Computer Sciences Commons^™

Metagenome – Processing And Analysis, Sheetal Gosrani

Master's Projects

Metagenome means “multiple genomes” and the study of culture independent genomic content in environment is called metagenomics. Because of the advent of powerful and economic next generation sequencing technology, sequencing has become cheaper and faster and thus the study of genes and phenotypes is transitioning from single organism to that of a community present in the natural environmental sample. Once sequence data are obtained from an environmental sample, the challenge is to process, assemble and bin the metagenome data in order to get as accurate and complete a representation of the populations present in the community or to get high …

Cryptanalysis Of Typex, Kelly Chang

Master's Projects

Rotor cipher machines played a large role in World War II: Germany used Enigma; America created Sigaba; Britain developed Typex. The breaking of Enigma by Polish and (later) British cryptanalysts had a huge impact on the war. Despite be- ing based on the commercial version of the Enigma, there is no documented successful attack on Typex during its time in service. This project covers the Typex machine. We consider the development of Typex, we discuss how Typex works, and we present and analyze two distinct cryptanalytic attacks on the cipher. The first attack assumes the rotor wirings are known and …

Defeating Masquerade Detection, Avani Kothari

Master's Projects

A masquerader is an attacker who has obtained access to a legitimate user’s computer and is pretending to be that user. The masquerader’s goal is to conduct an attack while remaining undetected. Hidden Markov models (HMM) are well-known machine learning techniques that have been used successfully in a wide variety of fields, including speech recognition, malware detection, and intrusion detection systems. Previous research has shown that HMM trained on a user’s UNIX commands can provide an effective means of masquerade detection. Na ̈ Bayes is a simple classifier based on Bayes Theorem, ıve which relies on the command frequency. In …

Online Monitoring Using Kismet, Sumit Kumar

Master's Projects

Colleges and universities currently use online exams for student evaluation. Stu- dents can take assigned exams using their laptop computers and email their results to their instructor; this process makes testing more efficient and convenient for both students and faculty. However, taking exams while connected to the Internet opens many opportunities for plagiarism and cheating. In this project, we design, implement, and test a tool that instructors can use to monitor the online activity of students during an in-class online examination. This tool uses a wireless sniffer, Kismet, to capture and classify packets in real time. If a student attempts …

Cryptsim: Simulators For Classic Rotor Ciphers, Miao Ai

Master's Projects

In this project, web-based visual simulators have been implemented for three classic rotor cipher machines: Enigma, Typex, and Sigaba. Enigma was used by Germany during World War II, while Typex is a British cipher that was based on the commercial version of the Enigma. Sigaba is a relatively complex machine that was used by the Americans during the 1940s and into the 1950s. Sigaba is the most secure of the three ciphers, there was no successful attack on Sigaba during its service lifetime. Our web-based visual simulators are functionally equivalent to the actual electro- mechanical machines. Each simulator allows the …

Identifying Influential Bloggers, Sivanaga Prasad Shola

Master's Projects

This project addresses the problem of identifying influential bloggers in a web blog community. It investigates the problem of identifying influential bloggers by scoring each blog post, posted by bloggers, based on influential factors and ranking bloggers accordingly. There exists preliminary models that attempted to solve the problem but they lack some of important aspects of the blogosphere. In this project we try to combine and improve the methodologies and ideas present in the previous models. We have introduced a new influence factor, which is a combination of facebook likes and shares, into the literature that can further evaluate blog …

Cross-Lingual Text Classification With Model Translation And Document Translation, Zhang Zhang

Master's Projects

Most enterprise search engines employ data mining classifiers to classify documents. Along with the economic globalization, many companies are starting to have overseas branches or divisions. Those branches are using local languages in documents and emails. When a classifier tries to categorize those documents in another language, the trained model in mono-lingual will not work. The most direct solution would be to translate those documents in other languages into one language by the machine translator. But this solution suffers from inaccuracy of the machine translation, and the over-head work is economically inefficient. Another approach is to translate the feature extracted …

Stock Market Analysis, Sachin Kamath

Master's Projects

Stock market plays a pivotal role in financial aspect of the nation's growth, but stock market is highly volatile and complex in nature. It is affected by significant political issues, analyst calls, news articles , company's future plans of expansions and growth and many more. Hence, any investor would be interested in understanding the stock market overtime and how the factors mentioned above affect the behavior of the stock market.

