Computer Sciences Commons^™

Online Local Communities, Mrudula Murali

Master's Projects

A community in a network is a group of nodes that are densely and closely connected to each other, get sparsely connected to the nodes outside the community. Finding communities in a large network helps solve many real-world problems. But detecting such communities in a complex network by focusing on the whole network is not feasible. Instead, we focus on finding communities around one or more seed node(s) of interest. Therefore, in this project, we find local communities. Moreover, we consider the online setting where the whole graph is unknown in the beginning and we get a stream of edges, …

Intelligent Log Analysis For Anomaly Detection, Steven Yen

Master's Projects

Computer logs are a rich source of information that can be analyzed to detect various issues. The large volumes of logs limit the effectiveness of manual approaches to log analysis. The earliest automated log analysis tools take a rule-based approach, which can only detect known issues with existing rules. On the other hand, anomaly detection approaches can detect new or unknown issues. This is achieved by looking for unusual behavior different from the norm, often utilizing machine learning (ML) or deep learning (DL) models. In this project, we evaluated various ML and DL techniques used for log anomaly detection. We …

Breaking Audio Captcha Using Machine Learning/Deep Learning And Related Defense Mechanism, Heemany Shekhar

Master's Projects

CAPTCHA is a web-based authentication method used by websites to distinguish between humans (valid users) and bots(attackers). Audio captcha is an accessible captcha meant for the visually disabled section of users such as color-blind, blind, near-sighted users. In this project, I analyzed the security of audio captchas from attacks that employ machine learning and deep learning models. Audio captchas of varying lengths (5, 7 and 10) and varying background noise (no noise, medium noise or high noise) were analyzed. I found that audio captchas with no background noise or medium background noise were easily attacked with 99% - 100% accuracy. …

Influence Analysis Based On Political Twitter Data, Jace Rose

Master's Projects

Studies of online behavior often consider how users interact online, their posting behaviors, what they are tweeting about, and how likely they are to follow other people. The problem is there is that no deeper study on the people that a user has interacted with and how these other users affect them. This study examines if it is possible to draw similar sentiment from users with whom the target user has interacted with. The data collection process gathers data from Twitter users posting to popular political hashtags, which the highest at the time published were #MAGA and #TRUMP, as well …

Classification Of Humans Into Ayurvedic Prakruti Types Using Computer Vision, Gayatri Gadre

Master's Projects

Ayurveda, a 5000 years old Indian medical science, believes that the universe and hence humans are made up of five elements namely ether, fire, water, earth, and air. The three Doshas (Tridosha) Vata, Pitta, and Kapha originated from the combinations of these elements. Every person has a unique combination of Tridosha elements contributing to a person’s ‘Prakruti’. Prakruti governs the physiological and psychological tendencies in all living beings as well as the way they interact with the environment. This balance influences their physiological features like the texture and colour of skin, hair, eyes, length of fingers, the shape of the …

Improving Steering Ability Of An Autopilot In A Fully Autonomous Car, Shivanku Mahna

Master's Projects

The world we live in is developing at a really rapid pace and along with it is developing the technology that we use. We have clearly come a long way from calling a car modern because it had a touch screen infotainment system to calling it modern because it drives on its own. The progress has been so rapid that it demands for us to analyze this and try to improvise a small part of this journey. With the same thought in mind, this project focuses on improvising the steering ability of an autonomous car. In order to make more …

Yoda – Your Only Design Assistant, Siddharth Kulkarni

Master's Projects

Converting user interface designs created by graphic designers into computer code is a typical job of a front end engineer in order to develop functional web and mobile applications. This conversion process can often be extremely tedious, slow and prone to human error. In this project, deep learning based object detection along with optical character recognition is used to generate platform ready prototypes directly from design sketches. Also, a new design language is introduced to facilitate expressive prototyping and allowing the creation of more expressive and functional designs. It is observed that the AI powered application along with modern web …

