Information Security Commons^™

Determining Knowledge From Student Performance Prediction Using Machine Learning, Wala El Rashied Mohamed

Theses

Recent years have seen a rapid development in the field of educational data mining (EDM), enhancing the ability to trace student knowledge. Data from intelligent tutoring systems (ITS) have been analyzed and interpreted by multiple researchers seeking to measure students’ knowledge as it evolves. Human nature, as well as other factors, makes it difficult to determine whether or not students are knowledgeable. This thesis sets out to examine the level of students’ knowledge by predicting their current and future academic performance based on records of their historical interactions. By restructuring data and considering a student perspective, we can gain insight …

A Multi-Criteria Decision-Making (Mcdm) Approach For Data-Driven Distance Learning Recommendations, Aysha Meshaal Alshamsi

Theses

Distance learning has been adopted as an alternative learning strategy to the dominant face-to-face teaching methodology. It has been largely implemented by many governments worldwide due to the spread of the COVID-19 pandemic and the implication in enforcing lockdown and social distancing. In emergency situations distance learning is referred to as Emergency Remote Teaching (ERT). Due to this dynamic, sudden shift, and scaling demand in distance learning, many challenges have been accentuated. These include technological adoption, student commitments, parent involvement, and teacher extra burden management, changes in the organization methodology, in addition to government development of new guidelines and regulations …

Gauging The Acceptance Of Contact Tracing Technology: An Empirical Study Of Singapore Residents’ Concerns With Sharing Their Information And Willingness To Trust, Ee-Ing Ong, Wee Ling Loo

Research Collection Yong Pung How School Of Law

In response to the COVID-19 pandemic, governments began implementing various forms of contact tracing technology. Singapore’s implementation of its contact tracing technology, TraceTogether, however, was met with significant concern by its population, with regard to privacy and data security. This concern did not fit with the general perception that Singaporeans have a high level of trust in its government. We explore this disconnect, using responses to our survey (conducted pre-COVID-19) in which we asked participants about their level of concern with the government and business collecting certain categories of personal data. The results show that respondents had less concern with …

Shunted Self-Attention Via Multi-Scale Token Aggregation, Sucheng Ren, Daquan Zhou, Shengfeng He, Jiashi Feng, Xinchao Wang

Research Collection School Of Computing and Information Systems

Recent Vision Transformer (ViT) models have demonstrated encouraging results across various computer vision tasks, thanks to its competence in modeling long-range dependencies of image patches or tokens via self-attention. These models, however, usually designate the similar receptive fields of each token feature within each layer. Such a constraint inevitably limits the ability of each self-attention layer in capturing multi-scale features, thereby leading to performance degradation in handling images with multiple objects of different scales. To address this issue, we propose a novel and generic strategy, termed shunted selfattention (SSA), that allows ViTs to model the attentions at hybrid scales per …

Information Provenance For Mobile Health Data, Taylor A. Hardin

Dartmouth College Ph.D Dissertations

Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained intact---especially …

Small Business Cybersecurity: A Loophole To Consumer Data, Matthew R. Espinosa

The Scholar: St. Mary's Law Review on Race and Social Justice

Small businesses and small minority owned businesses are vital to our nation’s economy; therefore legislation, regulation, and policy has been created in order to assist them in overcoming their economic stability issues and ensure they continue to serve the communities that rely on them. However, there is not a focus on regulating nor assisting small businesses to ensure their cybersecurity standards are up to par despite them increasingly becoming a victim of cyberattacks that yield high consequences. The external oversight and assistance is necessary for small businesses due to their lack of knowledge in implementing effective cybersecurity policies, the fiscal …

Active Learning With Cybersecurity, Carole Shook

TFSC Publications and Presentations

A global campus grant was obtained in Spring 2020 to develop modules for Cybersecurity. This presentation encompasses the use of Cyberciege and case studies that require active learning of students.

