Information Security Commons^™

Prompt Engineering For Genai In Cybersecurity Incident Response: A Multi-Platform Evaluation Based On Nice Pr-Ir-001, Yuanyuan Liu

Journal of Cybersecurity Education, Research and Practice

This study explores the application of prompt engineering in cybersecurity education, mainly by evaluating the performance of different generative artificial intelligence (GenAI) platforms when performing tasks consistent with the NICE framework role pr-ir-001 - Network Defense Incident Responder. The study employed structured prompts designed for a medical technology environment compliant with HIPAA and NIST SP 800-53, while the tasks of the three GenAI models (GPT-4, Gemini, and DeepSeek) were to generate event response scenarios. Their outputs will be evaluated from four aspects: accuracy, relevance, clarity and completeness.

The results show that the three models differ in depth and consistency, but …

Static Malware Analysis For Incident Response: Developing A Tactical Aid With Ember, Joel Meoak, Shengjie Xu

Journal of Cybersecurity Education, Research and Practice

Incident responders face a variety of challenges when identifying malware using existing solutions, particularly when rapid tactical decisions are needed. Traditional malware detection methods are often signature-based, limiting their effectiveness to previously known threats detected by anti-virus (AV) engines. Online analysis tools introduce confidentiality risks, potentially alerting adversaries that their actions are under scrutiny. While free sandbox environments offer useful capabilities, they often require substantial setup time and hardware resources that may not be available in the field. This research leverages the Elastic Malware Benchmark for Empowering Researchers (EMBER) dataset to develop a lightweight, portable tactical decision aid that enables …

Conditional Attribute-Based Pre: Definition And Construction From Lwe, Lisha Yao, Jian Weng, Pengfei Wu, Guofeng Tang, Guomin Yang, Haiyang Xue, Robert H. Deng

Research Collection School Of Computing and Information Systems

Attribute-based proxy re-encryption (AB-PRE) is a crucial variant of proxy re-encryption. It allows a proxy with a re-encryption key to transform a delegator’s ciphertext associated with an access policy into another ciphertext associated with a new access policy, enabling delegatees with matching attributes to decrypt the transformed ciphertext. However, a key limitation of AB-PRE is that the delegator cannot control which ciphertexts are transformed. As a result, the proxy, once given the re-encryption key, indiscriminately transforms all ciphertexts, effectively switching their underlying policies—an issue known as the all-or-nothing problem. It limits the system’s flexibility and practicality in real-world use cases.In …

Ivycross: A Privacy-Preserving And Concurrency Control Framework For Blockchain Interoperability, Ming Li, Jian Weng, Jia-Si Weng, Yi Li, Yongdong Wu, Dingcheng Li, Guowen Xu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Interoperability is a fundamental challenge for long-envisioned blockchain applications. A mainstream approach is using Trusted Execution Environment (TEE) to support interoperable off-chain execution. However, this incurs multiple TEE configured with non-trivial storage capabilities running on fragile concurrent processing environments, rendering current strategies based on TEE far from being practical. This paper aims to fill this gap and design a practical interoperability mechanism with simplified TEE as the underlying architecture. Specifically, we present IvyCross, a TEE-based framework that achieves low-cost, privacy-preserving, and race-free blockchain interoperability. IvyCross allows running arbitrary smart contracts across heterogeneous blockchains atop two distributed TEE-powered hosts. We design …

Spd: Shallow Backdoor Protecting Deep Backdoor Against Backdoor Detection, Shunjie Yuan, Xinghua Li, Xuelin Cao, Haiyan Zhang, Mengyao Zhu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Backdoor attacks have revealed the vulnerability of deep neural networks (DNNs), which motivates the development of secure deep learning systems. However, existing backdoor attacks often fail to bypass backdoor detection and human visual inspection, resulting in the exposure of the backdoor implanted in DNNs, which can subsequently be significantly mitigated through pruning or fine-tuning on benign data. To address this issue, in this paper, we propose a novel backdoor attack called SPD (Shallow Protecting Deep), which consists of a deep backdoor in the frequency domain and a shallow backdoor in the pixel domain, where the shallow backdoor acts as a …

