Information Security Commons^™

Efficient Privacy-Preserving Spatial Range Query Over Outsourced Encrypted Data, Yinbin Miao, Yutao Yang, Xinghua Li, Zhiquan Liu, Hongwei Li, Kim-Kwang Raymond Choo, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid development of Location-Based Services (LBS), a large number of LBS providers outsource spatial data to cloud servers to reduce their high computational and storage burdens, but meanwhile incur some security issues such as location privacy leakage. Thus, extensive privacy-preserving LBS schemes have been proposed. However, the existing solutions using Bloom filter do not take into account the redundant bits that do not map information in Bloom filter, resulting in high computational overheads, and reveal the inclusion relationship in Bloom filter. To solve these issues, we propose an efficient Privacy-preserving Spatial Range Query (PSRQ) scheme by skillfully combining …

Distpreserv: Maintaining User Distribution For Privacy-Preserving Location-Based Services, Yanbing Ren, Xinghua Li, Yinbin Miao, Robert H. Deng, Jian Weng, Siqi Ma, Jianfeng Ma

Research Collection School Of Computing and Information Systems

Location-Based Services (LBSs) are one of the most frequently used mobile applications in the modern society. Geo-Indistinguishability (Geo-Ind) is a promising privacy protection model for LBSs since it can provide formal security guarantees for location privacy. However, Geo-Ind undermines the statistical location distribution of users on the LBS server because of perturbed locations, thereby disabling the server to provide distribution-based services (e.g., traffic congestion maps). To overcome this issue, we give a privacy definition, called DistPreserv, to enable the LBS server to acquire valid location distributions while providing users with strict location protection. Then we propose a privacy-preserving LBS scheme …

Trustworthy Machine Learning Through The Lens Of Privacy And Security, Thi Kim Phung Lai

Dissertations

Nowadays, machine learning (ML) becomes ubiquitous and it is transforming society. However, there are still many incidents caused by ML-based systems when ML is deployed in real-world scenarios. Therefore, to allow wide adoption of ML in the real world, especially in critical applications such as healthcare, finance, etc., it is crucial to develop ML models that are not only accurate but also trustworthy (e.g., explainable, privacy-preserving, secure, and robust). Achieving trustworthy ML with different machine learning paradigms (e.g., deep learning, centralized learning, federated learning, etc.), and application domains (e.g., computer vision, natural language, human study, malware systems, etc.) is challenging, …

What Effects Do Large Language Models Have On Cybersecurity, Josiah Marshall

Cybersecurity Undergraduate Research Showcase

Large Language Models (LLMs) are artificial intelligence (AI) tools that can process, summarize, and translate texts and predict future words in a sentence, letting the LLM generate sentences similar to how humans talk and write. One concern that needs to be flagged is that, often, the content generated by different LLMs is inaccurate. LLMs are trained on code that can be used to detect data breaches, detect ransomware, and even pinpoint organizational vulnerabilities in advance of a cyberattack. LLMs are new but have unbelievable potential with their ability to generate code that brings awareness to cyber analysts and IT professionals. …

Hacker, Influencer, Counter-Culture Spy: Cyberspace Actors’ Models Of Misinformation And Counter-Operations, Benjamin Kessell

College of Computing and Digital Media Dissertations

As misinformation continues to spread on social media, its residents have begun to fight back, independent of any platform. This organic resistance to the diffusion of misinformation is a clearly observable phenomenon with roots in Anonymous’ distributed campaigns from the 2010s outwards. Hacker and information security communities are acting in defense of some of their favorite spaces, most notably, Twitter. Security researchers of all stripes use it for sharing indicators of compromise but, as the diffusion of misinformation becomes more problematic it becomes more difficult to find signals in the noise.

These actors’ response to the issues at hand is …

Human And Technical Factors In The Adoption Of Quantum Cryptographic Algorithms, Alyssa Pinkston

Mathematical Sciences Technical Reports (MSTR)

The purpose of this research is to understand what factors would cause users to choose quantum key distribution (QKD) over other methods of cryptography. An Advanced Encryption Standard (AES) key can be exchanged through communication using the Rivest, Shamir, Adleman (RSA) cryptographic algorithm, QKD, or post-quantum cryptography (PQC). QKD relies on quantum physics where RSA and PQC use complex mathematics to encrypt data. The BB84 quantum cryptographic protocol involves communication over a quantum channel and a public channel. The quantum channel can be technically attacked by beamsplitting or intercept/resend. QKD, like other forms of cryptography, is vulnerable to social attacks …

An Empirical Study Of Pre-Trained Model Reuse In The Hugging Face Deep Learning Model Registry, Wenxin Jiang, Nicholas Synovic, Matt Hyattt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hisang Lu, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional software engineering, machine learning engineers have begun to reuse large-scale pre-trained models (PTMs) and fine-tune these models for downstream tasks. Prior works have studied reuse practices for traditional software packages to guide software engineers towards better package maintenance and dependency management. We lack a similar foundation of knowledge to guide behaviors in pre-trained model ecosystems.

In this work, we present the first empirical investigation of PTM reuse. …

An Analysis And Examination Of Consensus Attacks In Blockchain Networks, Thomas R. Clark

Senior Honors Projects, 2020-current

This paper examines consensus attacks as they relate to blockchain networks. Consensus attacks are a significant threat to the security and integrity of blockchain networks, and understanding these attacks is crucial for developers and stakeholders. The primary contribution of the paper is to present blockchain and consensus attacks in a clear and accessible manner, with the aim of making these complex concepts easily understandable for a general audience. Using literature review, the paper identifies various methods to prevent consensus attacks, including multi-chain networks, proof-of-work consensus algorithms, and network auditing and monitoring. An analysis revealed that these methods for preventing consensus …

An Analysis Of Text-Based Machine Learning Models For Vulnerability Detection, Kollin Ryne Napier

Theses and Dissertations

With an increase in complexity of software, developers rely more on reuse and dependencies in their source code via code snippets. As a result, it is becoming harder to identify and mitigate vulnerabilities. Although traditional analysis tools are still utilized, machine learning models are being adopted to expand efforts and combat such threats. Given the possibilities towards usage of such models, research in this area has introduced various approaches which vary in usability and prediction. In generalizing models to a more natural language approach, researchers have opted to train models on source code to identify existing and potential vulnerabilities. Exploratory …

Making The Transition To Post-Quantum Cryptography, J. Simon Richard

The Downtown Review: An Interdisciplinary Journal Written and Peer-Reviewed by Mandel Honors College Students at Cleveland State University

Without intervention, quantum computing could threaten the security of a large portion of our internet in the near future. However, solutions exist. This paper, which is intended for a general audience, provides a wider context for our current state of quantum-preparedness amid the transition from classical cryptosystems to post-quantum cryptosystems—cryptographic algorithms that can resist the attacks of quantum computers. It will also submit a possible way forward inspired by the actions taken around the globe to prevent the millennium (or Y2K) bug.

Du Undergraduate Showcase: Research, Scholarship, And Creative Works, Caitlyn Aldersea, Justin Bravo, Sam Allen, Anna Block, Connor Block, Emma Buechler, Maria De Los Angeles Bustillos, Arianna Carlson, William Christensen, Olivia Kachulis, Noah Craver, Kate Dillon, Muskan Fatima, Angel Fernandes, Emma Finch, Colleen Cassidy, Amy Fishman, Andrea Francis, Stacia Fritz, Simran Gill, Emma Gries, Rylie Hansen, Shannon Powers, Jacqueline Martinez, Zachary Harker, Ashley Hasty, Mykaela Tanino-Springsteen, Kathleen Hopps, Adelaide Kerenick, Colin Kleckner, Ci Koehring, Elijah Kruger, Braden Krumholz, Maddie Leake, Lyneé Alves, Seraphina Loukas, Yatzari Lozano Vazquez, Haley Maki, Emily Martinez, Sierra Mckinney, Audrey Mitchell, Kipling Newman, Audrey Ng, Megan Lucyshyn, Andrew Nguyen, Stevie Ostman, Casandra Pearson, Alexandra Penney, Julia Gielczynski, Tyler Ball, Anna Rini, Christina Rorres, Simon Ruland, Helayna Schafer, Emma Sellers, Sarah Schuller, Claire Shaver, Kevin Summers, Isabella Shaw, Madison Sinar, Claudia Pena, Apshara Siwakoti, Carter Sorensen, Madi Sousa, Anna Sparling, Alexandra Revier, Brandon Thierry, Dylan Tyree, Maggie Williams, Lauren Wols

DU Undergraduate Research Journal Archive

DU Undergraduate Showcase: Research, Scholarship, and Creative Works

Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii

Electronic Theses and Dissertations

This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.

Digital Dna: The Ethical Implications Of Big Data As The World’S New-Age Commodity, Clark H. Dotson

Honors Theses

In the emerging digital world that we find ourselves in, it becomes apparent that data collection has become a staple of daily life, whether we like it or not. This research discussion aims to bring light to just how much one’s own digital identity is valued in the technologically-infused world of today, with distinct research and local examples to bring awareness to the ethical implications of your online presence. The paper in question examines anecdotal and research evidence of the collection of data, both through true and unjust means, as well as ethical implications of what this information truly represents. …

What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer

Military Cyber Affairs

On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.

Combining Frameworks To Improve Military Health System Quality And Cybersecurity, Dr. Maureen L. Schafer, Dr. Joseph H. Schafer

Military Cyber Affairs

Existing conceptual frameworks and commercially available technology could be considered to rapidly operationalize the use of Quality Measures (QM) within military health systems (Costantino et al. 2020). Purchased healthcare as well as digital healthcare services have paved the way for data collection from multiple information systems thus offering stakeholders actionable intelligence to both guide and measure healthcare outcomes. However, the collection of data secondary to Smart Devices, disparate information systems, cloud services, and the Internet of Medical Things (IOMT) is a complication for security experts that also affect clients, stakeholders, organizations, and businesses delivering patient care. We have combined three …

A Survey And Comparative Study On Vulnerability Scanning Tools, Cassidy Khounborine

Computer Science and Computer Engineering Undergraduate Honors Theses

Vulnerability scanners are a tool used by many organizations and developers as part of their vulnerability management. These scanners aid in the security of applications, databases, networks, etc. There are many different options available for vulnerability scanners that vary in the analysis method they encompass or target for which they scan, among many other features. This thesis explores the different types of scanners available and aims to ease the burden of selecting the ideal vulnerability scanner for one’s needs by conducting a survey and comparative analysis of vulnerability scanners. Before diving into the vulnerability scanners available, background information is provided …

Linux Malware Obfuscation, Brian Roden

Computer Science and Computer Engineering Undergraduate Honors Theses

Many forms of malicious software use techniques and tools that make it harder for their functionality to be parsed, both by antivirus software and reverse-engineering methods. Historically, the vast majority of malware has been written for the Windows operating system due to its large user base. As such, most efforts made for malware detection and analysis have been performed on that platform. However, in recent years, we have seen an increase in malware targeting servers running Linux and other Unix-like operating systems resulting in more emphasis of malware research on these platforms. In this work, several obfuscation techniques for Linux …

Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge

Computer Science and Computer Engineering Undergraduate Honors Theses

Post-quantum cryptography is a necessary countermeasure to protect against attacks from quantum computer. However, the post-quantum cryptography schemes are potentially vulnerable to side channel attacks. One such method of attacking involves creating bit-flips in victim memory through a process called Rowhammer. These attacks can vary in nature, but can involve rowhammering bits to raise the encryption scheme's decryption failure rate, or modifying the scheme's random seed. With a high enough decryption failure rate, it becomes feasible to generate sufficient information about the secret key to perform a key recovery attack. This thesis proposed two attacks on proposed post-quantum cryptography algorithms, …

Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield

Computer Science and Computer Engineering Undergraduate Honors Theses

As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …