Using random projections for dimensionality reduction in identifying rogue applications

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

KINEMATIC COMPARISON OF THE UNDERWATER DOLPHIN KICK BETWEEN SWIMMERS WITH DIFFERENT LEVELS OF COMPETITIVE ABILITY

In order to be competitive in elite swimming competition, underwater dolphin kick (UDK) is considered an essential skill to master, although swim researchers and coaches claim that the mechanics of UDK are poorly understood and are often overlooked in training. The purpose of this study was to identify kinematic differences in the UDK between experienced swimmers within a broad range of competitive abilities, using a model which more accurately represents UDK trunk undulations than models used in previous kinematic studies. Fifteen competitive male swimmers (22.16 ± 3.48 years) ranging from provincial to international level were recruited from local varsity and club programs. Swimmers were filmed performing three 15m maximum effort trials of UDK. The videos were manually digitized using a 2D twelve point model that identified three points of rotation along the trunk. A correlation analysis with horizontal velocity revealed significant correlations with downkick kick displacement (r=0.642, p=0.010), kick cycle displacement (r=0.561,p=0.029), upkick vertical toe velocity (r=0.643, p=0.010), the ratio of downkick/upkick vertical toe velocity (r=0.742, p=0.002), Strouhal number (r=-0.580, p=0.024), finger-tip amplitude (r=-0.674, p=0.006), and amplitude ratios of fmger/toe (r=-0.666, p=0.007), fmger/shoulder (r=-0.604, p=0.017), fmger/chest (r=-0.691, p=0.004), fmger/hip (r=-0.662, p=0.026), shoulder/hip (r=-0.571, p=0.026), and shoulder/chest (r=-0.723, p=0.002). Vertical toe velocities appear to be important for propulsion, and are likely related to vortex shedding. It appears that symmetry between the downkick and upkick is important for UDK performance, both mechanically and propulsively. Faster UDK swimmers were able to minimize arm and upper body amplitudes better than slower UDK swimmers, which is likely a mechanism for drag reduction. The 2D model used in this study demonstrated the presence of undulations along the trunk; however, did not accurately represent the UDK as bilateral asymmetries were identified which could not be measured. 3D models should be employed in the future to evaluate the importance of bilateral asymmetries during UDK

A Forensic Enabled Data Provenance Model for Public Cloud

Cloud computing is a newly emerging technology where storage, computation and services are extensively shared among a large number of users through virtualization and distributed computing. This technology makes the process of detecting the physical location or ownership of a particular piece of data even more complicated. As a result, improvements in data provenance techniques became necessary. Provenance refers to the record describing the origin and other historical information about a piece of data. An advanced data provenance system will give forensic investigators a transparent idea about the data\u27s lineage, and help to resolve disputes over controversial pieces of data by providing digital evidence. In this paper, the challenges of cloud architecture are identified, how this affects the existing forensic analysis and provenance techniques is discussed, and a model for efficient provenance collection and forensic analysis is proposed

A Power Grid Incident Identification Based on Physically Derived Cyber-Event Detection

This article proposes a cyber-event detection framework to aid in incident Identification and digital forensics cases aimed at investigating cyber crime committed against the critical infrastructure power grid. However, unlike other similar investigative techniques, the proposed approach examines only the physical information to derive a cyber conclusion. The developed framework extracts information from the physical parameters stored in historical databases of SCADA systems. The framework uses a pseudo-trusted model derived from randomly selected power system observations found in the historical databases. Afterwards, a technique known as Bayesian Model Averaging is used to average the models and create a more trusted model. Results indicate a successful Classification of on average 89% for the simulated cyber events of varying magnitudes

Early critical care course in children after liver transplant

Objective. To review the critical care course of children receiving orthotopic liver transplantation (OLT)

Culinary mapping and tourism development in South Africa's Karoo region

Successful development of cuisine as a niche tourism product has been portrayed in various countries in the world. The paper argues that the Karoo provides evidence of a substantial culinary resource base and an established local food identity. This, in turn, can be promoted as a tourism destination by means of culinary mapping. Geographic Information Systems (GIS) tools are used, supported by a culinary database with information compiled from various sources in literature, the internet, lifestyle magazines, recipe books, census data and tourism structures. A proposed culinary route/itinerary synthesizes the data, identifying authentic food experiences as a niche tourism product, based on a regional cuisine.http//: www.ajhtl.comam2017Consumer ScienceGeography, Geoinformatics and Meteorolog