Information Security Commons^™

Prevalence And Trends Of Depression Among Cyberbullied Adolescents - Youth Risk Behavior Survey, United States, 2011 – 2019, Jason Nicholson, Catherine Marcum, George E. Higgins

International Journal of Cybersecurity Intelligence & Cybercrime

The difference in depression between non-cyberbullied and cyberbullied youth is not well understood. To describe the prevalence and trends in depression among cyberbullied adolescents. Using cross-sectional, nationally-representative data from the YRBS 2011 - 2019, we estimated the prevalence and trends of depression across the total years and within cyberbullied groups that include biological sex and race and ethnicity among adolescents. The results indicated the prevalence of depression was higher among those that were cyberbullied. Within the cyberbullied groups the total trend was higher than the non-cyberbullied, females had a higher prevalence of depression than males, and Hispanics had a higher …

Understanding The Connection Between Hackers And Their Hacks: Analyzing Usdoj Reports For Hacker Profiles, Joshua Gerstenfeld

International Journal of Cybersecurity Intelligence & Cybercrime

Recently, it seems as if hacking-related stories can be found in the news every day. To study, and hopefully prevent, this new type of crime, the field of cyber criminology has emerged. This study adds to the existing cybercrime literature by examining hacking behavior specifically. It determines if there is a relationship between the age, gender, and nationality of hackers and characteristics of the cyberattacks that they perpetrate. To do this, this study analyzes 122 United States Department of Justice (USDOJ) press reports from January 2019 to December 2021. Some key results include the finding that older hackers and international …

Healthcare Facilities: Maintaining Accessibility While Implementing Security, Ryan Vilter

UNO Student Research and Creative Activity Fair

In the wake of the Tulsa, Oklahoma hospital shooting in the summer of 2022, it was made clear that more security needed to be implemented in healthcare facilities. As a result, I inquired: What is the happy balance for healthcare facilities to maintain their accessibility to the public while also implementing security measures to prevent terrorist attacks? With that base, I give recommendations in the areas of cybersecurity, physical infrastructure, and physical and mental health, based off the existing literature and data gathered from terrorist attacks against hospitals over several decades.

Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps), Juan E. Nunez, Roger W. Tchegui Donfack, Rohit Rohit, Hayley Horn

SMU Data Science Review

Today, there is an increased risk to data privacy and information security due to cyberattacks that compromise data reliability and accessibility. New machine learning models are needed to detect and prevent these cyberattacks. One application of these models is cybersecurity threat detection and prevention systems that can create a baseline of a network's traffic patterns to detect anomalies without needing pre-labeled data; thus, enabling the identification of abnormal network events as threats. This research explored algorithms that can help automate anomaly detection on an enterprise network using Canadian Institute for Cybersecurity data. This study demonstrates that Neural Networks with Bayesian …

A Comprehensive Review On Deep Learning-Based Generative Linguistic Steganography, Dr Khaled Nagaty, Israa Lotfy Lotfy, Abeer Hamdy Dr.

Computer Science

. The recent development of deep learning has made a significant breakthrough in linguistic generative steganography. The text has become one of the most intensely used communication carriers on the Internet, making steganography an efficient carrier for concealing secret messages. Text steganography has long been used to protect the privacy and confidentiality of data via public transmission. Steganography utilizes a carrier to embed the data to generate a secret unnoticed and less attractive message. Different techniques have been used to improve the security of the generated text and quality of the steganographic text, such as the Markov model, Recurrent Neural …

The Rise And Risks Of Internet Of Things, Diamond E. Hicks

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) has become a necessary part of our everyday lives. IoT is the network in which many different devices communicate, connect, and share data. Though how IoT got to where it is today, the issues it faced, and how it affects our lives today is not common knowledge. Despite the fact that IoT has advanced our technology to what it is today, people do not completely understand what it does.

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Using Probabilistic Context-Free Grammar To Create Password Guessing Models, Isabelle Hjelden

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper will discuss two versions of probabilistic context-free grammar password-guessing models. The first model focuses on using English semantics to break down passwords and identify patterns. The second model identifies repeating chunks in passwords and uses this information to create possible passwords. Then, we will show the performance of each model on leaked password databases, and finally discuss the observations made on these tests.