Measuring Malware Evolution Using Support Vector Machines, Mayuri Wadkar

Master's Projects

Malware is software that is designed to do harm to computer systems. Malware often evolves over a period of time as malware developers add new features and fix bugs. Thus, malware samples from the same family from different time periods can exhibit significantly different behavior. Differences between malware samples within a single family can originate from various code modifications designed to evade signature-based detection or changes that are made to alter the functionality of the malware itself. In this research, we apply feature ranking based on linear support vector machine (SVM) weights to identify, quantify, and track changes within malware …

Sensor - Based Human Activity Recognition Using Smartphones, Mustafa Badshah

Master's Projects

It is a significant technical and computational task to provide precise information regarding the activity performed by a human and find patterns of their behavior. Countless applications can be molded and various problems in domains of virtual reality, health and medical, entertainment and security can be solved with advancements in human activity recognition (HAR) systems. HAR is an active field for research for more than a decade, but certain aspects need to be addressed to improve the system and revolutionize the way humans interact with smartphones. This research provides a holistic view of human activity recognition system architecture and discusses …

Chatbots With Personality Using Deep Learning, Susmit Gaikwad

Master's Projects

Natural Language Processing (NLP) requires the computational modelling of the complex relationships of the syntax and semantics of a language. While traditional machine learning methods are used to solve NLP problems, they cannot imitate the human ability for language comprehension. With the growth in deep learning, these complexities within NLP are easier to model, and be used to build many computer applications. A particular example of this is a chatbot, where a human user has a conversation with a computer program, that generates responses based on the user’s input. In this project, we study the methods used in building chatbots, …

Optimizing E-Commerce Product Classification Using Transfer Learning, Rashmeet Kaur Khanuja

Master's Projects

The global e-commerce market is snowballing at a rate of 23% per year. In 2017, retail e-commerce users were 1.66 billion and sales worldwide amounted to 2.3 trillion US dollars, and e-retail revenues are projected to grow to 4.88 trillion USD in 2021. With the immense popularity that e-commerce has gained over past few years comes the responsibility to deliver relevant results to provide rich user experience. In order to do this, it is essential that the products on the ecommerce website be organized correctly into their respective categories. Misclassification of products leads to irrelevant results for users which not …

Real-Time Data Processing With Lambda Architecture, Omkar Ashok Malusare

Master's Projects

Data has evolved immensely in recent years, in type, volume and velocity. There are several frameworks to handle the big data applications. The project focuses on the Lambda Architecture proposed by Marz and its application to obtain real-time data processing. The architecture is a solution that unites the benefits of the batch and stream processing techniques. Data can be historically processed with high precision and involved algorithms without loss of short-term information, alerts and insights. Lambda Architecture has an ability to serve a wide range of use cases and workloads that withstands hardware and human mistakes. The layered architecture enhances …

Human Activity Recognition Based On Multimodal Body Sensing, Anish Hemant Narkhede

Master's Projects

In the recent years, human activity recognition has been widely popularized by a lot of smartphone manufacturers and fitness tracking companies. It has allowed us to gain a deeper insight into our physical health on a daily basis. However, with the evolution of fitness tracking devices and smartphones, the amount of data that is being captured by these devices is growing exponentially. This paper aims at understanding the process of dimensionality reduction such as PCA so that the data can be used to make meaningful predictions along with novel techniques using autoencoders with different activation functions. The paper also looks …

Malware Analysis On Pdf, Shubham Shashishekhar Pachpute

Master's Projects

Cyber-attacks are growing day by day and attackers are finding new techniques to cause harm to their target by spreading worms and malware. In the world of innovations and new technologies coming out every day, it creates a possibility of attacking a system and exploiting the vulnerabilities present in the system. One of the methods used for the spread of malware is the Portable Document Format (PDF) files. Due to the flexible nature of these files, it is becoming a sweet spot for the attackers to embed the malware easily into the PDF files. In this report, we are going …

Next Level: A Course Recommender System Based On Career Interests, Shehba Shahab

Master's Projects

Skills-based hiring is a talent management approach that empowers employers to align recruitment around business results, rather than around credentials and title. It starts with employers identifying the particular skills required for a role, and then screening and evaluating candidates’ competencies against those requirements. With the recent rise in employers adopting skills-based hiring practices, it has become integral for students to take courses that improve their marketability and support their long-term career success. A 2017 survey of over 32,000 students at 43 randomly selected institutions found that only 34% of students believe they will graduate with the skills and knowledge …

