, active databases etc.; however, there is only an insignificant amount work done on parameterized event monitoring, a feature that is necessary in any real application. The aim of this work is to investigate solutions for parameterized event composition that is scalable and efficient; these solutions are refined from existing event monitoring algorithms. An algorithm for parameterized event composition is proposed and analysis on algorithmic time complexity is performed. In addition to this, experiments on the prototype Solicitor, a software component in DeeDS, along with simulated input of events are conducted in order to validate the theoretical model and the hypothesis that were made. The experiments support the theoretical model and suggest that it is possible to build an efficient and scalable parameterized event composition that is useful in real applications.

To gain confidence in that a dynamic real-time system behaves correctly, we test it. Automated verification & validation can be used to conduct testing of such systems in an effective and economic way. An event monitor can be used as a part of a test oracle to monitor the system that is being tested. The test oracle could use the data (i.e., the streams of events) derived from the tested system, to determine if an executed test case gave a positive or negative result. To do this, the test oracle compares the streams of events received from the event monitor with the event expressions derived from the formal specification, and decides if the executed test case has responded positive or negative. Any deviations between observed behaviour and accepted behaviour should be reported by the test oracle as a negative result. If the executed test case gave a negative result, the monitor part should signal this to the reporter part of the test oracle. This work aims to investigate how the event expressions can be derived from the formal specification, and in particular, how the event specification language Solicitor can be used to represent these event expressions. We also discuss the need for parameterized event types in Solicitor, and any other event specification languages used in event monitoring. We also show that support for parameterized event types is a significant requirement for such languages.

To gain confidence in that a dynamic real-time system behaves correctly, we test it. Automated verification & validation can be used to conduct testing of such systems in an effective and economic way. An event monitor can be used as a part of a test oracle to monitor the system that is being tested. The test oracle could use the data (i.e., the streams of events) derived from the tested system, to determine if an executed test case gave a positive or negative result. To do this, the test oracle compares the streams of events received from the event monitor with the event expressions derived from the formal specification, and decides if the executed test case has responded positive or negative. Any deviations between observed behaviour and accepted behaviour should be reported by the test oracle as a negative result. If the executed test case gave a negative result, the monitor part should signal this to the reporter part of the test oracle. This work aims to investigate how the event expressions can be derived from the formal specification, and in particular, how the event specification language Solicitor can be used to represent these event expressions. We also discuss the need for parameterized event types in Solicitor, and any other event specification languages used in event monitoring. We also show that support for parameterized event types is a significant requirement for such languages.

Event monitoring has been employed in many applications such as network monitoring, active databases etc.; however, there is only an insignificant amount work done on parameterized event monitoring, a feature that is necessary in any real application. The aim of this work is to investigate solutions for parameterized event composition that is scalable and efficient; these solutions are refined from existing event monitoring algorithms. An algorithm for parameterized event composition is proposed and analysis on algorithmic time complexity is performed. In addition to this, experiments on the prototype Solicitor, a software component in DeeDS, along with simulated input of events are conducted in order to validate the theoretical model and the hypothesis that were made. The experiments support the theoretical model and suggest that it is possible to build an efficient and scalable parameterized event composition that is useful in real applications.

An event monitor is a part of a real-time system that can be used to check if the system follows the specifications posed on its behavior. This dissertation covers an approach to event monitoring where such specifications (represented by time constraints) are represented by graphs. Not much work has previously been done on designing and implementing constraint graph-based event monitors. In this work, we focus on presenting an extensible design for such an event monitor. We also evaluate different data structure types (linked lists, dynamic arrays, and static arrays) that can be used for representing the constraint graphs internally. This is done by creating an event monitor implementation, and conducting a number of benchmarks where the time used by the monitor is measured. The result is presented in the form of a design specification and a summary of the benchmark results. Dynamic arrays are found to be the generally most efficient, but advantages and disadvantages of all the data structure types are discussed.

