Computer Sciences Commons^™

Policy-Agnostic Programming On The Client-Side, Kushal Palesha

Master's Projects

Browser security has become a major concern especially due to web pages becoming more complex. These web applications handle a lot of information, including sensitive data that may be vulnerable to attacks like data exfiltration, cross-site scripting (XSS), etc. Most modern browsers have security mechanisms in place to prevent such attacks but they still fall short in preventing more advanced attacks like evolved variants of data exfiltration. Moreover, there is no standard that is followed to implement security into the browser.

A lot of research has been done in the field of information flow security that could prove to be …

Implementing Dynamic Coarse & Fine Grained Taint Analysis For Rhino Javascript, Tejas Saoji

Master's Projects

Web application systems today are at great risk from attackers. They use methods like cross-site scripting, SQL injection, and format string attacks to exploit vulnerabilities in an application. Standard techniques like static analysis, code audits seem to be inadequate in successfully combating attacks like these. Both the techniques point out the vulnerabilities before an application is run. However, static analysis may result in a higher rate of false positives, and code audits are time-consuming and costly. Hence, there is a need for reliable detection mechanisms.

Dynamic taint analysis offers an alternate solution — it marks the incoming data from the …

A Ltihub For Composite Assignments, Sunita Rajain

Master's Projects

Learning management systems (LMS) such as Canvas and Blackboard use Learning Tool Interoperability (LTI) as their main integration point for external learning tools. Each external tool provider has to implement LTI specifications or follow LTI standards that is a time consuming and complex process as there is no easy to follow specification available. Through this project, I have developed a system that follows the LTI specifications and integrates the CodeCheck autograder and interactive exercises with any LMS. I developed a Java based web app named LTIHub that acts as a mediator between LMS and any Learning Tool Provider. The LTIHub …

Headline Generation Using Deep Neural Networks, Dhruven Vora

Master's Projects

News headline generation is one of the important text summarization tasks. Human generated news headlines are generally intended to catch the eye rather than provide useful information. There have been many approaches to generate meaningful headlines by either using neural networks or using linguistic features. In this report, we are proposing a novel approach based on integrating Hedge Trimmer, which is a grammar based extractive summarization system with a deep neural network abstractive summarization system to generate meaningful headlines. We analyze the results against current recurrent neural network based headline generation system.

Application Of Computational Methods To Study The Selection Of Authentic And Cryptic Splice Sites, Tapomay Dey

Master's Projects

Proteins are building blocks of the bodies of eukaryotes, and the process of synthesizing proteins from DNA is crucial for the good health of an organism [13]. However, some mutations in the DNA may disrupt the selection of 5’ or 3’ splice sites by a spliceosome. An important research question is whether the disruptions have a stochastic relation to the position of nucleotides in the vicinity of the known authentic and cryptic splice sites. This can be achieved by proving that the authentic and cryptic splice sites are intrinsically different. However, the behavior of the spliceosome is not accurately known. …

Named Entity Recognition And Classification For Natural Language Inputs At Scale, Shreeraj Dabholkar

Master's Projects

Natural language processing (NLP) is a technique by which computers can analyze, understand, and derive meaning from human language. Phrases in a body of natural text that represent names, such as those of persons, organizations or locations are referred to as named entities. Identifying and categorizing these named entities is still a challenging task, research on which, has been carried out for many years. In this project, we build a supervised learning based classifier which can perform named entity recognition and classification (NERC) on input text and implement it as part of a chatbot application. The implementation is then scaled …

Image Spam Detection, Aneri Chavda

Master's Projects

Email is one of the most common forms of digital communication. Spam can be de ned as unsolicited bulk email, while image spam includes spam text embedded inside images. Image spam is used by spammers so as to evade text-based spam lters and hence it poses a threat to email based communication. In this research, we analyze image spam detection methods based on various combinations of image processing and machine learning techniques.

