Information Security Commons^™

A Neat Approach To Malware Classification, Jason Do

Master's Projects

Current malware detection software often relies on machine learning, which is seen as an improvement over signature-based techniques. Problems with a machine learning based approach can arise when malware writers modify their code with the intent to evade detection. This leads to a cat and mouse situation where new models must constantly be trained to detect new malware variants. In this research, we experiment with genetic algorithms as a means of evolving machine learning models to detect malware. Genetic algorithms, which simulate natural selection, provide a way for models to adapt to continuous changes in a malware families, and thereby …

Signature Identification And Verification Systems: A Comparative Study On The Online And Offline Techniques, Nehal Hamdy Al-Banhawy, Heba Mohsen, Neveen I. Ghali Prof.

Future Computing and Informatics Journal

Handwritten signature identification and verification has become an active area of research in recent years. Handwritten signature identification systems are used for identifying the user among all users enrolled in the system while handwritten signature verification systems are used for authenticating a user by comparing a specific signature with his signature that is stored in the system. This paper presents a review for commonly used methods for preprocessing, feature extraction and classification techniques in signature identification and verification systems, in addition to a comparison between the systems implemented in the literature for identification techniques and verification techniques in online and …

Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao

Articles

It is often the case with new technologies that it is very hard to predict their long-term impacts and as a result, although new technology may be beneficial in the short term, it can still cause problems in the longer term. This is what happened with oil by-products in different areas: the use of plastic as a disposable material did not take into account the hundreds of years necessary for its decomposition and its related long-term environmental damage. Data is said to be the new oil. The message to be conveyed is associated with its intrinsic value. But as in …

Malware Classification With Gaussian Mixture Model-Hidden Markov Models, Jing Zhao

Master's Projects

Discrete hidden Markov models (HMM) are often applied to the malware detection and classification problems. However, the continuous analog of discrete HMMs, that is, Gaussian mixture model-HMMs (GMM-HMM), are rarely considered in the field of cybersecurity. In this study, we apply GMM-HMMs to the malware classification problem and we compare our results to those obtained using discrete HMMs. As features, we consider opcode sequences and entropy-based sequences. For our opcode features, GMM-HMMs produce results that are comparable to those obtained using discrete HMMs, whereas for our entropy-based features, GMM-HMMs generally improve on the classification results that we can attain with …

Improving A Wireless Localization System Via Machine Learning Techniques And Security Protocols, Zachary Yorio

Masters Theses, 2020-current

The recent advancements made in Internet of Things (IoT) devices have brought forth new opportunities for technologies and systems to be integrated into our everyday life. In this work, we investigate how edge nodes can effectively utilize 802.11 wireless beacon frames being broadcast from pre-existing access points in a building to achieve room-level localization. We explain the needed hardware and software for this system and demonstrate a proof of concept with experimental data analysis. Improvements to localization accuracy are shown via machine learning by implementing the random forest algorithm. Using this algorithm, historical data can train the model and make …

Malware Classification Using Lstms, Dennis Dang

Master's Projects

Signature and anomaly based detection have long been quintessential techniques used in malware detection. However, these techniques have become increasingly ineffective as malware becomes more complex. Researchers have therefore turned to deep learning to construct better performing models. In this project, we create four different long-short term memory (LSTM) models and train each model to classify malware by family type. Our data consists of opcodes extracted from malware executables. We employ techniques used in natural language processing (NLP) such as word embedding and bidirection LSTMs (biLSTM). We also use convolutional neural networks (CNN). We found that our model consisting of …

Using Eye-Gaze To Evaluate Neural Attention, Shahansha Salim

Master’s Dissertations

The ability to selectively concentrate on areas of interest while ignoring the rest is termed as attention in human beings. This ability has played a key role in survival as well as information processing. Neural Attention is said to be an effort to bring similar action of selectively concentrating areas of relevance in deep neural networks. This simple yet powerful concept has attracted a lot of research in recent years, yielding breakthrough results in Natural Language Processing (NLP) problems and main stream Computer Vision problems such as Image Caption Generation, Neural Machine Translation (NMT), Visual Question Answering (VQA), Action Recognition, …