On Every business day, millions of traders invest in stock market. Most of these investors lose money and others gain. However, considering any trading day, loss or gain is absolutely …

Provable De-Anonymization Of Large Datasets With Sparse Dimensions, Anupam Datta, Divya Sharma, Arunesh Sinha

Research Collection School Of Computing and Information Systems

There is a significant body of empirical work on statistical de-anonymization attacks against databases containing micro-dataabout individuals, e.g., their preferences, movie ratings, or transactiondata. Our goal is to analytically explain why such attacks work. Specifically, we analyze a variant of the Narayanan-Shmatikov algorithm thatwas used to effectively de-anonymize the Netflix database of movie ratings. We prove theorems characterizing mathematical properties of thedatabase and the auxiliary information available to the adversary thatenable two classes of privacy attacks. In the first attack, the adversarysuccessfully identifies the individual about whom she possesses auxiliaryinformation (an isolation attack). In the second attack, the adversarylearns additional …

Motivated Learning For The Development Of Autonomous Agents, Janusz A. Starzyk, James T. Graham, Pawel Raif, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A new machine learning approach known as motivated learning (ML) is presented in this work. Motivated learning drives a machine to develop abstract motivations and choose its own goals. ML also provides a self-organizing system that controls a machine’s behavior based on competition between dynamically-changing pain signals. This provides an interplay of externally driven and internally generated control signals. It is demonstrated that ML not only yields a more sophisticated learning mechanism and system of values than reinforcement learning (RL), but is also more efficient in learning complex relations and delivers better performance than RL in dynamically changing environments. In …

Evaluation Of Different Electronic Product Code Discovery Service Models, Su Mon Kywe, Jie Shi, Yingjiu Li, Raghuwanshi Kailash

Research Collection School Of Computing and Information Systems

Electronic Product Code Discovery Service (EPCDS) is an important concept in supply chain processes and in Internet of Things (IOT). It allows supply chain participants to search for their partners, communicate with them and share product information using standardized interfaces securely. Many researchers have been proposing different EPCDS models, considering different requirements. In this paper, we describe existing architecture designs of EPCDS systems, namely Directory Service Model, Query Relay Model and Aggregating Discovery Service Model (ADS). We also briefly mention Secure Discovery Service (SecDS) Model, which is an improved version of Directory Service Model with a secure attribute-based access control …

Architecture-Based Reliability Analysis Of Web Services, Cobra Mariam Rahmani

Student Work

In a Service Oriented Architecture (SOA), the hierarchical complexity of Web Services (WS) and their interactions with the underlying Application Server (AS) create new challenges in providing a realistic estimate of WS performance and reliability. The current approaches often treat the entire WS environment as a black-box. Thus, the sensitivity of the overall reliability and performance to the behavior of the underlying WS architectures and AS components are not well-understood. In other words, the current research on the architecture-based analysis of WSs is limited.

This dissertation presents a novel methodology for modeling the reliability and performance of web services. WSs …

Taxonomic Classification Of Media Reports In The Cyber Attack Domain, Jinhua Zhang

Student Work

Cyber-attacks have become a huge threat to the information age. In a previous study, cyber-attacks associated with events in Social, Political, Economic and Cultural (SPEC) dimensions were analyzed [6]. The task of this research is to construct an automated classifier that can classify media reports related to past and current cyber-attack events according to the SPEC taxonomy. The classifier was built on a machine learning principle incorporated with approaches focused on 1) document indexing; 2) calculation of classification thresholds; 3) definition of classification effectiveness; and 4) calculation of precision and recall. The classifier is expected to perform with acceptable effectiveness …

Hasbe: A Hierarchical Attribute-Based Solution For Flexible And Scalable Access Control In Cloud Computing, Zhiguo Wan, Jun'e Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing has emerged as one of the most influential paradigms in IT industry in recent years. Since this new computing technology requires users to entrust their valuable data to cloud providers, there have been increasing security and privacy concerns on outsourced data. Several schemes employing attribute-based encryption (ABE) have been proposed for access control of outsourced data in cloud computing; however, most of them suffer from inflexibility in implementing complex access control policies. In order to realize scalable, flexible, and fine-grained access control of outsourced data in cloud computing, in this paper we propose hierarchical attribute-set-based encryption (HASBE) by …

Mining Social Dependencies In Dynamic Interaction Networks, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

User-to-user interactions have become ubiquitous in Web 2.0. Users exchange emails, post on newsgroups, tag web pages, co-author papers, etc. Through these interactions, users co-produce or co-adopt content items (e.g., words in emails, tags in social bookmarking sites). We model such dynamic interactions as a user interaction network, which relates users, interactions, and content items over time. After some interactions, a user may produce content that is more similar to those produced by other users previously. We term this effect social dependency, and we seek to mine from such networks the degree to which a user may be socially dependent …

