A Mixed-Method Study Exploring Cyber Ranges And Educator Motivation,
2023
Regent University
A Mixed-Method Study Exploring Cyber Ranges And Educator Motivation, Cheryl Beauchamp, Holly M. Matusovich
Journal of Cybersecurity Education, Research and Practice
A growing number of academic institutions have invested resources to integrate cyber ranges for applying and developing cybersecurity-related knowledge and skills. Cyber range developers and administrators provided much of what is known about cyber range resources and possible educational applications; however, the educator provides valuable understanding of the cyber range resources they use, how they use them, what they value, and what they do not value. This study provides the cyber range user perspective of cyber ranges in cybersecurity education by describing how K-12 educators are motivated using cyber ranges. Using mixed methods, this study explored educator motivation associated with …
Exploring Network Security Educator Knowledge,
2023
University of Houston
Exploring Network Security Educator Knowledge, Jennifer B. Chauvot, Deniz Gurkan, Cathy Horn
Journal of Cybersecurity Education, Research and Practice
It is critical for nations to have trained professionals in network security who can safeguard hardware, information systems, and electronic data. Network security education is a key knowledge unit of the National Centers of Academic Excellence in Cybersecurity and various information systems security curricula at the master's and bachelor's levels in higher education. Network security units are components of computer science curricula in high school contexts as well. Educators who teach these concepts play a significant role in developing a skilled workforce of network security experts for both governmental and non-governmental organizations. Understanding the necessary knowledge and skills of network …
Editorial,
2023
Kennesaw State University
Editorial, Michael E. Whitman, Herbert J. Mattord
Journal of Cybersecurity Education, Research and Practice
Editorial for Volume 2023, Issue 2
Like Treating The Symptom Rather Than The Cause - The Omission Of Courses Over Terrorism In Nsa Designated Institutions,
2023
Old Dominion University
Like Treating The Symptom Rather Than The Cause - The Omission Of Courses Over Terrorism In Nsa Designated Institutions, Ida L. Oesteraas
Journal of Cybersecurity Education, Research and Practice
The National Security Agency (NSA) awards Center of Academic Excellence (CAE) designations to institutions that commit to producing cybersecurity professionals who will work in careers that reduce vulnerabilities in our national infrastructure. A review of the curricula in the 327 institutions and their degree programs reveal that only two programs offer a required course about terrorism. Given the fluid nature of terrorism and its threat to national infrastructure, the omission is concerning. It is recommended that NSA-certified cybersecurity programs begin implementing educational content that aim to teach about this emerging crime and justice issue. One suggestion is to embrace the …
Integrating Certifications Into The Cybersecurity College Curriculum: The Efficacy Of Education With Certifications To Increase The Cybersecurity Workforce,
2023
Georgia Gwinnett College
Integrating Certifications Into The Cybersecurity College Curriculum: The Efficacy Of Education With Certifications To Increase The Cybersecurity Workforce, Binh Tran, Karen C. Benson, Lorraine Jonassen
Journal of Cybersecurity Education, Research and Practice
One only needs to listen to the news reports to recognize that the gap between securing the enterprise and cybersecurity threats, breaches, and vulnerabilities appears to be widening at an alarming rate. An un-tapped resource to combat these attacks lies in the students of the secondary educational system. Necessary in the cybersecurity education is a 3-tiered approach to quickly escalate the student into a workplace-ready graduate. The analogy used is a three-legged-stool, where curriculum content, hands-on skills, and certifications are equal instruments in the edification of the cybersecurity student. This paper endeavors to delve into the 3rd leg of …
Privacy Harm And Non-Compliance From A Legal Perspective,
2023
Dakota State University
Privacy Harm And Non-Compliance From A Legal Perspective, Suvineetha Herath, Haywood Gelman, Lisa Mckee
Journal of Cybersecurity Education, Research and Practice
In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, …
Cybersecurity Challenges And Awareness Of The Multi-Generational Learners In Nepal,
2023
Kathmandu University, School of Education
Cybersecurity Challenges And Awareness Of The Multi-Generational Learners In Nepal, Raj Kumar Dhungana, Lina Gurung Dr, Hem Poudyal