Analysis Of Periodicity In Botnets, Prathiba Nagarajan

Master's Projects

A botnet consists of a network of infected computers which are controlled re- motely via a command and control (C&C) server. A typical botnet requires frequent communication between the C&C server and the infected nodes. Previous approaches to detecting botnets have employed various machine learning techniques, based on features extracted from network tra c. In this research, we carefully analyze the pe- riodicity of tra c as a means for detecting a variety of botnets by applying machine learning to publicly available datasets.

Mmorpgs And Their Effect On Players, Udit Manocha

ART 108: Introduction to Games Studies

The purpose of this essay is to explore the popularity and effects of video games in the MMORPG genre. Games and play have been a part of human culture for an exceptionally long time, and in the recent decades video games have a become a large medium to continue this. Studying how video games, such as MMORPGs, can be used in order to advance life skills is important to understand the future of human development. By researching other studies done on various topics of related to MMORPG, I developed the idea that this genre of video games could be very …

Inside The Mind Of Mcmillen, Tina Duong

ART 108: Introduction to Games Studies

The paper discusses how Edmund McMillen created “The Binding of Isaac”. It goes into his inspirations, influences, and his background leading up to the game. It then describes the game, going into its mechanics, design, art and story and how each of these elements were unique and risky to put into an Indie game. I discussed how “The Binding of Isaac” brought in fresh, new elements that most mainstream games wouldn’t dare touch, and despite that “Binding of Isaac” accomplished amazing success. Then, I talk about how the game was initially made by a group of two people, and was …

Glhf: A Brief Overview Of Gaming Cafes, John Sun

ART 108: Introduction to Games Studies

My paper is on the history of internet and gaming cafes, focusing on how they are seen today, the problems they face and some potential solutions. Although my focus is on gaming cafes in America, because they are so popular overseas in Asian countries (such as South Korea, China, and Japan), they inevitably come up more often in my paper and presentation.

Art/Cs 108, Introduction To Game Studies, Section 2, Spring 2017, James Morgan

ART 108: Introduction to Games Studies

Course syllabus.

Art/Cs 108, Introduction To Game Studies, Section 1, Spring 2017, James Morgan

ART 108: Introduction to Games Studies

Course syllabus.

Improving Energy Efficiency For Iot Communications In 5g Networks, Gary Su

Master's Projects

Increase in number of Internet of Things (IoT) devices is quickly changing how mobile networks are being used by shifting more usage to uplink transmissions rather than downlink transmissions. Currently, mobile network uplinks utilize Single Carrier Frequency Division Multiple Access (SC-FDMA) schemes due to the low Peak to Average Power Ratio (PAPR) when compared to Orthogonal Frequency Division Multiple Access (OFDMA). In an IoT perspective, power ratios are highly important in effective battery usage since devices are typically resource-constrained. Fifth Generation (5G) mobile networks are believed to be the future standard network that will handle the influx of IoT device …

Generic Online Learning For Partial Visible & Dynamic Environment With Delayed Feedback, Behrooz Shahriari

Master's Projects

Reinforcement learning (RL) has been applied to robotics and many other domains which a system must learn in real-time and interact with a dynamic environment. In most studies the state-action space that is the key part of RL is predefined. Integration of RL with deep learning method has however taken a tremendous leap forward to solve novel challenging problems such as mastering a board game of Go. The surrounding environment to the agent may not be fully visible, the environment can change over time, and the feedbacks that agent receives for its actions can have a fluctuating delay. In this …

Mining Frequency Of Drug Side Effects Over A Large Twitter Dataset Using Apache Spark, Dennis Hsu

Master's Projects

Despite clinical trials by pharmaceutical companies as well as current FDA reporting systems, there are still drug side effects that have not been caught. To find a larger sample of reports, a possible way is to mine online social media. With its current widespread use, social media such as Twitter has given rise to massive amounts of data, which can be used as reports for drug side effects. To process these large datasets, Apache Spark has become popular for fast, distributed batch processing. In this work, we have improved on previous pipelines in sentimental analysis-based mining, processing, and extracting tweets …

Design Concept For A Failover Mechanism In Distributed Sdn Controllers, Nathan Kong