An event monitor is a part of a real-time system that can be used to check if the system follows the specifications posed on its behavior. This dissertation covers an approach to event monitoring where such specifications (represented by time constraints) are represented by graphs. Not much work has previously been done on designing and implementing constraint graph-based event monitors. In this work, we focus on presenting an extensible design for such an event monitor. We also evaluate different data structure types (linked lists, dynamic arrays, and static arrays) that can be used for representing the constraint graphs internally. This is done by creating an event monitor implementation, and conducting a number of benchmarks where the time used by the monitor is measured. The result is presented in the form of a design specification and a summary of the benchmark results. Dynamic arrays are found to be the generally most efficient, but advantages and disadvantages of all the data structure types are discussed.

Currently the Computer Aided Prototyping System software development environment provides monitoring techniques for real-time tasking execution times. However, these techniques are constrained in that there is only a provision for simple error messages to be presented upon execution failure such as that caused by a missed deadline. This approach necessitates that the software system designer haphazardly guess a task set execution time. This thesis performed an examination of fine grain execution timing. This work was accomplished through the development of a program to perform true dynamic run time data collection of the typical task set execution exhibited within a real-time environment. The results of this work is an accurate and efficient real-time task set execution monitoring software program which assists in overcoming the problem of task set execution run time prediction. The program itself has been embedded within the Computer Aided Prototyping System environment and is an enhancement over the previous monitoring technique by providing the system designer with true and accurate run time execution times. The validation of the thesis work has been performed by successful design and development of time critical real-time prototype software within the Computer Aided Programming System usn the execution monitoring program.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

This report is a survey of monitoring and event detection in distributed fault-tolerant real-time systems, as used in primarily active database systems, for testing and debugging purposes. It contains a brief overview of monitoring in general, with examples of how software systems can be instrumented in a distributed environment, and of the active database area with additional constraints of real-time discussed. The main part is a survey of event monitoring mostly taken from the active database area with additional discussion concerning distribution and fault-tolerance. Similarities between testing and debugging distributed real-time systems are described.

Cílem této práce je vytvořit software, který je schopen monitorovat a publikovat notifikace o události z Openstack Swift i z OpenIO Software-Defined Storage (SDS) do fronty Beanstalk. Tato práce také navrhuje řešení pro publikování notifikaci o událostech z MinIO do fronty Beanstalk. K dosažení tohoto cíle je navržen nový middleware, který lze spouštět uvnitř pipeline proxy serveru v OpenStack Swift a uvnitř pipeline OIO-Swift serveru v OpenIO SDS. Navržený middleware umožňuje uživatelům určit, zda mají zájem o publikování notifikaci o události pro konkrétní objekty/kontejnery pomocí metadat. Uživatel může specifikovat sadu pravidel zahrnující vlastnosti objektu, jako je název (prefix, přípona, podřetězec) a velikost, a budou publikovány pouze události splňující tato pravidla. Přínosem této práce je unikátní software schopný monitorování událostí z OpenIO SDS i Openstack Swift., The goal of this thesis is to create software that can monitor and publish event notifications from Openstack Swift and OpenIO Software-Defined Storage (SDS) to a Beanstalk queue. In addition, this thesis also proposes a solution for publishing event notifications from MinIO to a Beanstalk queue. In order to accomplish this goal, new middleware is proposed that can be run inside a pipeline of Proxy Server in OpenStack Swift and inside the pipeline of OIO-Swift inside OpenIO SDS. Proposed middleware allows users to specify if they are interested in publishing event notifications for specific objects/containers using metadata. For example, users can specify a set of rules involving object properties, such as name (prefix, suffix) and size, and only events satisfying those rules will be published. The contribution of this thesis is unique software capable of event monitoring from both OpenIO SDS and Openstack Swift.