Journal of Cybersecurity Education, Research and Practice
Increased exposure to technologies has lately emerged as one of the everyday realities of digital natives, especially K-12 students, and teachers, the digital immigrants. Protection from cybersecurity risks in digital learning spaces is a human right, but students are increasingly exposed to high-risk cyberspace without time to cope with cybersecurity risks. This study, using a survey (N-891 students and 157 teachers) and in-depth interviews (27 students and 14 teachers), described the students' cybersecurity-related experiences and challenges in Nepal. This study revealed that the school’s cybersecurity support system is poor and teachers has very low awareness and competencies to protect students …
What You See Is Not What You Know: Studying Deception In Deepfake Video Manipulation,
2023
Kennesaw State University
What You See Is Not What You Know: Studying Deception In Deepfake Video Manipulation, Cathryn Allen, Bryson R. Payne, Tamirat Abegaz, Chuck Robertson
Journal of Cybersecurity Education, Research and Practice
Research indicates that deceitful videos tend to spread rapidly online and influence people’s opinions and ideas. Because of this, video misinformation via deepfake video manipulation poses a significant online threat. This study aims to discover what factors can influence viewers’ capability to distinguish deepfake videos from genuine video footage. This work focuses on exploring deepfake videos’ potential use for deception and misinformation by exploring people’s ability to determine whether videos are deepfakes in a survey consisting of deepfake videos and original unedited videos. The participants viewed a set of four videos and were asked to judge whether the videos shown …
Configuring Timing Parameters To Ensure Execution-Time Opacity In Timed Automata,
2023
Singapore Management University
Configuring Timing Parameters To Ensure Execution-Time Opacity In Timed Automata, Étienne André, Engel Lefaucheux, Didier Lime, Dylan Marinho, Jun Sun
Research Collection School Of Computing and Information Systems
Timing information leakage occurs whenever an attacker successfully deduces confidential internal information by observing some timed information such as events with timestamps. Timed automata are an extension of finite-state automata with a set of clocks evolving linearly and that can be tested or reset, making this formalism able to reason on systems involving concurrency and timing constraints. In this paper, we summarize a recent line of works using timed automata as the input formalism, in which we assume that the attacker has access (only) to the system execution time. First, we address the following execution-time opacity problem: given a timed …
Owner-Free Distributed Symmetric Searchable Encryption Supporting Conjunctive Queries,
2023
Singapore Management University
Owner-Free Distributed Symmetric Searchable Encryption Supporting Conjunctive Queries, Qiuyun Tong, Xinghua Li, Yinbin Miao, Yunwei Wang, Ximeng Liu, Robert H. Deng
Research Collection School Of Computing and Information Systems
Symmetric Searchable Encryption (SSE), as an ideal primitive, can ensure data privacy while supporting retrieval over encrypted data. However, existing multi-user SSE schemes require the data owner to share the secret key with all query users or always be online to generate search tokens. While there are some solutions to this problem, they have at least one weakness, such as non-supporting conjunctive query, result decryption assistance of the data owner, and unauthorized access. To solve the above issues, we propose an Owner-free Distributed Symmetric searchable encryption supporting Conjunctive query (ODiSC). Specifically, we first evaluate the Learning-Parity-with-Noise weak Pseudorandom Function (LPN-wPRF) …
Integrating Human Expert Knowledge With Openai And Chatgpt: A Secure And Privacy-Enabled Knowledge Acquisition Approach,
2023
California Polytechnic State University, San Luis Obispo
Integrating Human Expert Knowledge With Openai And Chatgpt: A Secure And Privacy-Enabled Knowledge Acquisition Approach, Ben Phillips
College of Engineering Summer Undergraduate Research Program
Advanced Large Language Models (LLMs) struggle to produce accurate results and preserve user privacy for use cases involving domain-specific knowledge. A privacy-preserving approach for leveraging LLM capabilities on domain-specific knowledge could greatly expand the use cases of LLMs in a variety of disciplines and industries. This project explores a method for acquiring domain-specific knowledge for use with GPT3 while protecting sensitive user information with ML-based text-sanitization.
Toward Intention Discovery For Early Malice Detection In Cryptocurrency,
2023
Singapore Management University
Toward Intention Discovery For Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu
Research Collection School Of Computing and Information Systems
Cryptocurrency’s pseudo-anonymous nature makes it vulnerable to malicious activities. However, existing deep learning solutions lack interpretability and only support retrospective analysis of specific malice types. To address these challenges, we propose Intention-Monitor for early malice detection in Bitcoin. Our model, utilizing Decision-Tree based feature Selection and Complement (DT-SC), builds different feature sets for different malice types. The Status Proposal Module (SPM) and hierarchical self-attention predictor provide real-time global status and address label predictions. A survival module determines the stopping point and proposes the status sequence (intention). Our model detects various malicious activities with strong interpretability, outperforming state-of-the-art methods in extensive …
Visilience: An Interactive Visualization Framework For Resilience Analysis Using Control-Flow Graph,
2023
Singapore Management University
Visilience: An Interactive Visualization Framework For Resilience Analysis Using Control-Flow Graph, Hailong Jiang, Shaolun Ruan, Bo Fang, Yong Wang, Qiang Guan
Research Collection School Of Computing and Information Systems
Soft errors have become one of the main concerns for the resilience of HPC applications, as these errors can cause HPC applications to generate serious outcomes such as silent data corruption (SDC). Many approaches have been proposed to analyze the resilience of HPC applications. However, existing studies rarely address the challenges of analysis result perception. Specifically, resilience analysis techniques often produce a massive volume of unstructured data, making it difficult for programmers to perform resilience analysis due to non-intuitive raw data. Furthermore, different analysis models produce diverse results with multiple levels of detail, which can create obstacles to compare and …
Factors Influencing User Adherence Towards Privacy Standards Of Internet Of Things Devices,
2023
University of Cape Town
Factors Influencing User Adherence Towards Privacy Standards Of Internet Of Things Devices, Philip Bazanye, Walter Uys, Wallace Chigona
African Conference on Information Systems and Technology
The upsurge in the use of Internet of things (IoT) devices increases the likelihood of cyber-attacks on end users. The objective of the study reported here was to investigate the factors that influence IoT device users’ adherence to privacy standards. This interpretivist exploratory research was guided by a three-phased approach using activity theory. The interview questions were derived from the conceptual model and themes analysed using deductive thematic analysis. The findings indicate that a lack of adherence is driven by a lack of trust in IoT devices and service providers, as well as convenience and health factors. In addition, users’ …
Social Media & Privacy: Understanding Privacy In The Age Of Content Creator Culture,
2023
Ghana Institute of Management and Public Administration
Social Media & Privacy: Understanding Privacy In The Age Of Content Creator Culture, Robert Tagoe, Raphael Amponsah, Emmanuel Awuni Kolog, Eric Afful-Dadzie
African Conference on Information Systems and Technology
In today's digital age, content creators are gaining public attention and becoming highly influential. With that increased influence, it is important to acknowledge the privacy concerns within this culture. This interpretive research study seeks to identify and understand the dynamics of privacy within the content creator culture. This research will leverage information from interviews with content creators from various social media platforms such as YouTube, Instagram, Facebook, and TikTok. Using theories to understand the phenomena, theories of privacy calculus, privacy paradox and self-disclosure, will be used to view how content creators define and navigate privacy, strategies employed to control personal …
Identity Management Pki System Using Blockchain,
2023
American University in Cairo
Identity Management Pki System Using Blockchain, Mohamed Abdel Fattah Abdel Baki Awad
Theses and Dissertations
Identity management is one of the most important topics in the security field. Public Key Infrastructure (PKI) is the most commonly used approach in legally identity management systems. PKI systems have many centralized services that might affect the availability and trustworthiness of the system. Issues related to certificate verification methods such as Certificate Revocation List (CRL) and Online Certificate Status Protocol (OCSP) can be avoided if blockchain is used. Blockchain is a decentralized trusted system where data can only be appended to a public ledger. Edits are not allowed in blockchain. Blockchain consists of several nodes all of them have …
Threshold Attribute-Based Credentials With Redactable Signature,
2023
Singapore Management University
Threshold Attribute-Based Credentials With Redactable Signature, Rui Shi, Huamin Feng, Yang Yang, Feng Yuan, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Threshold attribute-based credentials are suitable for decentralized systems such as blockchains as such systems generally assume that authenticity, confidentiality, and availability can still be guaranteed in the presence of a threshold number of dishonest or faulty nodes. Coconut (NDSS'19) was the first selective disclosure attribute-based credentials scheme supporting threshold issuance. However, it does not support threshold tracing of user identities and threshold revocation of user credentials, which is desired for internal governance such as identity management, data auditing, and accountability. The communication and computation complexities of Coconut for verifying credentials are linear in the number of each user's attributes and …
Testsgd: Interpretable Testing Of Neural Networks Against Subtle Group Discrimination,
2023
Singapore Management University
Testsgd: Interpretable Testing Of Neural Networks Against Subtle Group Discrimination, Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun
Research Collection School Of Computing and Information Systems
Discrimination has been shown in many machine learning applications, which calls for sufficient fairness testing before their deployment in ethic-relevant domains. One widely concerning type of discrimination, testing against group discrimination, mostly hidden, is much less studied, compared with identifying individual discrimination. In this work, we propose TestSGD, an interpretable testing approach which systematically identifies and measures hidden (which we call ‘subtle’) group discrimination of a neural network characterized by conditions over combinations of the sensitive attributes. Specifically, given a neural network, TestSGD first automatically generates an interpretable rule set which categorizes the input space into two groups. Alongside, TestSGD …
Autodebloater: Automated Android App Debloating,
2023
Singapore Management University
Autodebloater: Automated Android App Debloating, Jiakun Liu, Xing Hu, Thung Ferdian, Shahar Maoz, Eran Toch, Debin Gao, David Lo
Research Collection School Of Computing and Information Systems
Android applications are getting bigger with an increasing number of features. However, not all the features are needed by a specific user. The unnecessary features can increase the attack surface and cost additional resources (e.g., storage and memory). Therefore, it is important to remove unnecessary features from Android applications. However, it is difficult for the end users to fully explore the apps to identify the unnecessary features, and there is no off-the-shelf tool available to assist users to debloat the apps by themselves. In this work, we propose AutoDebloater to debloat Android applications automatically for end users. AutoDebloater is a …
Hercules: Boosting The Performance Of Privacy-Preserving Federated Learning,
2023
Nanyang Technological University
Hercules: Boosting The Performance Of Privacy-Preserving Federated Learning, Guowen Xu, Xingshuo Han, Shengmin Xu, Tianwei Zhang, Hongwei Li, Xinyi Huang, Robert H. Deng
Research Collection School Of Computing and Information Systems
In this paper, we address the problem of privacy-preserving federated neural network training with N users. We present Hercules, an efficient and high-precision training framework that can tolerate collusion of up to N−1 users. Hercules follows the POSEIDON framework proposed by Sav et al. (NDSS’21), but makes a qualitative leap in performance with the following contributions: (i) we design a novel parallel homomorphic computation method for matrix operations, which enables fast Single Instruction and Multiple Data (SIMD) operations over ciphertexts. For the multiplication of two h×h dimensional matrices, our method reduces the computation complexity from O(h3) to O(h) . This …
