Computer Sciences Commons^™

Revolution In Crime: How Cryptocurrencies Have Changed The Criminal Landscape, Igor Groysman

Student Theses

This thesis will examine the ways in which various cryptocurrencies have impacted certain traditional crimes. While crime is always evolving with technology, cryptocurrencies are a game changer in that they provide anonymous and decentralized payment systems which, while they can be tracked in a reactive sense via the blockchain, are seen by criminals as having better uses for them than traditional fiat currencies, such as the ability to send money relatively fast to another party without going through an intermediary, or the ability to obscure the origin of the money for money laundering purposes. Every week there are new cryptocurrencies ...

Learning-Based Analysis On The Exploitability Of Security Vulnerabilities, Adam Bliss

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this thesis is to develop a tool that uses machine learning techniques to make predictions about whether or not a given vulnerability will be exploited. Such a tool could help organizations such as electric utilities to prioritize their security patching operations. Three different models, based on a deep neural network, a random forest, and a support vector machine respectively, are designed and implemented. Training data for these models is compiled from a variety of sources, including the National Vulnerability Database published by NIST and the Exploit Database published by Offensive Security. Extensive experiments are conducted, including testing ...

Static Analysis Of Android Secure Application Development Process With Findsecuritybugs, Xianyong Meng

Master of Science in Computer Science Theses

Mobile devices have been growing more and more powerful in recent decades, evolving from a simple device for SMS messages and phone calls to a smart device that can install third party apps. People are becoming more heavily reliant on their mobile devices. Due to this increase in usage, security threats to mobile applications are also growing explosively. Mobile app flaws and security defects can provide opportunities for hackers to break into them and access sensitive information. Defensive coding needs to be an integral part of coding practices to improve the security of our code.

We need to consider data ...

Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr.

Statistics Preprints

Warranty return data from repairable systems, such as vehicles, usually result in recurrent event data. The non-homogeneous Poisson process (NHPP) model is used widely to describe such data. Seasonality in the repair frequencies and other variabilities, however, complicate the modeling of recurrent event data. Not much work has been done to address the seasonality, and this paper provides a general approach for the application of NHPP models with dynamic covariates to predict seasonal warranty returns. A hierarchical clustering method is used to stratify the population into groups that are more homogeneous than the than the overall population. The stratification facilitates ...

A Data Set Of Bloodstain Patterns For Teaching And Research In Bloodstain Pattern Analysis: Gunshot Backspatters, Daniel Attinger, Yu Liu, Ricky Faflak, Yalin Rao, Bryce A. Struttman, Kris De Brabanter, Patrick M. Comiskey, Alex L. Yarin

Mechanical Engineering Publications

This is a data set of blood spatter patterns scanned at high resolution, generated in controlled experiments. The spatter patterns were generated with a rifle or a handgun, and different ammunitions. The resulting atomized blood droplets travelled opposite to the bullet direction, generating a gunshot backspatter on a poster board target sheet. Fresh blood with anticoagulants was used; its hematocrit and temperature were measured. Main parameters of the study were the bullet shape, size and speed, and the distance between the blood source and target sheet. Several other parameters were explored in a less systematic way. This new and original ...

Determinants Of Interval Matrices, Jaroslav Horáček, Milan Hladík, Josef Matějka

Electronic Journal of Linear Algebra

In this paper we shed more light on determinants of real interval matrices. Computing the exact bounds on a determinant of an interval matrix is an NP-hard problem. Therefore, attention is first paid to approximations. NP-hardness of both relative and absolute approximation is proved. Next, methods computing verified enclosures of interval determinants and their possible combination with preconditioning are discussed. A new method based on Cramer's rule was designed. It returns similar results to the state-of-the-art method, however, it is less consuming regarding computational time. Other methods transferable from real matrices (e.g., the Gerschgorin circles, Hadamard's inequality ...

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Zhaozheng Yin

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in ...

Enabling The Social Internet Of Things, Ahmed E. Khaled, Sumi Helal

Faculty Research and Creative Activities Symposium

No abstract provided.

A Study Of Text Simplification On Breast Cancer Information Targeting A Low-Health Literacy Population, Francisco D. Iacobelli, Xiwei Wang

Faculty Research and Creative Activities Symposium

No abstract provided.

Enhancing Value-Based Healthcare With Reconstructability Analysis: Predicting Cost Of Care In Total Hip Replacement, Cecily Corrine Froemke, Martin Zwick

Systems Science Faculty Publications and Presentations

Legislative reforms aimed at slowing growth of US healthcare costs are focused on achieving greater value per dollar. To increase value healthcare providers must not only provide high quality care, but deliver this care at a sustainable cost. Predicting risks that may lead to poor outcomes and higher costs enable providers to augment decision making for optimizing patient care and inform the risk stratification necessary in emerging reimbursement models. Healthcare delivery systems are looking at their high volume service lines and identifying variation in cost and outcomes in order to determine the patient factors that are driving this variation and ...

Virtual Reality And Visualization In Research And Cultural Preservation, Kari Noe

Mānoa Horizons

Visualization as a field can be defined as the process of turning data into interactive images to provide insight or knowledge to a user. New innovations in virtual reality hardware open up new opportunities in the field of visualization, rather than merely for entertainment. My research portfolio and poster highlight two visualization projects that I have created that utilize current virtual reality hardware, the HTC Vive and the University of Hawaiʻi at Mānoa’s Laboratory of Advanced Visualization and Applications (LAVA) Destiny-class CyberCANOE. The At-Risk Artifact Visualization System will allow users to view and study 3D models of archaeological artifacts ...