Bakalářská práce se zabývá analýzou stavu monitorování kybernetických bezpečnostních událostí v instituci a analýzou bezpečnostních politik instituce. Na základě analýzy pak návrhy změn nastavení monitorovacích systémů, úprav bezpečnostních politik a návrhy dalších opatření, vedoucích ke zvýšení stavu bezpečnosti informací a bezpečnosti provozu informačních systémů v instituci., The bachelor’s thesis analyzes the state of cybersecurity events monitoring in the institution and the security policies of the institution. Based on the analysis suggests updates of the settings of cybersecurity monitoring systems, changes of the security policies, and other steps to increase the state of information security and information systems security in the institution.

Bakalářská práce se zabývá analýzou stavu monitorování kybernetických bezpečnostních událostí v instituci a analýzou bezpečnostních politik instituce. Na základě analýzy pak návrhy změn nastavení monitorovacích systémů, úprav bezpečnostních politik a návrhy dalších opatření, vedoucích ke zvýšení stavu bezpečnosti informací a bezpečnosti provozu informačních systémů v instituci., The bachelor’s thesis analyzes the state of cybersecurity events monitoring in the institution and the security policies of the institution. Based on the analysis suggests updates of the settings of cybersecurity monitoring systems, changes of the security policies, and other steps to increase the state of information security and information systems security in the institution.

Cílem této práce je vytvořit software, který je schopen monitorovat a publikovat notifikace o události z Openstack Swift i z OpenIO Software-Defined Storage (SDS) do fronty Beanstalk. Tato práce také navrhuje řešení pro publikování notifikaci o událostech z MinIO do fronty Beanstalk. K dosažení tohoto cíle je navržen nový middleware, který lze spouštět uvnitř pipeline proxy serveru v OpenStack Swift a uvnitř pipeline OIO-Swift serveru v OpenIO SDS. Navržený middleware umožňuje uživatelům určit, zda mají zájem o publikování notifikaci o události pro konkrétní objekty/kontejnery pomocí metadat. Uživatel může specifikovat sadu pravidel zahrnující vlastnosti objektu, jako je název (prefix, přípona, podřetězec) a velikost, a budou publikovány pouze události splňující tato pravidla. Přínosem této práce je unikátní software schopný monitorování událostí z OpenIO SDS i Openstack Swift., The goal of this thesis is to create software that can monitor and publish event notifications from Openstack Swift and OpenIO Software-Defined Storage (SDS) to a Beanstalk queue. In addition, this thesis also proposes a solution for publishing event notifications from MinIO to a Beanstalk queue. In order to accomplish this goal, new middleware is proposed that can be run inside a pipeline of Proxy Server in OpenStack Swift and inside the pipeline of OIO-Swift inside OpenIO SDS. Proposed middleware allows users to specify if they are interested in publishing event notifications for specific objects/containers using metadata. For example, users can specify a set of rules involving object properties, such as name (prefix, suffix) and size, and only events satisfying those rules will be published. The contribution of this thesis is unique software capable of event monitoring from both OpenIO SDS and Openstack Swift.

Cílem této práce je vytvořit software, který je schopen monitorovat a publikovat notifikace o události z Openstack Swift i z OpenIO Software-Defined Storage (SDS) do fronty Beanstalk. Tato práce také navrhuje řešení pro publikování notifikaci o událostech z MinIO do fronty Beanstalk. K dosažení tohoto cíle je navržen nový middleware, který lze spouštět uvnitř pipeline proxy serveru v OpenStack Swift a uvnitř pipeline OIO-Swift serveru v OpenIO SDS. Navržený middleware umožňuje uživatelům určit, zda mají zájem o publikování notifikaci o události pro konkrétní objekty/kontejnery pomocí metadat. Uživatel může specifikovat sadu pravidel zahrnující vlastnosti objektu, jako je název (prefix, přípona, podřetězec) a velikost, a budou publikovány pouze události splňující tato pravidla. Přínosem této práce je unikátní software schopný monitorování událostí z OpenIO SDS i Openstack Swift., The goal of this thesis is to create software that can monitor and publish event notifications from Openstack Swift and OpenIO Software-Defined Storage (SDS) to a Beanstalk queue. In addition, this thesis also proposes a solution for publishing event notifications from MinIO to a Beanstalk queue. In order to accomplish this goal, new middleware is proposed that can be run inside a pipeline of Proxy Server in OpenStack Swift and inside the pipeline of OIO-Swift inside OpenIO SDS. Proposed middleware allows users to specify if they are interested in publishing event notifications for specific objects/containers using metadata. For example, users can specify a set of rules involving object properties, such as name (prefix, suffix) and size, and only events satisfying those rules will be published. The contribution of this thesis is unique software capable of event monitoring from both OpenIO SDS and Openstack Swift.

