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The proteinases present in Necator americanus larval excretory/secertory (ES) products were characterised using FITC labelled casein and shown to have a pH optimum of pH 6.5 with lesser peak of activity at pH 8. At pH 6.5 the presence of an aspartyl proteinase was demonstrated for the first time. At pH 8 a serine proteinase activity was shown to predominate. Metallo-proteinase activity was present at both pH points while cysteinyl proteinase activity was observed at pH 6.5. The mixture of proteinases secreted by both the adult and larval stages of N. americanus was further characterised by the use of a number of fluorogenic substiates. Both life cycle stages were shown to possess 'trypsin-like' serine proteinase activity together with cathepsin B and L 'like' cysteinyl proteinase activities. Larval ES products were shown to degrade the human skin macromolecules collagen (type I, III, IV and V), fibronectin, laminin and elastin. The aspartyl proteinase activity was capable of degrading all the skin macromolecules except type V collagen. The metalloproteinase degraded collagen and elastin while the serine proteinase degraded elastin alone. A number of larval and adult proteinases were purified from ES products by affinity chromatography. Cathepsin B and L 'like' cysteinyl proteinases with an approximate molecular mass of 55 kDa were purified using activated thiol Sepharose 4B, an aspartyl proteinase with a mass of 66 kDa was purified using pepstatin A agarose. A 42 kDa metallo-proteinase was purified from larval ES using Z-Gly-D-Leu-AH-Sepharose. A mixture of larval aspartyl and cathepsin B and L 'like' enzymes were used to vaccinate BALB/c mice against challenge infection with live N. americanus larvae, resulting in an apparent reduction in worm burden of 37.7% compared with non-vaccinated control animals. Immunity to N. americanus challenge infection was induced for the first time by vaccinating BALB/c mice with γ-irradiated larvae. ELISA analysis demonstrated that irradiated larvae induce a Th2 response characterised by IgGl and IL5 production typical of N. americanus infection, but with no significant difference to that induced by the same vaccination protocol using normal larvae. Further study is required to discover the mechanism or molecule(s) responsible for this immunity.

During the COVID-19 pandemic, when most businesses were not equipped for remote work and cloud computing, we saw a significant surge in ransomware attacks. This study aims to utilize machine learning and artificial intelligence to prevent known and unknown malware threats from being exploited by threat actors when developers build and deploy applications to the cloud. This study demonstrated an experimental quantitative research design using Aqua. The experiment's sample is a Docker image. Aqua checked the Docker image for malware, sensitive data, Critical/High vulnerabilities, misconfiguration, and OSS license. The data collection approach is experimental. Our analysis of the experiment demonstrated how unapproved images were prevented from running anywhere in our environment based on known vulnerabilities, embedded secrets, OSS licensing, dynamic threat analysis, and secure image configuration. In addition to the experiment, the forensic data collected in the build and deployment phase are exploitable vulnerability, Critical/High Vulnerability Score, Misconfiguration, Sensitive Data, and Root User (Super User). Since Aqua generates a detailed audit record for every event during risk assessment and runtime, we viewed two events on the Audit page for our experiment. One of the events caused an alert due to two failed controls (Vulnerability Score, Super User), and the other was a successful event meaning that the image is secure to deploy in the production environment. The primary finding for our study is the forensic data associated with the two events on the Audit page in Aqua. In addition, Aqua validated our security controls and runtime policies based on the forensic data with both events on the Audit page. Finally, the study’s conclusions will mitigate the likelihood that organizations will fall victim to ransomware by mitigating and preventing the total damage caused by a malware attack.

Galapagomystides is an exclusively deep sea group of phyllodocid annelids, originally erected for Galapgomystides aristata from hydrothermal vents of the Galapagos Rift. In this study, numerous specimens of Phyllodocidae collected from hydrothermal vents and methane seeps from the Pacific Ocean, including specimens that are likely to represent Galapgomystides aristata, were studied using morphology (light microscopy and scanning electron microscopy) and DNA sequence data. Phylogenetic analysis of the newly generated molecular data (cytochrome c oxidase subunit I, 16S rRNA, 18S rRNA, and 28S rRNA) combined with an already available extensive dataset for Phyllodocidae resulted in a monophyletic Galapagomystides. Two new species from hydrothermal vents in the West Pacific, G. bobpearsoni n. sp., and G. kathyae n. sp., as well as one new species from a cold seep in the East Pacific, G. patricki n. sp. were inferred from the phylogenetic results and morphology. These new species are formally described, and a previously known vent species, Protomystides verenae, is redescribed and transferred to Galapagomystides. Galapagomystides verenae was found to occur in both vents and seeps in the eastern Pacific, from Oregon to Costa Rica. The diagnosis of Galapagomystides is amended and the biogeography and habitat evolution of the five species of Galapagomystides is discussed. This study reinforces the conception that species within the genus Galapagomystides likely feed on the blood of tube worms, resulting in the colloquial name applied here, “vampire worms”.

