Cerberus: Exploring Federated Prediction of Security Events

Modern defenses against cyberattacks increasingly rely on proactive approaches, e.g., to predict the adversary's next actions based on past events. Building accurate prediction models requires knowledge from many organizations; alas, this entails disclosing sensitive information, such as network structures, security postures, and policies, which might often be undesirable or outright impossible. In this paper, we explore the feasibility of using Federated Learning (FL) to predict future security events. To this end, we introduce Cerberus, a system enabling collaborative training of Recurrent Neural Network (RNN) models for participating organizations. The intuition is that FL could potentially offer a middle-ground between the non-private approach where the training data is pooled at a central server and the low-utility alternative of only training local models. We instantiate Cerberus on a dataset obtained from a major security company's intrusion prevention product and evaluate it vis-a-vis utility, robustness, and privacy, as well as how participants contribute to and benefit from the system. Overall, our work sheds light on both the positive aspects and the challenges of using FL for this task and paves the way for deploying federated approaches to predictive security

Formal Analysis of Artificial Collectives using Parametric Markov Models

There are many potential applications for the deployment of distributed systems composed of identical autonomous agents such as swarm robotic systems or wireless sensor networks, including remote monitoring, space exploration, or environmental clean up. Such systems need to be robust, and the loss of a small number of agents should not compromise the effectiveness of the system as they will often operate in hostile environments where individual members of that system may suffer failures, or communication may be hindered. To address this, these artificial systems are often designed to imitate the behaviour of self-organising systems found in nature, where simple reactive behaviours for individual members of a system can lead to complex global behaviours, and the collective remains robust to the loss of individuals. Despite much research being conducted into the development and evaluation of these systems, the industrial application of these technologies is still low. This issue could be addressed by further demonstrating that they can reliably, and predictably, achieve given objectives. Designing such systems is challenging, and often detailed simulations are developed for their analysis. Simulations give invaluable insight into the behaviour of such a system, however, there are often corner cases that might be overlooked. By developing a formal model of the system using some appropriate formalism, mathematical techniques can be applied during development to ensure that the system behaves correctly with respect to some given specification. These dynamic and inherently stochastic systems can be modelled as Markov processes; memoryless stochastic processes whose behaviour at any moment in time is determined solely by their current state. Model checking is an algorithmic technique to exhaustively check that a representation of a system as a Markov process exhibits some desirable property; furthermore, such an analysis can be extended to analyse systems whose parameters may not be known in an advance. However, the analysis of formal models of large systems is limited due to the resources that are required for their analysis: the size of the model may grow exponentially with the size of the system, and the subsequent analysis may prove to be impossible due to hardware or time constraints. This thesis investigates the suitability of parametric Markov models for the analysis of swarm robotic systems and wireless sensor networks. The analysis of such models is costly in terms of the size of the formal model representing a system, and the computation time required for its subsequent analysis. Modelling techniques and abstractions are developed for the construction of macroscopic models that abstract away from the identities of individual swarm robots or sensor nodes, and instead focus on the desirable global behaviours of such a system, resulting in smaller formal models. New techniques are then introduced to facilitate the analysis of large families of such models, where similarities between models who share some parameter values are exploited to speed up their analysis. In addition, new representations for such models are developed that allow for larger models to be analysed, and also significantly reduce the time required for that analysis

A mathematical model and numerical method for thermoelectric DNA sequencing

DNA sequencing is the process of determining the precise order of nucleotide bases, adenine, guanine, cytosine, and thymine within a DNA molecule. It includes any method or technology that is used to determine the order of the four bases in a strand of DNA. The advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery. Thermoelectric DNA sequencing is a novel method to sequence DNA by measuring the heat that is released when DNA polymerase inserts a deoxyribonucleoside triphosphate into a growing DNA strand. The thermoelectric device for this project is composed of four parts: a microfluidic channel with a reaction zone that contains DNA template/primer complex, the device\u27s lower channel wall, the device\u27s upper channel wall and a thin-film thermopile attached to the external surface of the lower channel wall which measures the dynamic change in temperature that results when Klenow polymerase inserts a deoxyribonucleoside triphosphate into the DNA template. Mathematical models of DNA sequencing methods can be very helpful in specifying the important DNA sequencer design parameters for optimal sequencer performance. This dissertation is to propose mathematical models that can predict the temperature change in thermoelectric DNA sequencing devices. To this end, a two-dimensional model is first developed to simulate the chemical reaction in the reaction zone and the temperature distribution in a cross-section of the device. A more sophisticated three-dimensional model is then developed, which considers the convection-diffusion process in the microchannel, the chemical reaction in the reaction zone, and the temperature change in the whole device. Because of the nonlinearity of equations, the models must be solved numerically. In particular, in this research, a Crank-Nicolson scheme is employed to discretize the convection-diffusion equations and energy equations, and the ODE solver odel5s (which uses the Gear\u27s method) in MATLAB is used to solve the chemical reaction equations. As such, concentrations of the reactants and the temperature distributions in the device are obtained. Results indicate that when the nucleoside is complementary to the next base in the DNA template, polymerization occurs, lengthening the complementary polymer and releasing thermal energy with a measurable temperature change of about 0.4-0.5 mK. This implies that the thermoelectric conceptual device for sequencing DNA may be feasible for identifying specific genes in individuals. Furthermore, mathematical and numerical methods are used to test the influential elements of temperature change by varying operational parameters and microfluidic device design variables. Results can be useful to provide the information on optimizing the DNA sequencer design parameters

An evaluation of Lolita and related natural language processing systems

This research addresses the question, "how do we evaluate systems like LOLITA?" LOLITA is the Natural Language Processing (NLP) system under development at the University of Durham. It is intended as a platform for building NL applications. We are therefore interested in questions of evaluation for such general NLP systems. The thesis has two, parts. The first, and main, part concerns the participation of LOLITA in the Sixth Message Understanding Conference (MUC-6). The MUC-relevant portion of LOLITA is described in detail. The adaptation of LOLITA for MUC-6 is discussed, including work undertaken by the author. Performance on a specimen article is analysed qualitatively, and in detail, with anonymous comparisons to competitors' output. We also examine current LOLITA performance. A template comparison tool was implemented to aid these analyses. The overall scores are then considered. A methodology for analysis is discussed, and a comparison made with current scores. The comparison tool is used to analyse how systems performed relative to each-other. One method, Correctness Analysis, was particularly interesting. It provides a characterisation of task difficulty, and indicates how systems approached a task. Finally, MUC-6 is analysed. In particular, we consider the methodology and ways of interpreting the results. Several criticisms of MUC-6 are made, along with suggestions for future MUC-style events. The second part considers evaluation from the point of view of general systems. A literature review shows a lack of serious work on this aspect of evaluation. A first principles discussion of evaluation, starting from a view of NL systems as a particular kind of software, raises several interesting points for single task evaluation. No evaluations could be suggested for general systems; their value was seen as primarily economic. That is, we are unable to analyse their linguistic capability directly

REEs in the North Africa P‐Bearing Deposits, Paleoenvironments, and EconomicPerspectives: AReview

AreviewofthecompositionalfeaturesofTunisia,Algeria,andMoroccophosphoritesisproposedinordertoassessandcomparethepaleoenvironmentalconditionsthatpromotedthede‐positformationaswellasprovideinformationabouttheireconomicperspectiveinlightofgrowingworldwidedemand.Sincethesedepositsshareaverysimilarchemicalandmineralogicalcomposi‐tion,theattentionwasfocusedonthegeochemistryofrareearthelements(REEs)andmostlyonΣREEs,CeandEuanomalies,and(La/Yb)and(La/Gd)normalizedratios.TheREEsdistributionsrevealseveraldifferencesbetweendepositsfromdifferentlocations,suggestingmostlythattheTu‐nisianandAlgerianphosphoritesprobablywerepartofthesamedepositionalsystem.There,sub‐reducingtosub‐oxicconditionsandamajorREEsadsorptionbyearlydiagenesiswererecorded.Conversely,intheMoroccanbasins,sub‐oxictooxicenvironmentsandaminordiageneticalterationoccurred,whichwaslikelyduetoadifferentseawatersupply.Moreover,thedrasticenvironmentalchangesassociatedtothePaleocene–EoceneThermalMaximumeventprobablyinfluencedthecom‐positionofNorthernAfricanphosphoritesthataccumulatedthehighestREEsamountsduringthatspanoftime.BasedontheREEsconcentrations,andconsideringtheoutlookcoefficientofREEcomposition(Koutl)andthepercentageofcriticalelementsin ΣREEs(REEdef),thestudieddepositscanbeconsideredaspromisingtohighlypromisingREEoresandcouldrepresentaprofitableal‐ternativesourceforcriticalREEs

SYSTEMS BIOLOGY OF AGING: MODELING & ANALYSIS OF MITOCHONDRIAL GENOME INTEGRITY

Ph.DDOCTOR OF PHILOSOPH

A survey of the mathematics of cryptology

Herein I cover the basics of cryptology and the mathematical techniques used in the field. Aside from an overview of cryptology the text provides an in-depth look at block cipher algorithms and the techniques of cryptanalysis applied to block ciphers. The text also includes details of knapsack cryptosystems and pseudo-random number generators