Speaker Recognition Using Machine Learning Techniques, Abhishek Manoj Sharma

Master's Projects

Speaker recognition is a technique of identifying the person talking to a machine using the voice features and acoustics. It has multiple applications ranging in the fields of Human Computer Interaction (HCI), biometrics, security, and Internet of Things (IoT). With the advancements in technology, hardware is getting powerful and software is becoming smarter. Subsequently, the utilization of devices to interact effectively with humans and performing complex calculations is also increasing. This is where speaker recognition is important as it facilitates a seamless communication between humans and computers. Additionally, the field of security has seen a rise in biometrics. At present, …

Contract Builder Ethereum Application, Colin M. Fowler

Master's Projects

Developments in Blockchain, smart contract, and decentralized application (“dApps”) technology have enabled new types of software that can improve efficiency within law firms by increasing speed at which attorneys may draft and execute contracts. Smart contracts and dApps are self-executing software that reside on a blockchain. Custom smart contracts can be built in a modular manner in order to emulate contracts that are commonly generated and executed in law firms. Such contracts include those for the transfer of services, goods, and title. This article explores exactly how implementations of smart contracts for law firms may look.

Image Retrieval Using Image Captioning, Nivetha Vijayaraju

Master's Projects

The rapid growth in the availability of the Internet and smartphones have resulted in the increase in usage of social media in recent years. This increased usage has thereby resulted in the exponential growth of digital images which are available. Therefore, image retrieval systems play a major role in fetching images relevant to the query provided by the users. These systems should also be able to handle the massive growth of data and take advantage of the emerging technologies, like deep learning and image captioning. This report aims at understanding the purpose of image retrieval and various research held in …

Javascript Metamorphic Malware Detection Using Machine Learning Techniques, Aakash Wadhwani

Master's Projects

Various factors like defects in the operating system, email attachments from unknown sources, downloading and installing a software from non-trusted sites make computers vulnerable to malware attacks. Current antivirus techniques lack the ability to detect metamorphic viruses, which vary the internal structure of the original malware code across various versions, but still have the exact same behavior throughout. Antivirus software typically relies on signature detection for identifying a virus, but code morphing evades signature detection quite effectively.

JavaScript is used to generate metamorphic malware by changing the code’s Abstract Syntax Tree without changing the actual functionality, making it very difficult …

Topic Classification Using Hybrid Of Unsupervised And Supervised Learning, Jayant Shelke

Master's Projects

There has been research around the idea of representing words in text as vectors and many models proposed that vary in performance as well as applications. Text processing is used for content recommendation, sentiment analysis, plagiarism detection, content creation, language translation, etc. to name a few. Specifically, we want to look at the problem of topic detection in text content of articles/blogs/summaries. With the humungous amount of text content published each and every minute on the internet, it is imperative that we have very good algorithms and approaches to analyze all the content and be able to classify most of …

Pose Estimation And Action Recognition In Sports And Fitness, Parth Vyas

Master's Projects

The emergence of large datasets and major improvements in Deep Learning has lead to many real-world applications. These applications have been focused on automotive markets, mobile markets, stock markets, and the healthcare market. Although Deep Learning has strong foundations across many areas, the few applications in Sports, Fitness, or even Injury Rehabilitation could benefit greatly from it. For example, if you are performing a workout and you need to evaluate your form, but do not have access or resources for an instructor to evaluate your form, it would be great to have an Artificial Intelligent agent provide real time feedback …

Detecting Cars In A Parking Lot Using Deep Learning, Samuel Ordonia

Master's Projects

Detection of cars in a parking lot with deep learning involves locating all objects of interest in a parking lot image and classifying the contents of all bounding boxes as cars. Because of the variety of shape, color, contrast, pose, and occlusion, a deep neural net was chosen to encompass all the significant features required by the detector to differentiate cars from not cars. In this project, car detection was accomplished with a convolutional neural net (CNN) based on the You Only Look Once (YOLO) model architectures. An application was built to train and validate a car detection CNN as …