A botnet is a collection of remotely controlled and compromised computers that are controlled by a bot master. Botnets are the main crime tool used by cybercriminals. To use an analogy, many crimes may be committed with a gun ranging from murder to rape to armed robbery to assault to breaking and entering to theft. Likewise, a botnet may be used in many forms of cybercrime and civil wrong ranging from sending spam, to denial of service attacks, to child pornography distribution, to worm propagation, to click-fraud, to keylogging technology and traffic sniffing which captures passwords and credit card information, and to mass identity theft. Botnets are a major crime tool used on the internet in a similar fashion to how a gun is used on the street. This thesis explores the regulation of botnets and the role that botnets play as a tool to commit many forms of cybercrime. In exploring regulation of botnets, countermeasures against fighting this crime tool will be analysed, and policy options evaluated as to under what circumstances society should prioritise combating botnets at the expense of encroaching on civil liberties, in particular the values of privacy and freedom of expression. This thesis argues that Internet service providers, domain name service providers and self-organised security communities are best positioned to effectively combat botnets. In determining the most effective regulatory measures to combat botnets, this thesis has investigated, and at points discounted, a range of other measures such as data breach notification, Sarbanes-Oxley, banking law, user education and training, non-criminal legal remedies, the range of technologies that botnets utilise, economic models to disrupt profitability, national and international criminal law, and technologies non-essential to botnets. This thesis is the result of inter-disciplinary research on botnets, combining insights from the disciplines of computer security, information systems, risk management, economics, regulation and law. Based on this inter-disciplinary research, the thesis demonstrates how cybercrime laws both at the national and international levels are rendered impotent through modern obfuscation crime tools. Reforms to the law are necessary to offer security research exemptions, remote search and seizure by law enforcement and the introduction of unwanted software legislation. At the same time, more safeguards to preserve civil liberties must also be built into Australian regulatory practice. In the course of examining the most effective ways to regulate botnets, the thesis also provides a case study demonstrating weaknesses in Lessig's Internet regulatory theory. Internet regulatory theories have generally placed emphasis on civil liberties and the struggles between users and governments over control of the regulation of the Internet. These theories, however, ignored the complex issues that cybercrime would bring into the discussion. The regulation of botnets is used to evaluate the utility of Lawrence Lessig's theory of Internet regulation through four modalities (market, norms, law and code). It is argued that the levels and types of cybercrime which have occurred in the last decade and in the decades to come were not anticipated by these theories and poses new theoretical issues. This thesis will demonstrate that effective botnet regulation will involve some use of illegal means, and inevitably will challenge not only the mindset that the law plays an authoritative role in regulation, but also Lessig's theory that market, code, and norms are the only significant forms of regulation. Changes or developments of Lessig's model are required. For example, many of the actions by self-organised security groups to combat botnets may be conceived as effective and moral though, as will be demonstrated, clearly illegal. The work of self-help remedies by these groups does not fit well with Lessig's theory. Self-organised security communities do not fall within any of Lessig's modalities and yet, the efforts of such groups are the most important countermeasures in combating botnets, and possibly in combating many forms of cybercrime.

Attacks on the Internet are characterized by several alarming trends: 1) increases in frequency; 2) increases in speed; and 3) increases in severity. Modern computer worms simply propagate too quickly for human detection. Since attacks are now occurring at a speed which prevents direct human intervention, there is a need to develop automated defenses. Since the financial, social and political stakes are so high, we need defenses which are provably good against worst case attacks and are not too costly to deploy. In this dissertation we present two approaches to tackle these problems. For the first part of the dissertation we consider a game between an alert and a worm over a large network. We show, for this game, that it is possible to design an algorithm for the alerts that can prevent any worm from infecting more than a vanishingly small fraction of the nodes with high probability. Critical to our result is designing a communication network for spreading the alerts that has high expansion. The expansion of the network is related to the gap between the 1st and 2nd eigenvalues of the adjacency matrix. Intuitively high expansion ensures redundant connectivity. We also present results simulating our algorithm on networks of size up to $2^{25}$. In the second part of this dissertation we consider the virus inoculation game which models the selfish behavior of the nodes involved. We present a technique for this game which makes it possible to achieve the 'windfall of malice' even without the actual presence of malicious players. We also show the limitations of this technique for congestion games that are known to have a windfall of malice.