Cybersecurity Knowledge Research Articles

Enhancing Cybersecurity Awareness through Gamification: Design an Interactive Cybersecurity Learning Platform for Multimedia University Students

Cybersecurity has emerged as a critical imperative in contemporary digital landscapes, necessitating heightened awareness and proficiency across all demographic segments. Accordingly, this research has been meticulously crafted to delve into the complexities of cybersecurity awareness, with a specific focus on university students. The study embarks on an exhaustive analysis encompassing the evaluation of cybersecurity awareness levels within the targeted groups, the identification of prevailing issues and practices, and an exploration of novel methodologies, notably gamification, to fortify cybersecurity knowledge and skills among diverse user cohorts. Central to this investigation is the efficacy of gamified learning environments tailored expressly for augmenting cybersecurity awareness among university students. Through a comprehensive examination of existing platforms, methodological frameworks, and user interactions, this research outlines critical trends, challenges, and latent opportunities within the cybersecurity awareness domain, with a specific emphasis on gamification's transformative potential. The study not only identifies key areas for improvement but also proposes innovative solutions rooted in gamified learning paradigms, with the overarching goal of fostering engaging, effective, and sustainable cybersecurity awareness initiatives among students. Drawing upon a synthesis of theoretical constructs, empirical insights, and pragmatic recommendations, this research significantly contributes to the evolving discourse on cybersecurity education. By underscoring the transformative efficacy of gamification as a pivotal tool in cybersecurity awareness initiatives, this study overlays the way for substantial advancements in cybersecurity education paradigms, offering a roadmap for enhancing cybersecurity awareness levels among university students and beyond.

Mitigating Complex Cyber Threats: An Integrated Multimodal Deep Learning Framework for Enhanced Security

Abstract: The rapidly evolving landscape of cyber threats poses significant challenges to traditional cybersecurity methods, particularly in detecting and mitigating complex attacks that combine multiple data modalities. This article introduces a novel approach utilizing Multimodal Deep Learning (MDL) to enhance cybersecurity detection and prevention capabilities. By fusing Natural Language Processing (NLP) and computer vision techniques, our proposed MDL framework demonstrates superior performance in analyzing both textual and visual data associated with potential threats. Through a series of experiments and case studies, we show that this integrated approach significantly improves detection accuracy, reduces false positives, and exhibits remarkable adaptability to emerging attack vectors. Our results indicate a 37% increase in threat detection efficiency and a 42% reduction in false positives compared to traditional unimodal methods. Furthermore, we explore the potential applications of this technology in email security, social media monitoring, and advanced malware detection. This article not only contributes to the growing body of knowledge in AI-driven cybersecurity but also provides a roadmap for future developments, including the integration of audio analysis and the application of Explainable AI (XAI) to enhance trust and transparency in MDL-based security systems.

Evaluating and validating the Serious Slow Game Jam methodology as a mechanism for co-designing serious games to improve understanding of cybersecurity for different demographics

We present an evaluation of a Serious Slow Game Jam (SSGJ) methodology as a mechanism for co-designing serious games in the application domain of cybersecurity, to evaluate how the SSGJ methodology contributed to improving the understanding of cybersecurity for different demographics. The aim of this study was to evaluate how the SSGJ contributed to improving the understanding of cybersecurity for young persons between the ages of 11 and 16 years old who had no formal training or education in cybersecurity, and to validate and compare these results to previous work where the same SSGJ methodology was used with a different target demographic (i.e.,M.Sc. students with no formal training or education in secure coding). To this end, we engaged 23 participants between the ages of 11 and 16 years old for 5 consecutive days over a one-week period, in a multidisciplinary SSGJ involving domain-specific, pedagogical, and game design knowledge, and encouraged engagement in-between scheduled events of the SSGJ. Findings show improved confidence of participants in their knowledge of cybersecurity, for both demographics, after undertaking the Serious Slow Game Jam (from 41.2% to 76.5% for young persons, and from 12.5% to 62.5% for M.Sc. students). Free-text answers specifically indicate an improved understanding of cybersecurity in general, and one specific security vulnerability, attack or defence for a quarter of young persons, and the trichotomy of security vulnerabilities, attacks, and defences for three quarters of the M.Sc. students. Also, confidence in knowledge of game design improved for both demographics (from 47.1% to 82.4% for young persons and from 12.5% to 75% for M.Sc. students). The SSGJ methodology also successfully engaged both demographics of participants in-between scheduled days. Finally, two serious games in the application domain of cybersecurity are presented that were co-designed during the SSGJ with participants and produced as an output of the SSGJs.