Thaw Publications, Carl Landwehr, David Kotz

Computer Science Technical Reports

In 2013, the National Science Foundation's Secure and Trustworthy Cyberspace program awarded a Frontier grant to a consortium of four institutions, led by Dartmouth College, to enable trustworthy cybersystems for health and wellness. As of this writing, the Trustworthy Health and Wellness (THaW) project's bibliography includes more than 130 significant publications produced with support from the THaW grant; these publications document the progress made on many fronts by the THaW research team. The collection includes dissertations, theses, journal papers, conference papers, workshop contributions and more. The bibliography is organized as a Zotero library, which provides ready access to citation materials …

On Improving The Memorability Of System-Assigned Recognition-Based Passwords, Mahdi Nasrullah Al-Ameen, Sonali T. Marne, Kanis Fatema, Matthew Wright, Shannon Scielzo

Computer Science Faculty and Staff Publications

User-chosen passwords reflecting common strategies and patterns ease memorization but offer uncertain and often weak security, while system-assigned passwords provide higher security guarantee but suffer from poor memorability. We thus examine the technique to enhance password memorability that incorporates a scientific understanding of long-term memory. In particular, we examine the efficacy of providing users with verbal cues—real-life facts corresponding to system-assigned keywords. We also explore the usability gain of including images related to the keywords along with verbal cues. In our multi-session lab study with 52 participants, textual recognition-based scheme offering verbal cues had a significantly higher login success …

Narrowing The Wealth And Income Gap In Poland, China, And The United States, Cyndy Carboo, Zhiling Song, Jiawei Feng, Xudong Zhu

School of Professional Studies

With the widespread of globalization, the wealth gap continues to widen globally. Due to the enormous differences in national conditions and political systems of various countries, this article selects China, the United States, and Poland as the research objects, and uses a specific time unit as the benchmark, and mainly focuses on the four directions of medical care, education, job opportunities, and pensions. A reader could understand the correlation between the wealth gap and multiple factors deeply in this article. This article analyzes the impact of income disparity on these three countries and proposes solutions to help narrow the gap …

Worst Time Being Poor? The Hunger Problem In U.S. During Covid-19 Pandemic, Yuanhang Hu

School of Professional Studies

Food insecurity is deeply rooted in American society during and before the COVID-19 pandemic. Food Insecurity usually associates with economic indicators, such as unemployment rate, income level, etc. Currently, there are two main tools to fight the war of hunger. The first one is the government food assistance programs. And the second one is food pantries from the private sectors of the community. Both tools are facing numerous challenges due to COVID-19. The purpose of this article is to provide rational reasons to persuade the government to enhance the benefits of the Supplemental Nutrition Assistance Program (SNAP) and use administrative …

The Practical Applications Of Video Games Beyond Entertainment, Jack Martin

School of Professional Studies

Much of the attention directed toward video games is focused on their role as entertainment. However, researchers have found that video games can have other, more practical uses for society. This thesis is designed to examine three specific examples of the practical applications of video games: video games in education, video games as accessible technology, and the social uses of video games. This project is based on pre-existing research conducted by professionals studying the aforementioned subtopics. Anecdotal stories from educators, people with disabilities, and developers are also discussed. The thesis explores specific examples of video games being used practically, and …

Transparency And Yielding Of Law Officers Reform (Taylor) Act Of 2020: Proposal For Police Reform, Marwa Alnaal, Matthew L. Anderson, Hannah Brier, Mollie Campbell, Rose Wine

School of Professional Studies

The Transparency and Yielding of Law Officers Reform Act of 2020 (TAYLOR) proposes an example bill for law enforcement reform. During the summer of 2020, the United States witnessed civilian demonstrations nationwide calling for a change to policing. Our proposal is hoping to heed that call, offering a foundation for change that police forces and localities across the United States can utilize to rebuild trust and accountability.

The goal of the TAYLOR Act is not to defund the police; but rather, TAYLOR rethinks the priorities of the police. There can be no denying that the relationship of trust and security …

How Museum Utilize Social Media On Communication, Jiake Han

School of Professional Studies

With the development of Internet, social media became more and more popular among people. Many industries realize the importance of social media in business. Traditionally, museum concentrates more on personal visual experience, which is hard to be replaced by online media. However, museums now also put more concentrate on social media platform because it expands the way of engagement. Especially, for Coronavirus, many organizations including museums have to close. Therefore, museums have to depend more on social media platforms to communicate with audiences. This research aims at finding how different kind of social media help museum communicate and engage with …

Healthy Food Portal Business Plan And Its Function Model, Alena Raupova

School of Professional Studies

Business planning is a tool of paramount importance in the process of company management, on the efficiency of which the future functioning of the enterprise depends. Formation of a business plan enables the team to productively and competently use existing funds and resources in their work and apply planning as a very effective management mechanism (Hamm, 2016).