Bakalářská práce se zabývá analýzou stavu monitorování kybernetických bezpečnostních událostí v instituci a analýzou bezpečnostních politik instituce. Na základě analýzy pak návrhy změn nastavení monitorovacích systémů, úprav bezpečnostních politik a návrhy dalších opatření, vedoucích ke zvýšení stavu bezpečnosti informací a bezpečnosti provozu informačních systémů v instituci., The bachelor’s thesis analyzes the state of cybersecurity events monitoring in the institution and the security policies of the institution. Based on the analysis suggests updates of the settings of cybersecurity monitoring systems, changes of the security policies, and other steps to increase the state of information security and information systems security in the institution.

Cílem této práce je vytvořit software, který je schopen monitorovat a publikovat notifikace o události z Openstack Swift i z OpenIO Software-Defined Storage (SDS) do fronty Beanstalk. Tato práce také navrhuje řešení pro publikování notifikaci o událostech z MinIO do fronty Beanstalk. K dosažení tohoto cíle je navržen nový middleware, který lze spouštět uvnitř pipeline proxy serveru v OpenStack Swift a uvnitř pipeline OIO-Swift serveru v OpenIO SDS. Navržený middleware umožňuje uživatelům určit, zda mají zájem o publikování notifikaci o události pro konkrétní objekty/kontejnery pomocí metadat. Uživatel může specifikovat sadu pravidel zahrnující vlastnosti objektu, jako je název (prefix, přípona, podřetězec) a velikost, a budou publikovány pouze události splňující tato pravidla. Přínosem této práce je unikátní software schopný monitorování událostí z OpenIO SDS i Openstack Swift., The goal of this thesis is to create software that can monitor and publish event notifications from Openstack Swift and OpenIO Software-Defined Storage (SDS) to a Beanstalk queue. In addition, this thesis also proposes a solution for publishing event notifications from MinIO to a Beanstalk queue. In order to accomplish this goal, new middleware is proposed that can be run inside a pipeline of Proxy Server in OpenStack Swift and inside the pipeline of OIO-Swift inside OpenIO SDS. Proposed middleware allows users to specify if they are interested in publishing event notifications for specific objects/containers using metadata. For example, users can specify a set of rules involving object properties, such as name (prefix, suffix) and size, and only events satisfying those rules will be published. The contribution of this thesis is unique software capable of event monitoring from both OpenIO SDS and Openstack Swift.

Bakalářská práce se zabývá analýzou stavu monitorování kybernetických bezpečnostních událostí v instituci a analýzou bezpečnostních politik instituce. Na základě analýzy pak návrhy změn nastavení monitorovacích systémů, úprav bezpečnostních politik a návrhy dalších opatření, vedoucích ke zvýšení stavu bezpečnosti informací a bezpečnosti provozu informačních systémů v instituci., The bachelor’s thesis analyzes the state of cybersecurity events monitoring in the institution and the security policies of the institution. Based on the analysis suggests updates of the settings of cybersecurity monitoring systems, changes of the security policies, and other steps to increase the state of information security and information systems security in the institution.