Evaluating The Effect Of Smart Parking Technology On Campus Parking System Efficiency Using Discrete Event Simulation, Glenn Phillip Surpris

Doctoral Dissertations and Master's Theses

This study was conducted to investigate the effect of smart parking systems (SPS) on parking search times (PST) in large parking lots. SPSs are systems that disseminate real-time parking spot availability to drivers searching for parking. The literature review revealed discrete event simulation (DES) to be a suitable tool for studying the dynamic behavior in parking lots. The parking lot selected for data collection was a university parking lot with 234 spaces. The data collected included arrival rates, departure rates, the geometric properties of the parking lot, preferred parking search strategies, and driving speeds. Arena 13.9, by Rockwell Automation, Inc, …

Desktop Sharing Portal, Ming-Chen Tsai

Master's Projects

Desktop sharing technologies have existed since the late 80s. It is often used in scenarios where collaborative computing is beneficial to participants in the shared environment by the control of the more knowledgeable party. But the steps required in establishing a session is often cumbersome to many. Selection of a sharing method, obtaining sharing target’s network address, sharing tool’s desired ports, and firewall issues are major hurdles for a typical non-IT user. In this project, I have constructed a web-portal that helps collaborators to easily locate each other and initialize sharing sessions. The portal that I developed enables collaborated sessions …

An Algorithm For Data Reorganization In A Multi-Dimensional Index, Urvashi Samaresh Nair

Master's Projects

In spatial databases, data are associated with spatial coordinates and are retrieved based on spatial proximity. A spatial database uses spatial indexes to optimize spatial queries. An essential ingredient for efficient spatial query processing is spatial clustering of data and reorganization of spatial data. Traditional clustering algorithms and reorganization utilities lack in performance and execution. To solve this problem we have developed an algorithm to convert a two dimensional spatial index into a single dimensional value and then a reorganization is done on the spatial data. This report describes this algorithm as well as various experiments to validate its effectiveness.

Java Design Pattern Obfuscation, Praneeth Kumar Gone

Master's Projects

Software Reverse Engineering (SRE) consists of analyzing the design and imple- mentation of software. Typically, we assume that the executable file is available, but not the source code. SRE has many legitimate uses, including analysis of software when no source code is available, porting old software to a modern programming language, and analyzing code for security vulnerabilities. Attackers also use SRE to probe for weaknesses in closed-source software, to hack software activation mecha- nisms (or otherwise change the intended function of software), to cheat at games, etc. There are many tools available to aid the aspiring reverse engineer. For example, …

Improving Backup And Restore Performance For Deduplication-Based Cloud Backup Services, Stephen Mkandawire

School of Computing: Dissertations, Theses, and Student Research

The benefits provided by cloud computing and the space savings offered by data deduplication make it attractive to host data storage services like backup in the cloud. Data deduplication relies on comparing fingerprints of data chunks, and store them in the chunk index, to identify and remove redundant data, with an ultimate goal of saving storage space and network bandwidth.

However, the chunk index presents a bottleneck to the throughput of the backup operation. While several solutions to address deduplication throughput have been proposed, the chunk index is still a centralized resource and limits the scalability of both storage capacity …

An Efficient Boosted Classifier Tree-Based Feature Point Tracking System For Facial Expression Analysis, Adam Redd Livingston

Electrical & Computer Engineering Theses & Dissertations

The study of facial movement and expression has been a prominent area of research since the early work of Charles Darwin. The Facial Action Coding System (FACS), developed by Paul Ekman, introduced the first universal method of coding and measuring facial movement. Human-Computer Interaction seeks to make human interaction with computer systems more effective, easier, safer, and more seamless. Facial expression recognition can be broken down into three distinctive subsections: Facial Feature Localization, Facial Action Recognition, and Facial Expression Classification. The first and most important stage in any facial expression analysis system is the localization of key facial features. Localization …

Structural Analysis In Multi-Relational Social Networks, Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Modern social networks often consist of multiple relationsamong individuals. Understanding the structureof such multi-relational network is essential. In sociology,one way of structural analysis is to identify differentpositions and roles using blockmodels. In thispaper, we generalize stochastic blockmodels to GeneralizedStochastic Blockmodels (GSBM) for performing positionaland role analysis on multi-relational networks.Our GSBM generalizes many different kinds of MultivariateProbability Distribution Function (MVPDF) tomodel different kinds of multi-relational networks. Inparticular, we propose to use multivariate Poisson distributionfor multi-relational social networks. Our experimentsshow that GSBM is able to identify the structuresfor both synthetic and real world network data.These structures can further be used for predicting …