Master's Projects

Software defined networking allows the separation of the control plane and data plane in networking. It provides scalability, programmability, and centralized control. It will use these traits to reach ubiquitous connectivity. Like all concepts software defined networking does not offer these advantages without a cost. By utilizing a centralized controller, a single point of failure is created. To address this issue, this paper proposes a distributed controller failover. This failover will provide a mechanism for recovery when controllers are not located in the same location. This failover mechanism is based on number of hops from orphan nodes to the controller …

Multi-Valued Sequences Generated By Power Residue Symbols Over Odd Characteristic Fields, Begum Nasima, Yasuyuki Nogami, Satoshi Uehara, Robert Morelos-Zaragoza

Faculty Publications

This paper proposes a new approach for generating pseudo random multi-valued (including binary-valued) sequences. The approach uses a primitive polynomial over an odd characteristic prime field $\f{p}$, where p is an odd prime number. Then, for the maximum length sequence of vectors generated by the primitive polynomial, the trace function is used for mapping these vectors to scalars as elements in the prime field. Power residue symbol (Legendre symbol in binary case) is applied to translate the scalars to k-value scalars, where k is a prime factor of p-1. Finally, a pseudo random k-value sequence is obtained. Some important properties …

Intelligent Web Crawler For Semantic Search Engine, Shujia Zhang

Master's Projects

A Semantic Search Engine (SSE) is a program that produces semantic-oriented concepts from the Internet. A web crawler is the front end of our SSE; its primary goal is to supply important and necessary information to the data analysis component of SSE. The main function of the analysis component is to produce the concepts (moderately frequent finite sequences of keywords) from the input; it uses some variants of TF-IDF as a primary tool to remove stop words. However, it is a very expensive way to filter out stop words using the idea of TF-IDF. The goal of this project is …

Malware Detection Using The Index Of Coincidence, Bhavna Gurnani

Master's Projects

In this research, we apply the Index of Coincidence (IC) to problems in malware analysis. The IC, which is often used in cryptanalysis of classic ciphers, is a technique for measuring the repeat rate in a string of symbols. A score based on the IC is applied to a variety of challenging malware families. We nd that this relatively simple IC score performs surprisingly well, with superior results in comparison to various machine learning based scores, at least in some cases.

Impact Of Reviewer Social Interaction On Online Consumer Review Fraud Detection, Kunal Goswami, Younghee Park, Chungsik Song

Faculty Publications

Background Online consumer reviews have become a baseline for new consumers to try out a business or a new product. The reviews provide a quick look into the application and experience of the business/product and market it to new customers. However, some businesses or reviewers use these reviews to spread fake information about the business/product. The fake information can be used to promote a relatively average product/business or can be used to malign their competition. This activity is known as reviewer fraud or opinion spam. The paper proposes a feature set, capturing the user social interaction behavior to identify fraud. …

Robust And Agile System Against Fault And Anomaly Traffic In Software Defined Networks, Mihui Kim, Younghee Park, Rohit Kotalwar

Faculty Publications

The main advantage of software defined networking (SDN) is that it allows intelligent control and management of networking though programmability in real time. It enables efficient utilization of network resources through traffic engineering, and offers potential attack defense methods when abnormalities arise. However, previous studies have only identified individual solutions for respective problems, instead of finding a more global solution in real time that is capable of addressing multiple situations in network status. To cover diverse network conditions, this paper presents a comprehensive reactive system for simultaneously monitoring failures, anomalies, and attacks for high availability and reliability. We design three …

Human-Centered Authentication Guidelines, Jeremiah Still, Ashley Cain, David Schuster

Faculty Publications

PurposeDespite the widespread use of authentication schemes and the rapid emergence of novel authentication schemes, a general set of domain-specific guidelines has not yet been developed. This paper aims to present and explain a list of human-centered guidelines for developing usable authentication schemes.Design/methodology/approachThe guidelines stem from research findings within the fields of psychology, human–computer interaction and information/computer science.FindingsInstead of viewing users as the inevitable weak point in the authentication process, this study proposes that authentication interfaces be designed to take advantage of users’ natural abilities. This approach requires that one understands how interactions with authentication interfaces can be improved and …

Cryptanalysis Of Homophonic Substitution Cipher Using Hidden Markov Models, Guannan Zhong

