Article Review: Tackling APTs and Cybersecurity Vulnerabilities

Chris Heckman
Old Dominion University
CYSE 201
Mr. Aslan
2/5/2024

Introduction

The integrity, confidentiality, and availability of the organizational data and services by advanced persistent threats (APTs) and the use of sophisticated cybersecurity vulnerability exploitation is a significant challenge. This article review juxtaposes two scholarly works: For instance, the articles ‘Harnessing Large Language Models to Simulate Realistic Human Responses to Social Engineering Attacks: A Case Study’ by Asfour & Murillo and ‘A Systematic Literature Review on Advanced Persistent Threat Behaviors and its Detection Strategy’ by Che Mat et al. investigate new ways of counteracting APTs, where
Relation to Social Sciences Principles
The topic of cybersecurity, specifically the study of APTs and the utilization of large language models (LLMs) for simulating human responses to social engineering, interlaces closely with the principles of social sciences. It underscores the pivotal role of understanding human behavior, psychology, and social engineering tactics, which are central to both perpetrating and defending against cyber-attacks. The studies encapsulate the dynamic interplay between technology and human factors, presenting a multidisciplinary approach that integrates insights from criminology, psychology, and information technology.
Research Questions and Hypotheses
Asfour & Murillo’s Study:
Research Question: How do personality traits influence susceptibility to social engineering attacks?
Hypothesis: Individuals with certain personality traits, as defined by the Big Five, show varying levels of susceptibility to social engineering attacks, with traits like high agreeableness and extraversion potentially leading to higher vulnerability.
Che Mat et al.’s Study:
Research Question: How can understanding APT behaviors and detection strategies improve cybersecurity defenses?
Hypothesis: A detailed review of APT behaviors and existing detection strategies will highlight weaknesses in current approaches and suggest improvements for more effective defense mechanisms against APTs.
Both studies seek to identify and mitigate vulnerabilities—Asfour & Murillo by examining human factors in social engineering attacks, and Che Mat et al. by analyzing strategies for detecting and defending against APTs.
Research Methods and Data Analysis
Asfour & Murillo (2023), employed LLMs to create simulations, reflecting an innovative use of generative AI for cybersecurity research. Che Mat et al. (2024), systematic literature review method, guided by PRISMA protocols, offers a comprehensive analysis of APT detection techniques, leveraging academic and industry insights to map out current trends and gaps in APT mitigation strategies.
Contribution to Understanding Marginalized Groups’ Concerns
While neither article directly addresses the concerns of marginalized groups, the implications of their research are significant for broader societal protection. Improved understanding and mitigation of APTs and social engineering attacks contribute to a safer digital environment for all, including vulnerable populations who may be disproportionately affected by cybercrime.
Societal Contributions
These researchers contribute to society by improving our knowledge about cyber threats and defense measures. Work by Asfour et al. (2023) on simulating human reactions to phishing presents an example of the necessity of cybersecurity education and awareness programs to be fit for the specifics of the attack. APT detection approaches, which clearly state the importance of the holistic approach reminds Che Mat et al. (2024), review that the complete solution includes the behavioral analysis, vulnerability assessment, and systems involving the methods of the advanced APT detection. With these edits in mind, the conferment of all the contributions can inform a new approach in cybersecurity policy development as well as in marketing innovative tools and practices to benefit societies and individuals.
Conclusion
In summary, APTs’ comprehension, human factors issue in cybersecurity, and intersection of APTs are augmented through access to the reviewed articles. However, by overcoming the gap and realizing that technological vulnerabilities are the effects of human behavior, they open up the horizon that more advanced and productive mitigation strategies for cyber threats are possible. Studies conducted in the future will, therefore, need to focus on aspects such as the Artificial Intelligence-assisted detection tactics and the need for education in developing cyber resilience.

References
Asfour, M., & Murillo, J. C. (2023). Harnessing large language models to simulate realistic human responses to social engineering attacks: A case study. International Journal of Cybersecurity Intelligence & Cybercrime, 6(2), 21-49.
Che Mat, N. I., Jamil, N., Yusoff, Y., & Mat Kiah, M. L. (2024). A systematic literature review on advanced persistent threat behaviors and its detection strategy. Journal of Cybersecurity, 10(1), tyad023.