Obfuscating The Topical Intention In Enterprise Text Search, Hwee Hwa Pang, Xiaokui Xiao, Jialie Shen

Research Collection School Of Computing and Information Systems

The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the search engine, without requiring it to be re-engineered. In this paper, we advocate a unique approach to profile the topics that are relevant to the user intention. Based on this approach, we introduce an (ε ₁, ε ₂)-privacy model that allows a user to stipulate that topics relevant to her intention …

Scalable Activity-Travel Pattern Monitoring Framework For Large-Scale City Environment, Youngki Lee, Sangjeong Lee, Byoungjip Kim, Jungwoo Kim, Yunseok Rhee, Junehwa Song

Research Collection School Of Computing and Information Systems

In this paper, we introduce Activity Travel Pattern (ATP) monitoring in a large-scale city environment. ATP represents where city residents and vehicles stay and how they travel around in a complex megacity. Monitoring ATP will incubate new types of value-added services such as predictive mobile advertisement, demand forecasting for urban stores, and adaptive transportation scheduling. To enable ATP monitoring, we develop ActraMon, a high-performance ATP monitoring framework. As a first step, ActraMon provides a simple but effective computational model of ATP and a declarative query language facilitating effective specification of various ATP monitoring queries. More important, ActraMon employs the shared …

Detecting Extreme Rank Anomalous Collections, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Anomaly or outlier detection has a wide range of applications, including fraud and spam detection. Most existing studies focus on detecting point anomalies, i.e., individual, isolated entities. However, there is an increasing number of applications in which anomalies do not occur individually, but in small collections. Unlike the majority, entities in an anomalous collection tend to share certain extreme behavioral traits. The knowledge essential in understanding why and how the set of entities becomes outliers would only be revealed by examining at the collection level. A good example is web spammers adopting common spamming techniques. To discover this kind of …

A Vision-Based Automatic Safe Landing-Site Detection System, Yufei Shen

Electrical & Computer Engineering Theses & Dissertations

An automatic safe landing-site detection system is proposed for aircraft emergency landing, based on visible information acquired by aircraft-mounted cameras. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing-site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing-site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the …

Exploration Of Human-Computer Interaction (Hci) Applications In Hospitality Industry, Jia Wei

UNLV Theses, Dissertations, Professional Papers, and Capstones

Purpose: The purpose of this professional paper is to explore and identify the best practices in Human-Computer Interaction (HCI) applications and use within the hospitality industry.

Statement of Objectives: To accomplish the stated purpose, first, the paper will provide the universal definition of HCI applications and define HCI within the context of hospitality industry. Second, the paper will gather and categorize information, such as the standards of designing HCI applications, from other fields of study such as informatics. Third, the paper will gather existing examples of HCI applications across different areas within the hospitality industry, such as the front desk …

Adaptive Radial Basis Function Neural Networks-Based Real Time Harmonics Estimation And Pwm Control For Active Power Filters, Eyad Kh Almaita

Dissertations

With the proliferation of nonlinear loads in the power system, harmonic pollution becomes a serious problem that affects the power quality in both transmission and distribution systems. Active power filters (APF) have been proven to be one of the most successful methods for mitigating harmonics problems. So far, different techniques have been used in harmonics extraction and control of APF to satisfy the fast response and the accuracy required by the APF. Neural networks techniques have been used successfully in different real-time and complex situations. This dissertation demonstrates four main tasks; (i) a novel adaptive radial basis function neural networks …

Efficient Reinforcement Learning In Multiple-Agent Systems And Its Application In Cognitive Radio Networks, Jing Zhang

Dissertations

The objective of reinforcement learning in multiple-agent systems is to find an efficient learning method for the agents to behave optimally. Finding Nash equilibrium has become the common learning target for the optimality. However, finding Nash equilibrium is a PPAD (Polynomial Parity Arguments on Directed graphs)-complete problem. The conventional methods can find Nash equilibrium for some special types of Markov games.

This dissertation proposes a new reinforcement learning algorithm to improve the search efficiency and effectiveness for multiple-agent systems. This algorithm is based on the definition of Nash equilibrium and utilizes the greedy and rational features of the agents. When …

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.