The goal of this final project is to develop a business plan for a healthy nutrition portal for Bellyful LLC. Bellyful is based in Boston, USA, and the portal will be its first product. Our client is interested in researching the prospects of …

A Web-Based Ai Assistant Application Using Python And Javascript, Viet Le, Tej Bahadur, Jainee Shah, Roushan Ara

School of Professional Studies

Our research is mainly based on a chatbot which is powered by Artificial Intelligence. Nowadays, Artificial Intelligence assistants such as Apple’s Siri, Google’s Now and Amazon’s Alexa are currently fast-growing and widely integrated with many smart devices. These assistants are built with the primary purpose of being personal assistants for every individual user in certain contexts. In this research, we would highlight the development process of the chatbots, features, problems, case studies and limitations.

This research delivers the information, helps developers to build answer bots and integrate chatbots with business accounts. The aim is to assist users and allow transactions …

Rcap Solutions Breach Management - Case Study, Eugene Adu-Gyamfi, Gio Al Muarrawi, Kwame Ofori

School of Professional Studies

Companies get hacked every day, and our in-scope company for this case study, RCAP Solution, was not an exception. Security incidents have increased both in volume and range in recent years, and cyber-attacks have become more sophisticated than ever before. There are so many reasons that drive this fact; one is that our infrastructure was not protected efficiently, but also attackers have become more knowledgeable in initiating advanced attacks at a scale. Additionally, the entrance of emerging technologies such as blockchain, machine learning, and the internet of things, added additional complexity to the already complex scene. Cybercriminals are using various …

Cvs Covid-19 Screening Website: Test Automation, Savya Rawat

School of Professional Studies

CVS Pharmacy is an American retail corporation, also known as, and originally named, the Consumer Value Store owned by CVS Health, it is headquartered in Woonsocket, Rhode Island. CVS Pharmacy is currently the largest pharmacy chain in the United States by number of locations over 9,600 and total prescription revenue. CVS sells prescription drugs and a wide assortment of general merchandise, including over-the-counter drugs.

Now, coming to the reason why I have selected CVS pharmacy’s website cvs.com as my case study topic is because of CVS’s response to the covid-19 pandemic’s no-cost testing strategy. Whole of the world is suffering …

The Impact Of Special Interest Groups On The Federal Dietary Guidelines: Consequences For American Health, Dory Mcmillan

School of Professional Studies

This research paper explores the impact of relationships between lobbyists and both the USDA and HSS, and the impact these relationships have on the Dietary Guidelines for Americans that the agencies work together to create. The paper focuses specifically on the information the guidelines present in regard to red meat consumption, and the impacts this may have on American health, and healthcare costs associated. It was hypothesized that a relationship would be found between special interest groups and the U.S. Department of Health and Human Services and/or the U.S. Department of Agriculture. Research found there was a relationship between special …

The Killingly Mascot Case Study, Jordan Lumpkins

School of Professional Studies

In the summer of 2019, in Killingly, Connecticut the local Board of Education voted to retire the "Redmen" mascot name it had used for nearly a century. This legislation was widely opposed and received extensive media coverage. Within a few months, the town experienced a massive political referendum where several local Board of Education members and Councilmen were replaced by single issue politicians promising to reinstate the "Redmen" name. Now holding a majority on the Board of Education, these Board members made Killingly the first school in U.S. history to reinstate a mascot after being deemed "derogatory."

It is the …

Higher Education Responses To Crisis: A Case Study Of Clark University And The Pandemic Of 2020, Lisa Gillingham

School of Professional Studies

The COVID-19 pandemic has delivered an existential challenge to universities and other academic institutions at a time when they are already grappling with other weighty issues that may alter the fabric of higher education. COVID-19 has forced these institutions to consider and employ new ways of conducting its work with a sense urgency that is unprecedented in the recent history of the academy. The rate of learning around these models is rapid, and Higher Education is ripe for change.