Privacy Assessment Breakthrough: A Design Science Approach To Creating A Unified Methodology, Lisa Mckee

Masters Theses & Doctoral Dissertations

Recent changes have increased the need for and awareness of privacy assessments. Organizations focus primarily on Privacy Impact Assessments (PIA) and Data Protection Impact Assessments (DPIA) but rarely take a comprehensive approach to assessments or integrate the results into a privacy risk program. There are numerous industry standards and regulations for privacy assessments, but the industry lacks a simple unified methodology with steps to perform privacy assessments. The objectives of this research project are to create a new privacy assessment methodology model using the design science methodology, update industry standards and present training for conducting privacy assessments that can be …

Protecting Systems From Exploits Using Language-Theoretic Security, Prashant Anantharaman

Dartmouth College Ph.D Dissertations

Any computer program processing input from the user or network must validate the input. Input-handling vulnerabilities occur in programs when the software component responsible for filtering malicious input---the parser---does not perform validation adequately. Consequently, parsers are among the most targeted components since they defend the rest of the program from malicious input. This thesis adopts the Language-Theoretic Security (LangSec) principle to understand what tools and research are needed to prevent exploits that target parsers. LangSec proposes specifying the syntactic structure of the input format as a formal grammar. We then build a recognizer for this formal grammar to validate any …

Establishing Trust In Vehicle-To-Vehicle Coordination: A Sensor Fusion Approach, Jakob Veselsky, Jack West, Isaac Ahlgren, George K. Thiruvathukal, Neil Klingensmith, Abhinav Goel, Wenxin Jiang, James C. Davis, Kyuin Lee, Younghyun Kim

Computer Science: Faculty Publications and Other Works

Autonomous vehicles (AVs) use diverse sensors to understand their surroundings as they continually make safety- critical decisions. However, establishing trust with other AVs is a key prerequisite because safety-critical decisions cannot be made based on data shared from untrusted sources. Existing protocols require an infrastructure network connection and a third-party root of trust to establish a secure channel, which are not always available.

In this paper, we propose a sensor-fusion approach for mobile trust establishment, which combines GPS and visual data. The combined data forms evidence that one vehicle is nearby another, which is a strong indication that it is …

An Evaluation Of Security In Blockchain-Based Sharing Of Student Records In Higher Education, Timothy Arndt, Angela Guercio, Yonghun Chae

Information Systems

Blockchain has recently taken off as a disruptive technology, from its initial use in cryptocurrencies to wider applications in areas such as property registration and insurance due to its characteristic as a distributed ledger which can remove the need for a trusted third party to facilitate transactions. This spread of the technology to new application areas has been driven by the development of smart contracts – blockchain-based protocols which can automatically enforce a contract by executing code based on the logic expressed in the contract. One exciting area for blockchain is higher education. Students in higher education are ever more …

Demonstration Of Cyberattacks And Mitigation Of Vulnerabilities In A Webserver Interface For A Cybersecure Power Router, Benjamin Allen

Computer Science and Computer Engineering Undergraduate Honors Theses

Cyberattacks are a threat to critical infrastructure, which must be secured against them to ensure continued operation. A defense-in-depth approach is necessary to secure all layers of a smart-grid system and contain the impact of any exploited vulnerabilities. In this undergraduate thesis a webserver interface for smart-grid devices communicating over Modbus TCP was developed and exposed to SQL Injection attacks and Cross-Site Scripting attacks. Analysis was performed on Supply-Chain attacks and a mitigation developed for attacks stemming from compromised Content Delivery Networks. All attempted attacks were unable to exploit vulnerabilities in the webserver due to its use of input sanitization …

Analysis Of Gpu Memory Vulnerabilities, Jarrett Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Graphics processing units (GPUs) have become a widely used technology for various purposes. While their intended use is accelerating graphics rendering, their parallel computing capabilities have expanded their use into other areas. They are used in computer gaming, deep learning for artificial intelligence and mining cryptocurrencies. Their rise in popularity led to research involving several security aspects, including this paper’s focus, memory vulnerabilities. Research documented many vulnerabilities, including GPUs not implementing address space layout randomization, not zeroing out memory after deallocation, and not initializing newly allocated memory. These vulnerabilities can lead to a victim’s sensitive data being leaked to an …