Jtag-Based Extraction Of Processor And Memory Data For Anomaly Detection In Cyber-Physical Systems, Jonathan D. Price

Theses and Dissertations

This document is a compilation of two scholarly articles that together compose a graduate thesis. The first article assesses the viability of commercially available JTAG debuggers to access runtime memory and register data, finding that commercial JTAG debuggers are not suitable for runtime data extraction for anomaly detection in cyber-physical systems due to slow memory and register access times. Because of this gap in technology, the second article designs, implements, and tests a novel, custom-built architecture named JTAG Data Extraction Tool (J-DET) for program counter-sampling. J-DET is the first device purpose-built to extract processor information in runtime for attack detection; …

Air Force Digital Badges, Jacob Chan

Theses and Dissertations

The Air Force talent management and force development systems are antiquated. Airmen records are often stored on different Air Force information systems. Existing records sometimes lack granularity and context to recognize Airmen skills. Digital badges are a newer technology utilized by academia and industry to recognize member skills. However, military badging research is sparse and existing studies do not provide sufficient evidence on the value of digital badging to the Air Force. The studies: (1) lack background research on badging; (2) do not provide quantitative data on the effects of badging; and (3) issued badges through commercial entities which may …

Volere: Leakage Resilient User Authentication Based On Personal Voice Challenges, Rui Zhang, Zheng Yan, Xuerui Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Voiceprint Authentication as a Service (VAaS) offers great convenience due to ubiquity, generality, and usability. Despite its attractiveness, it suffers from user voiceprint leakage over the air or at the cloud, which intrudes user voice privacy and retards its wide adoption. The literature still lacks an effective solution on this issue. Traditional methods based on cryptography are too complex to be practically deployed while other approaches distort user voiceprints, which hinders accurate user identification. In this article, we propose a leakage resilient user authentication cloud service with privacy preservation based on random personal voice challenges, named VOLERE (VOice LEakage REsilient). …

Automatic Identification Of Crash-Inducing Smart Contracts, Chao Ni, Cong Tian, Kaiwen Yang, David Lo, Jiachi Chen, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Smart contract, a special software code running on and resided in the blockchain, enlarges the general application of blockchain and exchanges assets without dependence of external parties. With blockchain's characteristic of immutability, they cannot be modified once deployed. Thus, the contract and the records are persisted on the blockchain forever, including failed transactions that are caused by runtime errors and result in the waste of computation, storage, and fees. In this paper, we refer to smart contracts which will cause runtime errors as crash-inducing smart contracts. However, automatic identification of crash-inducing smart contracts is limited investigated in the literature. The …

Fa3: Fine-Grained Android Application Analysis, Yan Lin, Weng Onn Wong, Debin Gao

Research Collection School Of Computing and Information Systems

Understanding Android applications' behavior is essential to many security applications, e.g., malware analysis. Although many systems have been proposed to perform such dynamic analysis, they are limited by their applicable analysis environment (on device vs. emulator), transparency to subject apps, applicable runtime (Dalvik vs. ART), applicable system stack, or granularity. In this paper, we propose FA3 (Fine-Grained Android Application Analysis), a novel on-device, non-invasive, and fine-grained analysis platform by leveraging existing profiling mechanisms in the Android Runtime (ART) and kernel to inspect method invocations and control-flow transfers for both Java methods and third-party native libraries. FA3 embeds its tracing capability …

Lightweight And Non-Invasive User Authentication On Earables, Changshuo Hu, Xiao Ma, Dong Ma, Ting Dang

Research Collection School Of Computing and Information Systems

The widespread adoption of wireless earbuds has advanced the developments in earable-based sensing in various domains like entertainment, human-computer interaction, and health monitoring. Recently, researchers have shown an increased interest in user authentication using earables. Despite the successes witnessed in acoustic probing and speech based authentication systems, this paper proposed a lightweight and non-invasive ambient sound based user authentication scheme. It employs the difference between the in-ear and out-ear sounds to estimate the individual-specific occluded ear canal transfer function (OECTF). Specifically, the {out-ear, in-ear} scaling factors at different frequency bands are captured via linear regression and treated as the OECTF …

Learning To Count Isomorphisms With Graph Neural Networks, Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang

Research Collection School Of Computing and Information Systems

Subgraph isomorphism counting is an important problem on graphs, as many graph-based tasks exploit recurring subgraph patterns. Classical methods usually boil down to a backtracking framework that needs to navigate a huge search space with prohibitive computational costs. Some recent studies resort to graph neural networks (GNNs) to learn a low-dimensional representation for both the query and input graphs, in order to predict the number of subgraph isomorphisms on the input graph. However, typical GNNs employ a node-centric message passing scheme that receives and aggregates messages on nodes, which is inadequate in complex structure matching for isomorphism counting. Moreover, on …

Safe Delivery Of Critical Services In Areas With Volatile Security Situation Via A Stackelberg Game Approach, Tien Mai, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The COVID pandemic and the need to vaccinate added even more urgency to this issue. Motivated by this problem, we propose a general framework to set-up limited temporary (vaccination) centers that balance physical security and desired (vaccine) service coverage with limited resources. We set-up the problem as a Stackelberg game between the centers operator (defender) and an adversary, where the set of centers is not fixed a priori but is part of the decision output. This results in a mixed combinatorial and continuous optimization …

Teaching By Practice: Shaping Secure Coding Mentalities Through Cybersecurity Ctfs, Jazmin Collins, Vitaly Ford

Journal of Cybersecurity Education, Research and Practice

The use of the Capture the Flag (CTF)-style competitions has grown popular in a variety of environments as a method to improve or reinforce cybersecurity techniques. However, while these competitions have shown promise in student engagement, enjoyment, and the teaching of essential workforce cybersecurity concepts, many of these CTF challenges have largely focused on cybersecurity as a general topic. Further, most in-school CTF challenges are designed with technical institutes in mind, prepping only experienced or upper-level students in cybersecurity studies for real-world challenges. Our paper aims to focus on the setting of a liberal arts institute, emphasizing secure coding as …

Lightweight Pairwise Key Distribution Scheme For Iots, Kanwalinderjit Kaur

Journal of Cybersecurity Education, Research and Practice

Embedding a pairwise key distribution approach in IoT systems is challenging as IoT devices have limited resources, such as memory, processing power, and battery life. This paper presents a secure and lightweight approach that is applied to IoT devices that are divided into Voronoi clusters. This proposed algorithm comprises XOR and concatenation operations for interactive authentication between the server and the IoT devices. Predominantly, the authentication is carried out by the server. It is observed that the algorithm is resilient against man-in-the-middle attacks, forward secrecy, Denial of Service (DoS) attacks, and offers mutual authentication. It is also observed that the …

Reinventing Cybersecurity Internships During The Covid-19 Pandemic, Lori L. Sussman

Journal of Cybersecurity Education, Research and Practice

The Cybersecurity Ambassador Program provides professional skills training for emerging cybersecurity professionals remotely. The goal is to reach out to underrepresented populations who may use Federal Work-Study (FWS) or grant sponsored internships to participate. Cybersecurity Ambassadors (CAs) develop skills that will serve them well as cybersecurity workers prepared to do research, lead multidisciplinary, technical teams, and educate stakeholders and community members. CAP also reinforces leadership skills so that the next generation of cybersecurity professionals becomes a sustainable source of management talent for the program and profession. The remote curriculum innovatively builds non-technical professional skills (communications, teamwork, leadership) for cybersecurity research …

Risk Perceptions About Personal Internet-Of-Things: Research Directions From A Multi-Panel Delphi Study, Paul M. Di Gangi, Barbara A. Wech, Jennifer D. Hamrick, James L. Worrell, Samuel H. Goh

Journal of Cybersecurity Education, Research and Practice

Internet-of-Things (IoT) research has primarily focused on identifying IoT devices' organizational risks with little attention to consumer perceptions about IoT device risks. The purpose of this study is to understand consumer risk perceptions for personal IoT devices and translate these perceptions into guidance for future research directions. We conduct a sequential, mixed-methods study using multi-panel Delphi and thematic analysis techniques to understand consumer risk perceptions. The results identify four themes focused on data exposure and user experiences within IoT devices. Our thematic analysis also identified several emerging risks associated with the evolution of IoT device functionality and its potential positioning …