Clark University has addressed the pandemic with a plan to protect and pivot using strategies that support the continuation of its …

Internet Of Things (Iot): Cybersecurity Risks In Healthcare, Ruhi Patel

Cybersecurity Undergraduate Research Showcase

The rapid growth and investment in the Internet of Things (IoT) has significantly impacted how individuals and industries operate. The Internet of Things (IoT) refers to a network of physical, technology-embedded objects that communicate, detect, and interact with their external environment or internal state (Hung, 2017). According to Tankovska (2020), IoT devices are estimated to reach 21.5 billion units by 2025. This technological boom is leading various industrial sectors to notice a quick increase in cybersecurity risks and threats. One industrial sector has been particularly vulnerable to numerous cyber threats across the globe: healthcare. Oliver Noble (2020), a data encryption …

Confronting Wicked Crypto: Wicked Problems, Encryption Policy, And Exceptional Access Technology, Kevin Nicholas Kredit

Masters Theses

Public debate has resumed on the topic of exceptional access (EA), which refers to alternative means of decryption intended for law enforcement use. The resumption of this debate is not a renege on a resolute promise made at the end of the 1990s “crypto war”; rather, it represents a valid reassessment of optimal policy in light of changing circumstances. The imbalance between privacy, access, and security in the context of constantly changing society and technology is a wicked problem that has and will continue to evade a permanent solution. As policymakers consider next steps, it is necessary that the technical …

Politeness In Security Directives: Insights In Browser Compliance For The Human Element, Deanna House, Gabe Giordano

Information Systems and Quantitative Analysis Faculty Publications

The technical protection provided by information security technology is necessary as a frontline defense against threats. However, the human element adds great risk to systems and cannot be ignored. This research explores the human elements related to security communications and intention to comply with security directives. Security communications are more-commonly being sent using richer computer-based channels. While the goal of security communications is the gain compliance, there is still much to learn related to what influences a user to comply. This research explores the effects that (im)politeness has on intention to comply with security directives. The research utilized an experiment …

Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …

In-Depth Analysis Of College Students’ Data Privacy Awareness, Vernon D. Andrews

Theses and Dissertations

While attending university, college students need to be aware of issues related to data privacy. Regardless of the age, gender, race, or education level of college students, every student can relate to the advancement of the internet within the last decades. The internet has completely transformed the way the world receives and stores messages. Positively, the internet allows messages to be sent across the globe within the fraction of a second and provides students with access to potentially unlimited information on a variety of subjects. On the downside, there are issues on the internet that can cause more harm than …

Lightweight Deep Learning For Botnet Ddos Detection On Iot Access Networks, Eric A. Mccullough

Graduate Theses/Dissertations

With the proliferation of the Internet of Things (IoT), computer networks have rapidly expanded in size. While Internet of Things Devices (IoTDs) benefit many aspects of life, these devices also introduce security risks in the form of vulnerabilities which give hackers billions of promising new targets. For example, botnets have exploited the security flaws common with IoTDs to gain unauthorized control of hundreds of thousands of hosts, which they then utilize to carry out massively disruptive distributed denial of service (DDoS) attacks. Traditional DDoS defense mechanisms rely on detecting attacks at their target and deploying mitigation strategies toward the attacker …

Driving Cybersecurity Policy Insights From Information On The Internet, Qiu-Hong Wang, Steven Mark Miller, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cybersecurity policy analytics quantitatively evaluates the effectiveness of cybersecurity protection measures consisting of both technical and managerial countermeasures and is inherently interdisciplinary work, drawing on the concepts and methods from economics, business, social science, and law.

Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu

Research Collection School Of Computing and Information Systems

Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only …

Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu

Research Collection School Of Computing and Information Systems

Graphics Processing Units (GPUs) are now playing a vital role in many devices and systems including computing devices, data centers, and clouds, making them the next target of side-channel attacks. Unlike those targeting CPUs, existing side-channel attacks on GPUs exploited vulnerabilities exposed by application interfaces like OpenGL and CUDA, which can be easily mitigated with software patches. In this paper, we investigate the lower-level and native interface between GPUs and CPUs, i.e., the graphics interrupts, and evaluate the side channel they expose. Being an intrinsic profile in the communication between a GPU and a CPU, the pattern of graphics interrupts …