A System Framework To Symbolically Explore Intel Tdx Module Execution, Pansilu Pitigalaarachchillage, Xuhua Ding

Research Collection School Of Computing and Information Systems

We present TDXplorer, the first dynamic symbolic analysis system for Intel's TDX Module, the software trusted computing base of TDX. Without using TDX hardware, an analyzer function on top of TDXplorer can not only apply dynamic analysis to control and instrument the TDX Module's execution, but also carry out symbolic execution for path exploration as well as security and functionality reasoning. The two types of analysis are seamlessly integrated in a way that symbolic execution is conducted directly upon the TDX Module's binary code and runtime states, which are shaped by using dynamic analysis techniques. We implement TDXplorer on Linux …

Adaptive Security Metric For Optimizing Post-Quantum Cryptography In Constrained Iot Devices, Aisha Nasser Ahmed

Theses

Quantum Computing poses real threat to Classical Public-Key Cryptography requiring the use of Post-Quantum Cryptography for all Internet of Things Devices. However, there are greater computational, memory and communication overheads in PQC algorithms that create additional burdens on resource constrained IoT devices. At this time, there are no standard measures for systems developers to determine optimal PQC settings for the various IoT Device Classes. This Thesis develops a new framework of metrics for determining the most suitable PQC settings based on Security Strength, Performance Indicators (Latency, Memory, Energy), Communication Overhead and Reliability for each IoT device class. The Research introduces …

Better Digital Contracts With Prosocial Friction-In-Design, Brett Frischmann, Moshe Y. Vardi

Faculty Publications

Contract law is supposed to enable people to reach genuine agreements and cooperate. If this ideal was ever a reality, the rise of mass market contracts and boil­erplate rendered it pure fiction. Modern consumer contracts are incomprehensible to most people. No one reads them anyway.

Digital contracting involves design features that amplify traditional boilerplate harms and create others. For example, digital contracting is too cheap; low marginal costs lead to overexpansion in scale and scope. To make matters worse, the loss of autonomy from repeat engagement with digital contracting systems is pernicious. People become increasingly predictable and programmable as digital …

Experiential Learning: Innovative Approaches To Post-Secondary Cybersecurity Education, Brendan Bertone, Paul Wagner, Joshua Pauli

Journal of Cybersecurity Education, Research and Practice

The cybersecurity profession continues to face a significant shortfall of qualified professionals despite steady growth in degree programs. Employers consistently cite experience as the main barrier for entry-level cybersecurity hires. This paper argues that clinic-based experiential learning offers a scalable solution to that preparation gap. A systematic literature review spanning academic and professional literature was conducted to examine: (1) barriers to entry for aspiring cybersecurity professionals; (2) the effectiveness of experiential learning compared to traditional instruction; and (3) the viability and scalability of cybersecurity clinics. Screening emphasized workforce development, experiential pedagogy, and alignment with the NICE Cybersecurity Workforce Framework. Findings …

Information Security Awareness And Behavior Of Smartphone Users In The Ibadan Metropolis, Nigeria, Funmilola Olubunmi Omotayo

Journal of Cybersecurity Education, Research and Practice

Today, there is a rapid increase in the number of people using the Internet via smartphones and relying on them for most of their daily activities. Consequently, smartphones are becoming the target of criminals for atrocious purposes. This study investigated the information security awareness and behavior of smartphone users in the Ibadan metropolis, Nigeria. The study adopted a descriptive survey design. Data was collected with a questionnaire from 400 respondents who were conveniently selected. Findings revealed that most smartphone users knew about the smartphone security features available on their phones. However, most also engaged in behaviors that threatened their information …

Privacy-Preserving Ridge Regression Over Encrypted Data Under Multiple Keys, Yanling Li, Junzuo Lai, Meng Sun, Beibei Song, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the increase of private data being collected by data owners, it has been a trend for data owners to store the data on cloud computing platforms. The huge amounts of data in cloud servers bring fresh development opportunities to machine learning, which is applied to build a high-quality machine learning model based on a large training dataset. However, to ensure the privacy of data and facilitate retrieval, data owners often upload encrypted data under their public keys. But it creates new challenges for machine learning to learn a predictive model over these encrypted data under different keys. Most existing …