BVTED: A Specialized Bilingual (Chinese–English) Dataset for Vulnerability Triple Extraction Tasks

Extracting knowledge from cyber threat intelligence is essential for understanding cyber threats and implementing proactive defense measures. However, there is a lack of open datasets in the Chinese cybersecurity field that support both entity and relation extraction tasks. This paper addresses this gap by analyzing vulnerability description texts, which are standardized and knowledge-dense, to create a vulnerability knowledge ontology comprising 13 entities and 15 relations. We annotated 27,311 unique vulnerability description sentences from the China National Vulnerability Database, resulting in a dataset named BVTED for cybersecurity knowledge triple extraction tasks. BVTED contains 97,391 entities and 69,614 relations, with entities expressed in a mix of Chinese and English. To evaluate the dataset’s value, we trained five deep learning-based named entity recognition models, two relation extraction models, and two joint entity–relation extraction models on BVTED. Experimental results demonstrate that models trained on this dataset achieve excellent performance in vulnerability knowledge extraction tasks. This work enhances the extraction of cybersecurity knowledge triples from mixed Chinese and English threat intelligence corpora by providing a comprehensive ontology and a new dataset, significantly aiding in the mining, analysis and utilization of the knowledge embedded in cyber threat intelligence.

Cyber Defense Using Cyber Threat Intelligence to Anticipate and Avoid Future Cyber Attacks

Research objective: This study evaluates the efficiency of cyber threat intelligence (CTI) for predicting and mitigating cyber threats, which is important in business today. Organisations endure cyber assaults and fight cyber crimes, which threaten commercial exposure. CTI is a proactive approach to these risks since it gives the finest methods and relevant information on potential cyber crimes. Research significance: This review article analyses the literature in the context to find gaps and include ethical research practices. This systematic study may determine how threat intelligence improves cyber security knowledge and eliminates cyber threats by examining assessable information. It may guide the development of new threat intelligence-influencing methods and frameworks. Methodology: Through a qualitative approach based on the systematic review, the study goals were evaluated, analysed, and explained. PRISMA chart was also used to describe exclusion and inclusion study criteria to ensure correct data gathering. The results were presented in a thematic analysis while examining article dependability, quality, and validity. The author used inductive research to reach the primary study conclusions. Using observations or data, inductive inquiry creates hypotheses or generalisations. Research findings: Threat intelligence may considerably increase an organisation's ability to anticipate and prevent cyber threats. The literature emphasised that threat information improves incident response, identifies new threats, and strengthens cyber security. Organisations should continually train and educate cyber security personnel to increase threat intelligence utilisation. Instruct incident response, threat intelligence analysis, and emerging threat trends.CTI helps a company grow smoothly and achieve its goals.

Try to esCAPE from Cybersecurity Incidents! A Technology-Enhanced Educational Approach

AbstractIncorporating gamification elements and innovative approaches in training programs are promising for addressing cybersecurity knowledge gaps. Cybersecurity education should combine hard and soft skill development when building the capacity to manage cyber incidents requiring timely communication, team collaboration, and self-efficacy in risk assessment and incident mitigation. The paper presents a design and evaluation of the technology-enhanced cybersecurity education approach CAPE which works as a hybrid escape room. It combines a virtualized infrastructure simulating the business environment and the physical environment where game participants play the role of the incident response team at the organization’s premises. The CAPE could be applied as a student-centered approach in the educational environment. The work employed a multiple-methods research approach to design a gamified approach and investigate crisis communication, collaboration, self-regulation, and technical competences in incident management scenarios. The design science methodology empowered the game’s construction with an attack surface covering physical and digital security. The undergraduate students participated in the pilot execution and completed the psychological questionnaires. The results were analyzed using statistical methods. Results of the CAPE execution showed a positive impact on student performance and increased interest in cybersecurity. The designed approach promoted field-specific competence development. The results demonstrated the significance of psychological aspects related to incident management. Graphical abstract

A data-driven multi-perspective approach to cybersecurity knowledge discovery through topic modelling

Cybersecurity is crucial for protecting the privacy of digital systems, maintaining economic stability, and ensuring national security. This study presents a comprehensive approach to cybersecurity knowledge discovery through topic modelling, using a multi-perspective analysis of academic and industry sources. The datasets include 15,751 articles from the Web of Science (WoS) database and 5,831 articles from Security Magazine, spanning from 2011 to 2023. We employed BERTopic for topic modelling, UMAP for dimensionality reduction, and HDBSCAN clustering algorithm for grouping and analysing distinct article clusters to uncover latent topics, enhancing the understanding of the evolving cybersecurity landscape. This study found 12 micro-clusters and three macro-clusters, namely technology, smart city and education, from the WoS database and 12 more micro-clusters and four macro-clusters, including organization, public security, governance, and education, from magazines. This study reveals key cybersecurity research and practice trends, such as the increasing focus on malware, ransomware, and cyber-attack mitigation. Additionally, temporal analysis indicates a significant rise in cybersecurity interest around 2020, followed by a diversification of topics. The results highlight the importance of integrating diverse data sources to capture a holistic view of cybersecurity developments. Future work will aim to refine the clustering algorithms to further improve topic extraction and analysis and expand the datasets to include more diverse sources and perspectives. This approach helps discover current cybersecurity trends and provides a foundation for more targeted and effective cybersecurity strategies.

Using Wargaming to Model Cyber Defense Decision-Making: Observation-Based Research in Locked Shields

Defensive Cyber Operations (DCO) in complex environments, such as cyber wargames, require in-depth cybersecurity knowledge and the ability to make quick decisions. In a typical DCO, execution rarely follows a pre-planned path because of extensive adversary influence, challenging an already complex decision-making environment. Decision-making models have been extensively studied from perspectives of military operations and business management, but they are not sufficiently researched in the context of cyber. This paper responds to this need by examining the decision-making models of DCO leaders in a live-fire wargame environment. This study was conducted by observing leaders of cyber operations during the world's largest live-fire cyber exercise, NATO Locked Shield 2023. In this exercise, the blue teams plan and execute their defensive cyber operation in a realistic operational environment, while the red team conducts attacks against the defended environment. The large-scale, wargaming-style environment of Locked Shield is one of the best environments for modelling DCO decision-making models; in this exercise, the DCO is broad and multi-faceted, a perspective which cannot be achieved in a typical capture-the-flag competition or a single security incident. DCO leaders must be able to manage two distinct decision-making processes with different sets of required skills to be successful in the mission. While the primary process relates to the execution and evolution of the pre-designed plan with traditional operational leadership skills, the secondary process deals with unplanned and deliberately caused cyber-related events that require a deep understanding of cybersecurity. In this respect, the main contribution of this research is the constructed decision-making model of the DCO leader. This model is based on observations collected and presented in the context of multiple well-known decision-making frameworks. This model can be further used to train future DCO leaders and assess artificial intelligence's usability to support and automate decision-making in such operations.

Educating Cybersecurity Experts: Analysis of Cybersecurity Education in Finnish Universities

Cybersecurity is no longer just a technical discipline but a strategic concept. Nowadays, cybersecurity has become an essential part of national security strategies. The European Union and European countries have established cybersecurity strategies to strengthen European and national resilience against cyber threats and ensure that citizens and businesses can take full advantage of reliable services and digital tools. A wide range of actors in society, from both government and non-government sectors, are already involved in cybersecurity work. However, there is a constant need to increase the workforce of cybersecurity specialists to manage cybersecurity risks. Finland's cybersecurity strategy emphasizes the importance of developing cybersecurity education to address the cybersecurity risks the country faces. For the nation to achieve cyber self-sufficiency, the pool of cybersecurity specialists should include experts in every knowledge area relevant to various aspects of cybersecurity. Universities have a role in training cybersecurity specialists through their education programs. Consequently, universities should offer comprehensive education encompassing all cybersecurity knowledge areas. This paper aims to overview the state of cybersecurity education in Finland's universities by focusing on cybersecurity education content. By analysing the content of the universities' cybersecurity education, the aim was to understand how current education in Finland meets the cybersecurity knowledge areas of the European Cybersecurity Taxonomy. In spring 2023, data on cybersecurity degree programs and courses were collected through surveys from nine Finnish universities providing cybersecurity education. As a result, we gained an understanding of the capability of Finnish university-level cybersecurity education to offer specialists in different domain areas of cybersecurity.

Cybersecurity Awareness among Special Needs Students: The Role of Parental Control

The awareness of cybersecurity among special needs students is necessary to help them stay safe while using technology. Recently, a good amount of interest has been drawn toward understanding the concepts and awareness of cybersecurity, and institutions have made efforts to help introduce awareness campaigns to help students understand the concepts of cybersafety, particularly for special needs students. The prior literature has focused primarily on exploring students' preferences, readiness, and experiences with cybersecurity. However, little attention has been given to measuring the level of cybersecurity awareness among students with special needs. To bridge this knowledge gap, the present study conducted an online survey to analyse the level of cybersecurity awareness and parental control among secondary school students with special needs aged 13 to 19 years in Malaysia. The study revealed that special needs students have a moderate level of cybersecurity awareness, with no significant difference among genders or academic streams. However, age does play a role in the level of awareness. Students with better cybersecurity knowledge are more satisfied with their online activities. Educating and monitoring special needs students on cyberattacks, password management, and phishing is crucial. In addition, parental control was found to be reasonable for most parents of students with special needs. This study contributes new knowledge by emphasizing the importance of parental control as a moderating variable in explanatory studies. It also highlights the need for further research in this area to expand the understanding of the importance of cybersecurity and how it can be implemented in specific school environments.

Unraveling influential factors shaping employee cybersecurity behaviors: an empirical investigation of public servants in Vietnam

PurposeGovernment employees must comply with policies on information security regulations, online security practices, social networking usage, internet addiction, online cyberthreats and other related habits. These activities are considered cybersecurity behaviors. Government social media (GSM) accounts are increasingly used to educate employees about cybersecurity risks. To support the effectiveness of cybersecurity practices in government organizations, the purpose of this study is to investigate the impacts of GSM and organizational policy compliance on employees’ cybersecurity awareness, motivation and behaviors.Design/methodology/approachData were obtained by administering a questionnaire survey to public personnel in Vietnam. A total of 330 valid responses were obtained, and the research hypotheses were tested using partial least squares–structural equation modeling.FindingsFirst, cybersecurity awareness enhances information protection motivation and employee protective behavior. Second, GSM has positive impacts on cybersecurity knowledge and information protection motivation. Third, there is a strong positive association between information protection motivation and employee protective behavior. Finally, while organizational compliance significantly increases cybersecurity awareness, its impact on employee protective behavior is ind irect.Originality/valueThis research enhances the literature on the behavioral dimension of cybersecurity. The primary objective of this study is to assess the influence of cybersecurity awareness on protective behaviors rather than intents and attitudes alone. Furthermore, this research integrates protection motivation theory and cultivation theory to provide a more thorough assessment of cybersecurity awareness and protective behavior. By investigating the impact of GSM on the level of cybersecurity awareness among employees within government organizations, this study provides valuable insights into the efficacy of recent governmental initiatives aimed at fostering cybersecurity.

Lived Experiences, Challenges, and Coping Mechanisms of Undergraduate Students on Cybersecurity in Digital Environments

Higher education students use digital devices for learning, entertainment, and financial transactions. The present study examines undergraduate (UG) students’ challenges faced in cyber security space amid digital environments. The study employed a qualitative research design with a narrative inquiry method to capture the lived experiences, challenges, and coping mechanism of UG students through semi structured interviews. The researchers analyzed the qualitative data of ten UG students using the inductive thematic analysis method. UG students shared overall that they face varied experiences, multiple challenges, and cope with cyber security issues in multiple ways. Findings from the study led to recommendations for stakeholders, which includes designing higher education classes in a more secure way. This may offer students orientation on cybersecurity knowledge which keeps them safe and helps them understand the digital environment overall.

Reliability and validity of the Cybersecurity Awareness INventory (CAIN)

ABSTRACT The Cybersecurity Awareness INventory (CAIN) was introduced by Tempestini and colleagues (2023, “The Cybersecurity Awareness INventory (CAIN): Early Phases of Development of a Tool for Assessing Cybersecurity Knowledge Based on the ISO/IEC 27032.” Journal of Cybersecurity and Privacy 3 (1): 61–75) as a proficiency test designed to estimate individuals’ knowledge of cyber threats. The questionnaire was based on ISO/IEC 27032:2012 (Information Technology – Security Techniques – Guidelines for Cybersecurity) and consisted of 46 items. In this paper, we present the results of a survey study conducted on a sample of 1511 Italian workers belonging to the same large organisation. The administration of the CAIN to an Italian sample forced us to make an adaptation to the Italian language of the questionnaire. Using Rasch analysis, we improved the CAIN by eliminating some items that did not fit the expected response patterns, leading to a newer and more parsimonious 30-item version. the CAIN score was also used as the dependent variable in a series of ANOVA designs using several security behaviours as factors. That allowed us to test its predictive validity, confirming the ability of the instrument to discriminate between different user profiles with respect to reported security behaviours. Overall, the revised test showed better performance in terms of reliability and validity.

The impact of perceived cyber-risks on automated vehicle acceptance: Insights from a survey of participants from the United States, the United Kingdom, New Zealand, and Australia

No study has systematically investigated the public's perceptions of cyber risks and their relationship with the acceptance of fully Connected and Automated Vehicles (CAVs). To address this knowledge gap, we developed a conceptual model and investigated the impact of the cyber-emulated risks (cyberattack, safety risk, connectivity risk, privacy risk, and performance risk) that may influence the adoption of CAVs. We tested the proposed model using structural equation modelling with a nationally representative sample of 2062 adults from the US, UK, New Zealand, and Australia.The results indicate that perceived cyberattacks had a significant but marginally neutral effect on usage intent, illustrating the acceptance of technical risk with CAVs. This finding challenges the commonly held belief that cyberattacks negatively influence the adoption of products and technology in other product development fields, such as information technology. CAV cyberattacks elevate concerns about safety, connectivity, privacy, and performance risks. Interestingly, connectivity risk had no significant impact on CAV's behaviour intention, but mediation analysis showed it indirectly affects CAV's acceptance through privacy and performance risks. Regarding socio-demographic and technological attributes, participants of older age, middle income, low-middle education, high cybersecurity knowledge and AV understanding exhibit high anxiety about CAV cyberattacks. The results hold significant policy implications, suggesting the need for tailored strategies in enhancing the cybersecurity of CAVs to ensure their successful adoption and deployment. The findings of this study aim to enhance the quality of transport policy and bridge the gap between theory and practice in addressing cyber risks in the transport sector.

