Applying Bag of System Calls for Anomalous Behavior Detection of Applications in Linux Containers

In this paper, we present the results of using bags of system calls for learning the behavior of Linux containers for use in anomaly-detection based intrusion detection system. By using system calls of the containers monitored from the host kernel for anomaly detection, the system does not require any prior knowledge of the container nature, neither does it require altering the container or the host kernel.Comment: Published version available on IEEE Xplore (http://ieeexplore.ieee.org/document/7414047/) arXiv admin note: substantial text overlap with arXiv:1611.0305

The effects of atmospheric dust on observations of Martian surface albedo

The Mariner 9 and Viking missions provided abundant evidence that aeolian processes are active over much of surface of Mars. A radiative transfer model was developed which allows the effects of atmospheric dust loading and variable surface albedo to be investigated. This model incorporated atmospheric dust opacity, the single scattering albedo, and particle phase function of atmospheric dust, the bidirectional; reflectance of the surface, and variable lighting and viewing geometry. The Cerberus albedo feature was examined in detail using this technique

Recovering Dense Tissue Multispectral Signal from in vivo RGB Images

Hyperspectral/multispectral imaging (HSI/MSI) contains rich information clinical applications, such as 1) narrow band imaging for vascular visualisation; 2) oxygen saturation for intraoperative perfusion monitoring and clinical decision making [1]; 3) tissue classification and identification of pathology [2]. The current systems which provide pixel-level HSI/MSI signal can be generally divided into two types: spatial scanning and spectral scanning. However, the trade-off between spatial/spectral resolution, the acquisition time, and the hardware complexity hampers implementation in real-world applications, especially intra-operatively. Acquiring high resolution images in real-time is important for HSI/MSI in intra-operative imaging, to alleviate the side effect caused by breathing, heartbeat, and other sources of motion. Therefore, we developed an algorithm to recover a pixel-level MSI stack using only the captured snapshot RGB images from a normal camera. We refer to this technique as "super-spectral-resolution". The proposed method enables recovery of pixel-level-dense MSI signals with 24 spectral bands at ~11 frames per second (FPS) on a GPU. Multispectral data captured from porcine bowel and sheep/rabbit uteri in vivo has been used for training, and the algorithm has been validated using unseen in vivo animal experiments.Comment: accepted by Hamlyn Symposium 201

Properties of dust and clouds in the Mars atmosphere: Analysis of Viking IRTM emission phase function sequences

An analysis of emission-phase-function (EPF) observations from the Viking Orbiter Infrared Thermal Mapper (IRTM) yields a wide variety of results regarding dust and cloud scattering in the Mars atmosphere and atmospheric-corrected albedos for the surface of Mars. A multiple scattering radiative transfer model incorporating a bidirectional phase function for the surface and atmospheric scattering by dust and clouds is used to derive surface albedos and dust and ice optical properties and optical depths for these various conditions on Mars

Examining the mortality effects of the Irish National Smoking Ban.

Secondhand smoke causes disease and death in those exposed, with cardiovascular and respiratory problems as the most likely outcomes. The purpose of this study was to examine the mortality effects of the Irish national smoking ban of 2004

Combinatorial innovation, evidence from patent data, and mandated innovation

This dissertation explores the implications of a new model of knowledge production. In my model, researchers have access to a set of primitive knowledge elements that can be combined to form ideas, where a new combination is a new idea. Underlying parameters governing the connections between elements stochastically determine whether a given combination yields a useful idea (some elements tend to work well together, and others do not). These underlying parameters are unknown to researchers, but as they attempt to combine elements and create ideas, they observe signals which they use to improve their beliefs via Bayesian updating. I embed this production function into a simple model of research incentives, where a firms receive a reward for discovering new and useful combinations, but pay a cost to conduct research. I investigate empirically these predictions using a large dataset on US utility patents: all 8.3 million utility patents granted between 1836 and 2012. From this analysis, I find that the probability a pair of knowledge “elements” (now proxied by technology classifications assigned by patent examiners) will be combined in any given year is increasing in the number of past combinations, decreasing over time, and increasing when both elements in the pair are also used with many other elements. These predictions are consistent with my model. The same work also predicts that patenting activity is positively correlated with changes in researcher knowledge about the connections between elements, and negatively correlated with time. Using panel data on 429 technology classes, I find the growth rate of patents is falling over time, but that increases can be forecast from positive changes in connections between elements 1-5 years earlier, even after controlling for numerous other factors. In my second paper, I examine the characteristics of the optimal research strategy for a forward-looking researcher using the above framework. To characterize the optimal strategy, I examine two special cases that permit analytic solutions, as well as a set of 100 numerically solved cases. The optimal research strategy reproduces many stylized facts about the innovation process, including the initial dominance of applied research relative to basic research. The third paper of my dissertation examines the impact of environmental policy choice on innovation, when research is characterized by unobservable (to the policy-maker) variance in technological opportunity. I assume there exist two types of energy, clean and dirty, that are perfect substitutes but for their production costs and a negative externality from dirty energy. Innovators are expected profit maximizers, and their decision to expend resources on R&D depends on technological opportunity, as well as the policy of the government. We show the policy-maker’s decision to use quota or price based incentives matters. Price based incentives such as a carbon tax are characterized by disperse outcomes, with more R&D resources expended when technological opportunity is high, and reduced amounts when technological opportunity is low. Quotas such as mandates, in contrast, lead to a more consistent level of R&D spending across differences in technological opportunity. Thus, price-based systems are more likely to deliver great technological advances or none at all, while mandates are more likely to deliver consistent incremental gains. Moreover, we also show an optimal carbon tax is likely to outperform any mandate in expected welfare terms, and has less information requirements

Blowing the smoke out of the kitchen:core issues in household energy and gender

A literature search for papers on the theme “Household Energy” finds most researchers equate the term with cooking and stoves, issues strongly identified with women. However, a number of researchers have taken a broader definition (see for example Clancy, 1998, Klingshirn 2000) to encompass all the activities that take place within a household and the linkages to a much wider system of energy supply and demand. In addition, there are significant linkages between household energy and other sectors, for example, agriculture (agricultural residues as fuel source), health (lung and eye diseases, nutrition), education (children’s opportunity for after-school study) and income generation (cottage industries). These linkages also demonstrate that it is not sufficient to consider only women when addressing household energy issues but that men also play a significant role in decision making on household energy. This paper takes this broader definition as the framework in which to examine the issues around household energy from a gendered perspective