An Efficient Security-Enhanced Accountable Access Control For Named Data Networking, Jianfei Sun, Yuxian Li, Xuehuan Yang, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Named Data Networking (NDN) is embraced as the crucial implementation of Information-Centric Networking (ICN), enhancing content distribution and caching efficiency through edge routers. However, existing NDN architectures face significant security and privacy challenges, including: (a) a lack of secure and efficient access control; (b) inadequate support for flexible and selective content management by content publishers; (c) insufficient implementation of accountability and privilege revocation mechanisms. To handle these challenges, we propose ESAS, the first-ever Efficient Security-enhanced Accountable Access Control Scheme for NDN. Specifically, our ESAS incorporates anonymous authentication using group signatures at network routers to prevent unauthorized access, employs key-aggregation-based access …

Boosting Symbolic Execution For Vulnerability Detection, Haoxin Tu

Dissertations and Theses Collection (Open Access)

Software systems written by humans tend to be unreliable and insecure, hence, bugs or vulnerabilities in them are inevitable. Symbolic execution has shown considerable potential in detecting diverse types of software bugs and also vulnerabilities that have severe security implications. However, existing symbolic execution engines still suffer from at least three fundamental limitations in memory modeling, path exploration, and structured input generation, which significantly impede existing engines from efficiently and effectively detecting software bugs and vulnerabilities.

The objective of this dissertation is to boost existing symbolic execution engines by designing a new memory model, two new path exploration strategies, and …

Shortcuts Everywhere And Nowhere: Exploring Multi-Trigger Backdoor Attacks, Yige Li, Jiabo He, Hanxun Huang, Jun Sun, Xingjun Ma, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Backdoor attacks have become a significant threat to the pre-training and deployment of deep neural networks (DNNs). Although numerous methods for detecting and mitigating backdoor attacks have been proposed, most rely on identifying and eliminating the “shortcut” created by the backdoor, which links a specific source class to a target class. However, these approaches can be easily circumvented by designing multiple backdoor triggers that create shortcuts everywhere and therefore nowhere specific. In this study, we explore the concept of Multi-Trigger Backdoor Attacks (MTBAs), where multiple adversaries leverage different types of triggers to poison the same dataset. By proposing and investigating …

Cybersecurity And Intention To Use Mobile Banking Applications, Ishmael Chikoo, Salah Kabanda

African Conference on Information Systems and Technology

The adoption rate of mobile banking amongst consumers remains low, especially in developing countries where there is a knowledge gap in understanding why consumers do not engage in the frequent use of mobile banking applications. Given that most financial institutions see mobile banking as a strategy for their competitive advantage; it is important that they understand how best to address consumer’s fears brought about by cybersecurity threats. The purpose of this study is to investigate the perceived influence of cybersecurity on the user’s intentions to use mobile banking applications. Data collected from 90 participants was statistically analysed in Smart PLS …

A Comprehensive Review On Gamification In Neurocybersecurity, Ms. Kritika

Journal of Cybersecurity Education, Research and Practice

The research investigates gamification methods as it applies to the emerging interdisciplinary domain that brings together cybersecurity with neuroscience and psychology. Neurocybersecurity implements neural concepts to protect digital systems from security threats while targeting the human vulnerabilities that present as the strongest points of attack. Several researchers have examined gamification techniques which incorporate game design elements to enhance cybersecurity training outcomes by improving user participation and knowledge retention and user conduct compliance. The research incorporates Self-Determination Theory along with Cognitive Load Theory to explain the design principles for efficient gamified interventions. The implementation of both cognitive performance improvement and neuroplasticity …

A Study On Webassembly And Its Security, Thomas Crossman

Research from the Berry Summer Thesis Institute, 2025

This project studies WebAssembly, a binary language specification that enables non-native languages, such as C/C++ and Rust, to run efficiently on webpages, supporting complex tasks like gaming or data processing. It functions by translating a non-native language into a WebAssembly binary, which is natively supported by most browsers. Notably, WebAssembly uses a linear memory model, storing all non-code data in a single linear array. Unfortunately, this design compromises some security principles, introducing security risks and complications.

Our overall project goal is to investigate WebAssembly functionality, develop a test program, and address a critical security challenge to enhance the safety of …

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …