Passive capillary wick samplers (PCAPs) are primarily used to sample water from the vadose zone. PCAPs use fiberglass wicks to form a hanging water column that exerts suction on the surrounding soil. Although PCAPs have been used to estimate soil water flux, the accuracy with which PCAPs can estimate flux comes into question due to over/undersampling caused by this applied flux. I used numerical models to explore the effects of a PCAP on flow through the vadose zone. Specifically, I used a two-dimensional axisymmetric flow model of a PCAP embedded in a medium based on HYDRUS. Both steady-state and transient conditions were simulated through the application of various precipitation rates and periods across several soil textures. In this study, I examine soil hydraulic properties, across the soil texture triangle, subject to a range of precipitation events. Results show that the PCAP does over/underestimate water flux. The degree of error is quantified by defining a capture efficiency, which is the ratio of the flux into the plate and the flux that would occur at the same depth with no PCAP present. Higher fluxes and longer time periods resulted in increased convergence of flux into the PCAP, while lower fluxes and shorter durations resulted in divergence of flux from the PCAP. The goal of the study is to understand the behavior of PCAPs under different conditions and to use that knowledge to interpret field measurements in the Jemez River Basin Critical Zone Observatory.

This thesis solves possibility of using entropy for anomaly detection in data communication and especially for security attacks. The main advantage of using entropy is ability to identify unknown attacks because entropy detects changes in network traffic but not the content as existing methods. In this work was tested the suitability of different models entropy (Shannon, Renyi, Tsallis). Also been tested the effect of Renyi and Tsallis parameter on resulting entropy. From the resulting values, I found that all tested entropy achieve good result in the identification of anomalies in network traffic.

The Xilinx Multiprocessor System-on-Chip (MPSoC) is a complex device that uses 16nm FinFET technology to combine multiple processors, a large amount of FPGA resources, and many I/O interfaces on a single chip die. These features make the MPSoC a high-performance and architecturally flexible device. The potential computing power makes the MPSoC ideal for many embedded applications including terrestrial and space applications. The MPSoC, however, does not have extensive radiation history as many other devices have. The extent of the effect that ionized particles may have on the MPSoC is not well established. To solve this problem, neutron radiation testing can be used to determine the device's susceptibility to single-event upsets (SEUs). Though this thesis is not intended to qualify the MPSoC for space, this work does provide useful neutron radiation test data that helps to characterize the susceptible nature of the device. This thesis summarizes the SEU results obtained from neutron testing on the UltraScale+ MPSoC ZU9EG device. A series of three neutron beam tests were performed on the MPSoC ZU9EG at Los Alamos National Laboratories (LANL). Testing was performed using a novel testing methodology to collect SEU counts on the programmable logic and the processing system simultaneously. These results show a 10.1× improvement of the programmable logic CRAM over the previous Xilinx UltraScale device series.

The Xilinx Multiprocessor System-on-Chip (MPSoC) is a complex device that uses 16nm FinFET technology to combine multiple processors, a large amount of FPGA resources, and many I/O interfaces on a single chip die. These features make the MPSoC a high-performance and architecturally flexible device. The potential computing power makes the MPSoC ideal for many embedded applications including terrestrial and space applications.The MPSoC, however, does not have extensive radiation history as many other devices have. The extent of the effect that ionized particles may have on the MPSoC is not well established. To solve this problem, neutron radiation testing can be used to determine the device's susceptibility to single-event upsets (SEUs). . Though this thesis is not intended to qualify the MPSoC for space, this work does provide useful neutron radiation test data that helps to characterize the susceptible nature of the device. This thesis summarizes the SEU results obtained from neutron testing on the UltraScale+ MPSoC ZU9EG device. A series of three neutron beam tests were performed on the MPSoC ZU9EG at Los Alamos National Laboratories (LANL). Testing was performed using a novel testing methodology to collect SEU counts on the programmable logic and the processing system simultaneously. These results show a $10.1 timess improvement of the programmable logic CRAM over the previous Xilinx UltraScale device series.

The aim of this thesis is to show how to design and implement an application for network traces analysis using Apache Spark distributed system. Implementation can be divided into three parts - loading data from a distributed HDFS storage, supported network protocols analysis and distributed data processing. As a data visualization tool is used web-based notebook Apache Zeppelin. The resulting application is able to analyze individual packets as well as the entire flows. It supports JSON and pcap as input data formats. The goal of the application is to allow Big Data processing. The greatest impact on its performance has the input data format and allocation of the available cores.

This thesis describes the design and implementation of system for effective detection of network anomaly using DNS data. Effective detection is accomplished by combination and cooperation of detectors and detection techniques. Flow data in NetFlow and IPFIX formats are used as input for detection. Also packets in pcap format can be used. Main focus is put on detection of DNS tunneling. Thesis also describes Domain Name System (DNS) and anomalies associated with DNS.

This thesis is meant to present the methods of cluster analysis, their use for detecting network traffic anomalies. It deals with various types of cyber attacks particularly DoS (DDoS) attacks. It contains a list of well-known DoS attacks. Also includes a program in Python, using the k-means method for detection of anomalous traffic.

There is a growing need for more efficient tools and services for log analysis. A need that comes from the ever-growing use of digital services and applications, each one generating thousands of lines of log event message for the sake of auditing and troubleshooting. This thesis was initiated on behalf of one of the departments of the IT consulting company TietoEvry in Karlstad. The purpose of this thesis project was to investigate whether the log analysis service Elastic Stack would be a suitable solution for TietoEvry’s need for a more efficient method of log event analysis. As part of this investigation, a small-scale deployment of Elastic Stack was created, used as proof of concept. The investigation showed that Elastic Stack would be a suitable tool for the monitoring and analysis needs of TietoEvry. The final version of deployment was, however, not able to fulfill all of the requirements that were initially set out by TietoEvry, however, this was mainly due to a lack of time and rather than limitations of Elastic Stack.

This master‘s thesis focuses on distributed processing of big data from network communication. It begins with exploring network communication based on TCP/IP model with focus on data units on each layer, which is necessary to process during analyzation. In terms of the actual processing of big data is described programming model MapReduce, architecture of Apache Hadoop technology and it‘s usage for processing network flows on computer cluster. Second part of this thesis deals with design and following implementation of the application for processing network flows from network communication. In this part are discussed main and problematic parts from the actual implementation. After that this thesis ends with a comparison with available applications for network analysis and evaluation set of tests which confirmed linear growth of acceleration.

Monitoring and security in multigigabit networks with speeds 1 - 100 Gb/s needs hardware acceleration. NetCOPE platform for rapid development of network applications uses hardware acceleration card with FPGA technology by means of hardware/software codesign. Increas in performance of platform's software part is dependent of parallel processing in applications to take advantage of utilising more processor cores. This thesis analyses NetCOPE platform architecture and possibilities of parallelising classic network applications and creates models of concurrent access to data in NetCOPE platform to utilize more processor cores. These models are subsequently implemented as extensions to platform's Linux system drivers. Userspace libraries are created to provide simple interface for applications to use these new features. To achieve high throughput of this solution several optimizations are performed. Results are measured by created testing tools.