Master's Projects

We investigate the effectiveness of a Hidden Markov Model (HMM) with random restarts as a mean of breaking a homophonic substitution cipher. Based on extensive experiments, we find that such an HMM-based attack outperforms a previously de- veloped nested hill climb approach, particularly when the ciphertext message is short. We then consider a combination cipher, consisting of a homophonic substitution and a column transposition. We develop and analyze an attack on such a cipher. This attack employs an HMM (with random restarts), together with a hill climb to recover the column permutation. We show that this attack can succeed on …

Real-Time Online Chinese Character Recognition, Wenlong Zhang

Master's Projects

In this project, I built a web application for handwritten Chinese characters recognition in real time. This system determines a Chinese character while a user is drawing/writing it. The techniques and steps I use to build the recognition system include data preparation, preprocessing, features extraction, and classification. To increase the accuracy, two different types of neural networks ared used in the system: a multi-layer neural network and a convolutional neural network.

Handling Relationships In A Wiki System, Yashi Kamboj

Master's Projects

Wiki software enables users to manage content on the web, and create or edit web pages freely. Most wiki systems support the creation of hyperlinks on pages and have a simple text syntax for page formatting. A common, more advanced feature is to allow pages to be grouped together as categories. Currently, wiki systems support categorization of pages in a very traditional way by specifying whether a wiki page belongs to a category or not. Categorization represents unary relationship and is not sufficient to represent n-ary relationships, those involving links between multiple wiki pages.

In this project, we extend Yioop, …

Predicting User's Future Requests Using Frequent Patterns, Marc Nipuna Dominic Savio

Master's Projects

In this research, we predict User's Future Request using Data Mining Algorithm. Usage of the World Wide Web has resulted in a huge amount of data and handling of this data is getting hard day by day. All this data is stored as Web Logs and each web log is stored in a different format with different Field names like search string, URL with its corresponding timestamp, User ID’s that helps for session identification, Status code, etc. Whenever a user requests for a URL there is a delay in getting the page requested and sometimes the request is denied. Our …

Deep Data Analysis On The Web, Xuanyu Liu

Master's Projects

Search engines are well known to people all over the world. People prefer to use keywords searching to open websites or retrieve information rather than type typical URLs. Therefore, collecting finite sequences of keywords that represent important concepts within a set of authors is important, in other words, we need knowledge mining. We use a simplicial concept method to speed up concept mining. Previous CS 298 project has studied this approach under Dr. Lin. This method is very fast, for example, to mine the concept, FP-growth takes 876 seconds from a database with 1257 columns 65k rows, simplicial complex only …

Web-Based Integrated Development Environment, Hien T. Vu

Master's Projects

As tablets become more powerful and more economical, students are attracted to them and are moving away from desktops and laptops. Their compact size and easy to use Graphical User Interface (GUI) reduce the learning and adoption barriers for new users. This also changes the environment in which undergraduate Computer Science students learn how to program. Popular Integrated Development Environments (IDE) such as Eclipse and NetBeans require disk space for local installations as well as an external compiler. These requirements cannot be met by current tablets and thus drive the need for a web-based IDE. There are also many other …

A Multi-Value Sequence Generated By Power Residue Symbol And Trace Function Over Odd Characteristic Field, Yasuyuki Nogami, Satoshi Uehara, Kazuyoshi Tsuchiya, Nasima Begum, Hiroto Ino, Robert Morelos-Zaragoza

Faculty Publications

This paper proposes a new multi-value sequence generated by utilizing primitive element, trace, and power residue symbol over odd characteristic finite field. In detail, let p and k be an odd prime number as the characteristic and a prime factor of p-1, respectively. Our proposal generates k-value sequence T={ti | ti=fk(Tr(ωi)+A)}, where ω is a primitive element in the extension field $\F{p}{m}$, Tr(⋅) is the trace function that maps $\F{p}{m} \rightarrow \f{p}$, A is a non-zero scalar in the prime field $\f{p}$, and fk(⋅) is a certain mapping function based on k-th power residue symbol. Thus, the proposed sequence has …