An Ensemble Model For Click Through Rate Prediction, Muthaiah Ramanathan

Master's Projects

Internet has become the most prominent and accessible way to spread the news about an event or to pitch, advertise and sell a product, globally. The success of any advertisement campaign lies in reaching the right class of target audience and eventually convert them as potential customers in the future. Search engines like the Google, Yahoo, Bing are a few of the most used ones by the businesses to market their product. Apart from this, certain websites like the www.alibaba.com that has more traffic also offer services for B2B customers to set their advertisement campaign. The look of the advertisement, …

Classifying Classic Ciphers Using Machine Learning, Nivedhitha Ramarathnam Krishna

Master's Projects

We consider the problem of identifying the classic cipher that was used to generate a given ciphertext message. We assume that the plaintext is English and we restrict our attention to ciphertext consisting only of alphabetic characters. Among the classic ciphers considered are the simple substitution, Vigenère cipher, playfair cipher, and column transposition cipher. The problem of classification is approached in two ways. The first method uses support vector machines (SVM) trained directly on ciphertext to classify the ciphers. In the second approach, we train hidden Markov models (HMM) on each ciphertext message, then use these trained HMMs as features …

Smartphone Gesture-Based Authentication, Preethi Sundaravaradhan

Master's Projects

In this research, we consider the problem of authentication on a smartphone based on gestures, that is, movements of the phone. Accelerometer data from a number of subjects was collected and we analyze this data using a variety of machine learning techniques, including support vector machines (SVM) and convolutional neural networks (CNN). We analyze both the fraud rate (or false accept rate) and insult rate (or false reject rate) in each case.

Classification Of Malware Models, Akriti Sethi

Master's Projects

Automatically classifying similar malware families is a challenging problem. In this research, we attempt to classify malware families by applying machine learning to machine learning models. Specifically, we train hidden Markov models (HMM) for each malware family in our dataset. The resulting models are then compared in two ways. First, we treat the HMM matrices as images and experiment with convolutional neural networks (CNN) for image classification. Second, we apply support vector machines (SVM) to classify the HMMs. We analyze the results and discuss the relative advantages and disadvantages of each approach.

Machine Learning Versus Deep Learning For Malware Detection, Parth Jain

Master's Projects

It is often claimed that the primary advantage of deep learning is that such models can continue to learn as more data is available, provided that sufficient computing power is available for training. In contrast, for other forms of machine learning it is claimed that models ‘‘saturate,’’ in the sense that no additional learning can occur beyond some point, regardless of the amount of data or computing power available. In this research, we compare the accuracy of deep learning to other forms of machine learning for malware detection, as a function of the training dataset size. We experiment with a …

Deep Learning For Image Spam Detection, Tazmina Sharmin

Master's Projects

Spam can be defined as unsolicited bulk email. In an effort to evade text-based spam filters, spammers can embed their spam text in an image, which is referred to as image spam. In this research, we consider the problem of image spam detection, based on image analysis. We apply various machine learning and deep learning techniques to real-world image spam datasets, and to a challenge image spam-like dataset. We obtain results comparable to previous work for the real-world datasets, while our deep learning approach yields the best results to date for the challenge dataset.

Ai Dining Suggestion App, Bao Pham

Master's Projects

Trying to decide what to eat can sometimes be challenging and time-consuming for people. Google and Yelp have large scale data sets of restaurant information as well as Application Program Interfaces (APIs) for using them. This restaurant data includes time, price range, traffic, temperature, etc. The goal of this project is to build an app that eases the process of finding a restaurant to eat. This app has a Tinder-like user friendly User Interface (UI) design to change the common way that lists of restaurants are presented to users on mobile apps. It also uses the help of Artificial Intelligence …

Detection Of Hate Speech In Videos Using Machine Learning, Unnathi Bhandary

Master's Projects

With the progression of the internet and social media, people are given multiple platforms to share their thoughts and opinions about various subject matters freely. However, this freedom of speech is misused to direct hate towards individuals or group of people due to their race, religion, gender etc. The rise of hate speech has led to conflicts and cases of cyber bullying, causing many organizations to look for optimal solutions to solve this problem.

Developments in the field of machine learning and deep learning have piqued the interest of researchers, leading them to research and implement solutions to solve the …