A Light Review on Cyber Security Awareness Models for the Elderly

Millions of people use the internet daily, including the elderly, who are among the most at-risk groups for cybercrime, such as fraud, hacking, and cyberbullying. However, there has been a lack of cybercrime studies focusing on them. Additionally, various cybersecurity models deployed by governments and organizations are found to be inconvenient and too technical for the elderly, especially those with impairments or conditions that require special attention. This subsequently leads to an increasing number of cybercrimes. Therefore, this paper presents a light review of existing cybersecurity models suitable for the elderly. Three methods were used to review existing cybersecurity awareness models. First, a feasibility study was conducted following several works of literature related to cybersecurity, types of cybercrimes involving the elderly, characteristics of the elderly commonly targeted by cybercriminals, cybersecurity awareness models, and the elderly's learning styles. Second, based on the literature review, the elderly's learning styles were analyzed. Finally, the cybersecurity awareness model suitable for the elderly was chosen and analyzed with respect to their phases, validity, and technicality. In conclusion, the SCSAM-Elderly was selected as the most suitable model for the elderly to learn and spread awareness of cybersecurity. This study could increase cybersecurity awareness and encourage educating the elderly to maximize their knowledge of cybersecurity. The findings from this study can guide organizations, agencies, governments, and educational institutions in their endeavours to educate the elderly about cybercrime and cyberattacks.

Introduction to Cyber Security

In today’s world driven by technology and network connectivity, it’s important to know what cyber security is and be able to implement it effectively. Without a safeguard to protect it, systems, sensitive files, data, and other critical virtual resources are at risk. Whether it is IT company or not, every company deserves equal protection. With modern technologies being developed in cybersecurity, attackers are not falling behind in the same way. They follow and enhance the best hacking techniques and target the weakness of many businesses out there. Cyber security is important because military, government, finance, medical, corporate organizations, and more like these organizations store and process their data on systems or PCs. Significant amounts of data can have sensitive information, financial information, intellectual property, personal information, and other kind of data for which an unknown access can cause various concerns. Knowledge of cyber security should be must at least for those who works for these kinds of firms to protect their data from cyber attackers

Human-centric cyber security: Applying protection motivation theory to analyse micro business owners’ security behaviours

Purpose The current advancements in technologies and the internet industry provide users with many innovative digital devices for entertainment, communication and trade. However, simultaneous development and the rising sophistication of cybercrimes bring new challenges. Micro businesses use technology like how people use it at home, but face higher cyber risks during riskier transactions, with human error playing a significant role. Moreover, information security researchers have often studied individuals’ adherence to compliance behaviour in response to cyber threats. The study aims to examine the protection motivation theory (PMT)-based model to understand individuals’ tendency to adopt secure behaviours. Design/methodology/approach The study focuses on Australian micro businesses since they are more susceptible to cyberattacks due to the least security measures in place. Out of 877 questionnaires distributed online to Australian micro business owners through survey panel provider “Dynata,” 502 (N = 502) complete responses were included. Structural equational modelling was used to analyse the relationships among the variables. Findings The results indicate that all constructs of the protection motivation, except threat susceptibility, successfully predict the user protective behaviours. Also, increased cybersecurity costs negatively impact users’ safe cyber practices. Originality/value The study has critical implications for understanding micro business owners’ cyber security behaviours. The study contributes to the current knowledge of cyber security in micro businesses through the lens of PMT.

Research on quality assessment methods for cybersecurity knowledge graphs

In light of the continuous evolution of cyber threats and the escalating frequency of cyberattacks, cybersecurity knowledge graphs have emerged as vital tools for comprehending and countering cyber threats. Nonetheless, the quality of these knowledge graphs is of paramount significance for their effectiveness in cybersecurity applications. This research proposes a Parameter-Efficient Knowledge Graphs Quality Assessment model (PEKGQA), aimed at evaluating the quality of cybersecurity knowledge graphs. We partition the knowledge graph into different communities and select reserved entities based on degree centrality within each community, and we only learn the embeddings of these reserved entities, significantly reducing the model's parameter size. Moreover, we leverage linkage relationships information and K-nearest neighbor information to encode all entities. Then we employ graph attention networks for the joint iterative update of entity and relation embeddings. This approach not only reduces the parameter count but also achieves excellent quality assessment results. Experimental outcomes demonstrate that the PEKGQA model-based approach significantly outperforms traditional methods in evaluation metrics such as F1 value and accuracy, providing an efficient and accurate solution for quality assessment in the field of cybersecurity knowledge graphs.

