An Artificial Neural Network-based Decision-Support System for Integrated Network Security

As large-scale Cyber attacks become more sophisticated, local network defenders should employ strength-in-numbers to achieve mission success. Group collaboration reduces individual efforts to analyze and assess network traffic. Network defenders must evolve from an isolated defense in sector policy and move toward a collaborative strength-in-numbers defense policy that rethinks traditional network boundaries. Such a policy incorporates a network watch ap-proach to global threat defense, where local defenders share the occurrence of local threats in real-time across network security boundaries, increases Cyber Situation Awareness (CSA) and provides localized decision-support. A single layer feed forward artificial neural network (ANN) is employed as a global threat event recommender system (GTERS) that learns expert-based threat mitigation decisions. The system combines the occurrence of local threat events into a unified global event situation, forming a global policy that allows the flexibility of various local policy interpretations of the global event. Such flexibility enables a Linux based network defender to ignore windows-specific threats while focusing on Linux threats in real-time. In this thesis, the GTERS is shown to effectively encode an arbitrary policy with 99.7% accuracy based on five threat-severity levels and achieves a generalization accuracy of 96.35% using four distinct participants and 9-fold cross-validation

Pseudomonas aeruginosa Population Structure Revisited

At present there are strong indications that Pseudomonas aeruginosa exhibits an epidemic population structure; clinical isolates are indistinguishable from environmental isolates, and they do not exhibit a specific (disease) habitat selection. However, some important issues, such as the worldwide emergence of highly transmissible P. aeruginosa clones among cystic fibrosis (CF) patients and the spread and persistence of multidrug resistant (MDR) strains in hospital wards with high antibiotic pressure, remain contentious. To further investigate the population structure of P. aeruginosa, eight parameters were analyzed and combined for 328 unrelated isolates, collected over the last 125 years from 69 localities in 30 countries on five continents, from diverse clinical (human and animal) and environmental habitats. The analysed parameters were: i) O serotype, ii) Fluorescent Amplified-Fragment Length Polymorphism (FALFP) pattern, nucleotide sequences of outer membrane protein genes, iii) oprI, iv) oprL, v) oprD, vi) pyoverdine receptor gene profile (fpvA type and fpvB prevalence), and prevalence of vii) exoenzyme genes exoS and exoU and viii) group I pilin glycosyltransferase gene tfpO. These traits were combined and analysed using biological data analysis software and visualized in the form of a minimum spanning tree (MST). We revealed a network of relationships between all analyzed parameters and non-congruence between experiments. At the same time we observed several conserved clones, characterized by an almost identical data set. These observations confirm the nonclonal epidemic population structure of P. aeruginosa, a superficially clonal structure with frequent recombinations, in which occasionally highly successful epidemic clones arise. One of these clones is the renown and widespread MDR serotype O12 clone. On the other hand, we found no evidence for a widespread CF transmissible clone. All but one of the 43 analysed CF strains belonged to a ubiquitous P. aeruginosa “core lineage” and typically exhibited the exoS+/exoU− genotype and group B oprL and oprD alleles. This is to our knowledge the first report of an MST analysis conducted on a polyphasic data set

Improved Constraints on the 21 cm EoR Power Spectrum and the X-Ray Heating of the IGM with HERA Phase I Observations

We report the most sensitive upper limits to date on the 21 cm epoch of reionization power spectrum using 94 nights of observing with Phase I of the Hydrogen Epoch of Reionization Array (HERA). Using similar analysis techniques as in previously reported limits (HERA Collaboration 2022a), we find at 95% confidence that $\Delta^2(k = 0.34$ $h$ Mpc$^{-1}$) $\leq 457$ mK$^2$ at $z = 7.9$ and that $\Delta^2 (k = 0.36$ $h$ Mpc$^{-1}) \leq 3,496$ mK$^2$ at $z = 10.4$, an improvement by a factor of 2.1 and 2.6 respectively. These limits are mostly consistent with thermal noise over a wide range of $k$ after our data quality cuts, despite performing a relatively conservative analysis designed to minimize signal loss. Our results are validated with both statistical tests on the data and end-to-end pipeline simulations. We also report updated constraints on the astrophysics of reionization and the cosmic dawn. Using multiple independent modeling and inference techniques previously employed by HERA Collaboration (2022b), we find that the intergalactic medium must have been heated above the adiabatic cooling limit at least as early as $z = 10.4$, ruling out a broad set of so-called "cold reionization" scenarios. If this heating is due to high-mass X-ray binaries during the cosmic dawn, as is generally believed, our result's 99% credible interval excludes the local relationship between soft X-ray luminosity and star formation and thus requires heating driven by evolved low-metallicity stars.Comment: 57 pages, 37 figures. Updated to match the accepted ApJ version. Corresponding author: Joshua S. Dillo