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In general, the consumer must depend on others to provide their software solutions. However, this outsourcing of software development has caused it to become more and more abstract as to where the software is actually being developed and by whom, and it poses a potentially large security problem for the consumer as it opens up the possibility for rogue functionality to be injected into an application without the consumer’s knowledge or consent. This begs the question of ‘How do we know that the software we use can be trusted?’ or ‘How can we have assurance that the software we use is doing only the tasks that we ask it to do?’ Traditional methods for thwarting such activities, such as virus detection engines, are far too antiquated for today’s adversary. More sophisticated research needs to be conducted in this area to combat these more technically advanced enemies. To combat the ever increasing problem of rogue applications, this dissertation has successfully applied and extended the information retrieval techniques of n-gram analysis and document similarity and the data mining techniques of dimensionality reduction and attribute extraction. This combination of techniques has generated a more effective Trojan horse, rogue application detection capability tool suite that can detect not only standalone rogue applications but also those that are embedded within other applications. This research provides several major contributions to the field including a unique combination of techniques that have provided a new tool for the administrator’s multi-pronged defense to combat the infestation of rogue applications. Another contribution involves a unique method of slicing the potential rogue applications that has proven to provide a more robust rogue application classifier. Through experimental research this effort has shown that a viable and worthy rogue application detection tool suite can be developed. Experimental results have shown that in some cases as much as a 28% increase in overall accuracy can be achieved when comparing the accepted feature selection practice of mutual information with the feature extraction method presented in this effort called randomized projection.

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Internet of Things (IoT) är det senaste högaktuella som händer inom den digitala teknik-utvecklingen. Det är ett samlingsbegrepp för den utveckling som innebär att allt från in-frastruktur, fordon och hushållsmaskiner till bohag samt levande varelser (inklusive män-niskor), utrustas med små inbyggda sensorer och datorer och på så sätt kopplas upp i ett virtuellt kommunicerande nätverk. Det talas mycket om smarta hem och smarta städer i sammanhanget. 61 procent av de svenska företagen säger sig arbeta med IoT, 50 miljarder enheter beräknas med hjälp av IoT vara uppkopplade i världen år 2020. Den omfattande digitaliseringen innebär ett paradigmskifte som kommer att påverka hela industrin och samhället, inte minst skolan. Frågan är förberedd skolan är för den senaste stora digitala utmaningen och mer specifikt hur det ser ut på teknikprogrammet. Teknikprogrammet är ett högskoleförberedande program där eleven efter erhållen examen skall ha tillräckliga kunskaper för att bli behörig till högskolestudier.

<p>The current rise in multi-drug resistant Gram-negative bacterial infections is of particularconcern. Gram-negative pathogens are difficult to treat due to their intrinsic resistome.The outer membrane (OM) of Gram-negative bacteria serves as a permeability barrier tomany antibiotics, due in large part to the lipopolysaccharide (LPS) component that isunique to these organisms, and in addition to, the OM is lined with a number of multidrugresistant efflux pumps. As the clinical effectiveness of first line therapies declines inthe face of this resistance, novel strategies to discover new antibiotics are required. Theidentification of new antibiotic targets is one method currently being applied to meet thischallenge. This work examines the permeability barrier of Escherichia coli as a possibletarget for antibiotic adjuvants. A structure-function analysis of GmhA and GmhB, whichcatalyze the first and third conserved steps in LPS ADP-heptose biosynthesis, wasperformed. The active site residues of each of these enzymes were identified viacrystallographic, mutagenic, and kinetic analyses. Potential mechanisms have beenproposed, offering insight into the function of these potential adjuvant targets. In addition,a whole screen of E. coli was performed to identify compounds that potentiatenovobiocin, an antibiotic with limited activity against Gram-negative pathogens due toOM permeability. Four small molecules were found that were able to synergize withnovobiocin. One of these, A22, is known to alter bacterial cell shape, suggesting a newpathway for antibiotic adjuvants to combat Gram-negative infection. Together, thesestudies highlight the varied targets available for novel therapeutic strategies.</p> / Doctor of Philosophy (PhD)

Widespread antimicrobial resistance, particularly in Gram-negative pathogens, is a serious threat facing the global community. Aminoglycosides are inactivated by enzymes such as aminoglycoside N-acetyltransferase-3 (AAC(3)) and O-nucleotidyltransferase-2” (ANT(2”)), while the New Delhi metallo-b- lactamase-1 (NDM-1) degrades carbapenems. Inhibition of these enzymes should result in bacteria becoming once again susceptible to aminoglycosides and carbapenems. This thesis describes the development of inhibitors to these enzymes, in an effort to rescue the utility of aminoglycoside and carbapenem drug classes through adjuvant therapy. High-throughput screening of protein kinase libraries identified two AAC(3)-Ia inhibitors with a common 3-benzylidene-2-indolinone core. New methods for purification of AAC(3)-Ia and monitoring its activity were developed. A chemical library was built around this scaffold and assessed for SAR. It was found that the initial hit (Z)-methyl 3-(3,5-dibromo-4-hydroxybenzylidene)-2- oxoindoline-5-carboxylate was the most active against AAC(3)-Ia, and alterations to either the 3,5-dibromo-4-hydroxybenzyl warhead or methyl ester substituent resulted in a decrease in activity. Previous whole-cell screening had identified two protein kinase inhibitors with a biphenyl isonicotinamide scaffold as inhibitors of ANT(2”)-Ia. A convergent parallel synthesis was developed, involving Suzuki and amide couplings and protecting group strategies. This methodology was used to assemble a focused chemical library for SAR analysis. Stepwise removal of extraneous complexity from the initial hits yielded a selective ANT(2”)-Ia inhibitor which demonstrated in vivo synergy with gentamicin. Aspergillomarasmine A (AMA) is a natural product with activity against NDM-1. Several derivatives of AMA have been synthesized to assess SAR, but the specific contributions of individual carboxylic acids have yet to determined due to difficulties accessing position 6. A synthetic approach was developed via reductive amination using Garner’s aldehyde as a serine equivalent. This strategy was used to synthesize an AMA analog with a hydroxyl group in place of the carboxylic acid in position 6. Additionally, an imine-promoted isomeric resolution was discovered. / Thesis / Doctor of Philosophy (PhD) / Antibiotics, such as aminoglycosides and carbapenems, are losing their effectiveness against bacteria responsible for deadly diseases. This is often due to resistance enzymes such as aminoglycoside N-acetyltransferase-3 (AAC(3)) and O- nucleotidyltransferase-2” (ANT(2”)), which inactivate aminoglycosides, and the New Delhi metallo-b-lactamase-1 (NDM-1), which destroys carbapenems. If these enzymes are blocked, the antibiotics should work against bacteria again. In order to develop compounds that will inhibit these enzymes, sets of similar compounds are made and tested. Patterns of what chemical groups improve or worsen inhibitory activity are noted and used to make another set of compounds in an iterative process. This thesis describes the development of inhibitors of AAC(3)-Ia and ANT(2”)-Ia by this process. Additionally, a specific compound was made to test if a particular chemical group has a role in inhibiting NDM-1.