Automated Mapping of Common Vulnerabilities and Exposures to MITRE ATT&CK Tactics

Effectively understanding and categorizing vulnerabilities is vital in the ever-evolving cybersecurity landscape, since only one exposure can have a devastating effect on the entire system. Given the increasingly massive number of threats and the size of modern infrastructures, the need for structured, uniform cybersecurity knowledge systems arose. To tackle this challenge, the MITRE Corporation set up two powerful sources of cyber threat and vulnerability information, namely the Common Vulnerabilities and Exposures (CVEs) list focused on identifying and fixing software vulnerabilities, and the MITRE ATT&CK Enterprise Matrix, which is a framework for defining and categorizing adversary actions and ways to defend against them. At the moment, the two are not directly linked, even if such a link would have a significant positive impact on the cybersecurity community. This study aims to automatically map CVEs to the corresponding 14 MITRE ATT&CK tactics using state-of-the-art transformer-based models. Various architectures, from encoders to generative large-scale models, are employed to tackle this multilabel classification problem. Our results are promising, with a SecRoBERTa model performing best with an F1 score of 77.81%, which is closely followed by SecBERT (78.77%), CyBERT (78.54%), and TARS (78.01%), while GPT-4 showed a weak performance in zero-shot settings (22.04%). In addition, we perform an in-depth error analysis to better understand the models’ performance and limitations. We release the code used for all experiments as open source.

Cybersecurity Knowledge Deterioration and the role of Gamification Intervention

Cybersecurity is becoming an overly critical issue in contemporary times. Cyberspace safety is declining, and this covers all categories of persons, businesses, institutions, and even the government. Deterioration in cybersecurity knowledge and awareness has led people to become easy prey/victims of cybercrime. The more novel security systems are being developed, the higher the cyberattacks as hackers, scammers, and cybercriminals are innovative in their techniques to attack cyber-users. It is therefore paramount to investigate the stance of cybersecurity knowledge among the general IT (Information Technology) users, especially in the 21st century. This paper designed a cybersecurity quiz based on adaptations from literature and past cybersecurity quizzes and conducted investigations to test the knowledge of random cyber-users via the cybersecurity quiz. Results from investigations are quite surprising and instructive, thus serving as a propelling motivation to develop a cybersecurity game. Among the 10-questionnaire cybersecurity quiz, it was discovered that most cyber-users lack knowledge about network security. Also, the question on social engineering was not well performed by the respondents. Thus, it is important for upcoming innovations to take into consideration the aspects of network security, social engineering when designing cybersecurity gamification approaches. Gamification has been used as teaching aids for diverse learning fields, however the use of games in cybersecurity is still understudied. Thus, the result of this quiz is intended to be used to further boost the development of a cybersecurity game, which can be age centric, thus developing cybersecurity games that will be suitable for specific user groups. Interestingly, though females were not regular game players, however they were highly interested in playing a cybersecurity game, as majority of cyber-users (males inclusive), believed that a cybersecurity knowledge gamification approach can help enhance their cybersecurity knowledge and awareness. Conclusively, it is obvious that both the young and old still lack basic cybersecurity knowledge, thereby making them easy prey for cyberattacks. Gamification if applied properly into cybersecurity, could be an interactive learning platform that is both enjoyable, produces a high spirit of learning as well as help serve as a strong awareness tool that can boost cybersecurity user’s knowledge.