Validation Study Of Image Recognition Algorithms, Jacob Miller, Jeremy Evert

Student Research

Developments in machine learning in recent years have created opportunities that previously never existed. One such field with an explosion of opportunity is image recognition, also known as computer vision; the process in which a machine analyzes a digital image.

In order for a machine to ‘see’ as a human does, it must break down the image in a process called image segmentation. The way the machine goes about doing this is important, and many algorithms exist to determine just how a machine will decide to group the pixels in an image.

This research is a validation study of related ...

Constrained K-Means Clustering Validation Study, Nicholas Mcdaniel, Stephen Burgess, Jeremy Evert

Student Research

Machine Learning (ML) is a growing topic within Computer Science with applications in many fields. One open problem in ML is data separation, or data clustering. Our project is a validation study of, “Constrained K-means Clustering with Background Knowledge" by Wagstaff et. al. Our data validates the finding by Wagstaff et. al., which shows that a modified k-means clustering approach can outperform more general unsupervised learning algorithms when some domain information about the problem is available. Our data suggests that k-means clustering augmented with domain information can be a time efficient means for segmenting data sets. Our validation study focused ...

The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz

Daniel R. Tauritz

Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population of individuals, by regulating the probability that an individual's genes survive, typically based on fitness. Various conventional fitness based selection methods exist, each providing a unique relationship between the fitnesses of individuals in a population and their chances of selection. However, the full space of selection algorithms is only limited by max algorithm size, and each possible selection algorithm is optimal for some EA configuration applied to a particular problem class. Therefore, improved performance may be expected by tuning an EA's selection algorithm to the ...

Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent

Daniel R. Tauritz

Many abstract security measurements are based on characteristics of a graph that represents the network. These are typically simple and quick to compute but are often of little practical use in making real-world predictions. Practical network security is often measured using simulation or real-world exercises. These approaches better represent realistic outcomes but can be costly and time-consuming. This work aims to combine the strengths of these two approaches, developing efficient heuristics that accurately predict attack success. Hyper-heuristic machine learning techniques, trained on network attack simulation training data, are used to produce novel graph-based security metrics. These low-cost metrics serve as ...

A Simple Approach For Sustainable Transportation Systems In Smart Cities: A Graph Theory Model, Quinn Nelson, Donald Steffensmeier, Sachin Pawaskar

Sachin Pawaskar

Policy And Security Configuration Management Systems In Cross-Organisational Settings, Sascha Pudenz, Markus Manhart, Daniel Bachlechner, Stefan Thalmann

International Journal of Business and Technology

A context of use analysis is an important step in every software engineering project. Comprising the identification of the key system users as well as an analysis of the system environment and the activities supported, this engineering step is crucial for the successful development of information systems. Clarity with respect to the users’ demand for system support and their participation in the activities supported by the system is considered particularly important for systems which are critical for organizational continuity and which are used across organizational boundaries. Systems supporting policy and security configuration management in networks of IT service providers, their ...

Mobile-Cloud Cross Development (Mcx), Sachin Ahuja

International Journal of Business and Technology

There is a multitude of Mobile Operating Systems (MOSs) with iOS, Android, Windows Phone and, BlackBerry leading the space. New players continue to enter the market. Without a de-facto leader in this space, it has become necessary for businesses & developers to target multiple devices & MOSs in order to establish a relevant presence within their target audience. Cross-platform Mobile Development Tools (XMTs) were born out of this need to reduce developer effort in creating mobile applications by providing “write once run anywhere” (WORA) functionality. However, most of these tools sacrifice performance, features or maintainability in order to provide WORA functionality. Furthermore, these tools only attempt to manage the user interface and related client-side functionality. Most mobile applications need to follow the same principals that guide development of non-mobile web or desktop apps. Typical apps are deployed using an n-tier, cloud-based strategy with substantial functionality delegated to cloud resources. Given the above, there are two parts of an application’s anatomy that don’t get much attention – the cloud middleware functionality, and the database/model management features. In this paper I address these problems through creation of a Mobile-cloud Cross Development (McX) tool-chain that includes a type-safe meta-programming language, an integrated cloud node and, an active compiler. In order to effectively understand the problem with the current state of the art, I use 3 of the leading XMTs alongside the developed McX tool-chain and compare the effectiveness of each. The paper further introduces the language; it’s grammar and semantic structure, and provides discussions on how this approach fits the future of cross-platform, cloud-integrated mobile application development along with the associated issues and areas for further research.

Autonomous Agents As Tools For Modeling And Building Complex Control Systems That Operate In Dynamic And Unpredictable Environment, Alketa Hyso, Eva Çipi

International Journal of Business and Technology

Complex control systems that operate in not entirely predictable environment have to deal with this environment in an autonomous manner using adaptability, the ability to predict environmental changes, and to maintain their integrity. Elements of the system must be able to find a new solution in a dynamic way. In this paper, we present the modeling of a traffic lights’ control system using a multivalent system. This is a large-scale distributed system, consisting of autonomous and rational traffic light agents, in which there is no centre imposing an outcome. Multiagent system brings another kind of organization of the distributed control ...

An Innovative Web Application For Managing Academic Documents, Krenare Pireva, Petros Kefalas

International Journal of Business and Technology

Archiving versions of academic documents in consideration of green thinking was the motivation to develop an innovative tool that could organize academic documents in a centralized database. This paper presents a new web application, which aims to move towards a paperless University model for managing academic documents that are used within an educational institution, such as proposal courses, syllabuses etc. AcaDocMan, the developed application can be used by academic staff and quality assurance officers of institutions who are able not only to manage their course syllabuses but also to generate different consistent document formats for various purposes.