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …

Canary: An Automated Approach To Security Scanning And Remediation, David Wiles

Masters Theses & Specialist Projects

Modern software has a smaller attack surface today than in the past. Memory-safe languages, container runtimes, virtual machines, and a mature web stack all contribute to the relative safety of the web and software in general compared to years ago. Despite this, we still see high-profile bugs, hacks, and outages which affect major companies and widely-used technologies. The extensive work that has gone into hardening virtualization, containerization, and commonly used applications such as Nginx still depends on the end-user to configure correctly to prevent a compromised machine.

In this paper, I introduce a tool, which I call Canary, which can …

Side-Channel Analysis On Post-Quantum Cryptography Algorithms, Tristen Teague

Computer Science and Computer Engineering Undergraduate Honors Theses

The advancements of quantum computers brings us closer to the threat of our current asymmetric cryptography algorithms being broken by Shor's Algorithm. NIST proposed a standardization effort in creating a new class of asymmetric cryptography named Post-Quantum Cryptography (PQC). These new algorithms will be resistant against both classical computers and sufficiently powerful quantum computers. Although the new algorithms seem mathematically secure, they can possibly be broken by a class of attacks known as side-channels attacks (SCA). Side-channel attacks involve exploiting the hardware that the algorithm runs on to figure out secret values that could break the security of the system. …

Ransomware And Malware Sandboxing, Byron Denham

Computer Science and Computer Engineering Undergraduate Honors Theses

The threat of ransomware that encrypts data on a device and asks for payment to decrypt the data affects individual users, businesses, and vital systems including healthcare. This threat has become increasingly more prevalent in the past few years. To understand ransomware through malware analysis, care must be taken to sandbox the ransomware in an environment that allows for a detailed and comprehensive analysis while also preventing it from being able to further spread. Modern malware often takes measures to detect whether it has been placed into an analysis environment to prevent examination. In this work, several notable pieces of …

Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Network Intrusion Detection Systems (NIDS) are one layer of defense that can be used to protect a network from cyber-attacks. They monitor a network for any malicious activity and send alerts if suspicious traffic is detected. Two of the most common open-source NIDS are Snort and Suricata. Snort was first released in 1999 and became the industry standard. The one major drawback of Snort has been its single-threaded architecture. Because of this, Suricata was released in 2009 and uses a multithreaded architecture. Snort released Snort 3 last year with major improvements from earlier versions, including implementing a new multithreaded architecture …

An Application Of Machine Learning To Analysis Of Packed Mac Malware, Kimo Bumanglag

Masters Theses & Doctoral Dissertations

The macOS operating system is increasingly targeted by malware. Software written for macOS, both benign and malicious, is in the Mach-O executable format. Malware authors may frustrate analysts through obfuscation methods such as packing. The field of malware research on Windows is well-established but is less so on the macOS platform. Thus far, no research has been identified that studies how machine learning can be used to detected packed Mach-O malware. This research applies supervised machine learning techniques to the classification of packed Mach-O malware. This research will answer three research questions. First, whether machine learning can classify packed Mach-O …

Probabilistic Path Prioritization For Hybrid Fuzzing, Lei Zhao, Pengcheng Cao, Yue Duan, Heng Yin, Jifeng Xuan

Research Collection School Of Computing and Information Systems

Hybrid fuzzing that combines fuzzing and concolic execution has become an advanced technique for software vulnerability detection. Based on the observation that fuzzing and concolic execution are complementary in nature, state-of-the-art hybrid fuzzing systems deploy “optimal concolic testing” and “demand launch” strategies. Although these ideas sound intriguing, we point out several fundamental limitations in them, due to unrealistic or oversimplified assumptions. Further, we propose a novel “discriminative dispatch” strategy and design a probabilistic hybrid fuzzing system to better utilize the capability of concolic execution. Specifically, we design a Monte Carlo-based probabilistic path prioritization model to quantify each path’s difficulty, and …