A Survey-Based Quantitative Analysis of Stress Factors and Their Impacts Among Cybersecurity Professionals

• URL: http://arxiv.org/abs/2409.12047v1
• Date: Wed, 18 Sep 2024 15:18:33 GMT
• Title: A Survey-Based Quantitative Analysis of Stress Factors and Their Impacts Among Cybersecurity Professionals
• Authors: Sunil Arora, John D. Hastings,
• Abstract summary: This study investigates the prevalence and underlying causes of work-related stress and burnout among cybersecurity professionals. 44% report experiencing severe work-related stress and burnout, while an additional 28% are uncertain about their condition. The demanding nature of cybersecurity roles, unrealistic expectations, and unsupportive organizational cultures emerge as primary factors fueling this crisis.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study investigates the prevalence and underlying causes of work-related stress and burnout among cybersecurity professionals using a quantitative survey approach guided by the Job Demands-Resources model. Analysis of responses from 50 cybersecurity practitioners reveals an alarming reality: 44% report experiencing severe work-related stress and burnout, while an additional 28% are uncertain about their condition. The demanding nature of cybersecurity roles, unrealistic expectations, and unsupportive organizational cultures emerge as primary factors fueling this crisis. Notably, 66% of respondents perceive cybersecurity jobs as more stressful than other IT positions, with 84% facing additional challenges due to the pandemic and recent high-profile breaches. The study finds that most cybersecurity experts are reluctant to report their struggles to management, perpetuating a cycle of silence and neglect. To address this critical issue, the paper recommends that organizations foster supportive work environments, implement mindfulness programs, and address systemic challenges. By prioritizing the mental health of cybersecurity professionals, organizations can cultivate a more resilient and effective workforce to protect against an ever-evolving threat landscape.

Related papers

• New Emerged Security and Privacy of Pre-trained Model: a Survey and Outlook [54.24701201956833]
  Security and privacy issues have undermined users' confidence in pre-trained models. Current literature lacks a clear taxonomy of emerging attacks and defenses for pre-trained models. This taxonomy categorizes attacks and defenses into No-Change, Input-Change, and Model-Change approaches.
  arXiv  Detail & Related papers  (2024-11-12T10:15:33Z)
• Exploring the Cybersecurity-Resilience Gap: An Analysis of Student Attitudes and Behaviors in Higher Education [0.0]
  This study addresses the gap using the Theory of Behavior as a theoretical framework. A modified Human Aspects of Information Security Questionnaire was employed to gather 266 valid responses from undergraduate and postgraduate students. Key dimensions of cybersecurity awareness and behavior, including password management, email usage, social media practices, and mobile device security, were assessed.
  arXiv  Detail & Related papers  (2024-11-05T16:09:37Z)
• Alignment of Cybersecurity Incident Prioritisation with Incident Response Management Maturity Capabilities [0.0]
  This paper explores a possible utilisation of IR CMMs assessments to prioritise high-risk incidents. The findings reveal common weaknesses in incident response, such as inadequate training and poor communication. The analysis also emphasises the importance of organisational culture in enhancing incident response capabilities.
  arXiv  Detail & Related papers  (2024-10-03T07:05:47Z)
• Cybersecurity Challenge Analysis of Work-from-Anywhere (WFA) and Recommendations guided by a User Study [1.1749564892273827]
  Many organizations were forced to quickly transition to the work-from-anywhere (WFA) model as a necessity to continue with their operations and remain in business despite the restrictions imposed during the COVID-19 pandemic. This paper attempts to uncover some challenges and implications related to the cybersecurity of the WFA model. We conducted an online user study to investigate the readiness and cybersecurity awareness of employers and their employees who shifted to work remotely from anywhere.
  arXiv  Detail & Related papers  (2024-09-11T18:47:04Z)
• Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science [65.77763092833348]
  Intelligent agents powered by large language models (LLMs) have demonstrated substantial promise in autonomously conducting experiments and facilitating scientific discoveries across various disciplines. While their capabilities are promising, these agents also introduce novel vulnerabilities that demand careful consideration for safety. This paper conducts a thorough examination of vulnerabilities in LLM-based agents within scientific domains, shedding light on potential risks associated with their misuse and emphasizing the need for safety measures.
  arXiv  Detail & Related papers  (2024-02-06T18:54:07Z)
• PsySafe: A Comprehensive Framework for Psychological-based Attack, Defense, and Evaluation of Multi-agent System Safety [70.84902425123406]
  Multi-agent systems, when enhanced with Large Language Models (LLMs), exhibit profound capabilities in collective intelligence. However, the potential misuse of this intelligence for malicious purposes presents significant risks. We propose a framework (PsySafe) grounded in agent psychology, focusing on identifying how dark personality traits in agents can lead to risky behaviors. Our experiments reveal several intriguing phenomena, such as the collective dangerous behaviors among agents, agents' self-reflection when engaging in dangerous behavior, and the correlation between agents' psychological assessments and dangerous behaviors.
  arXiv  Detail & Related papers  (2024-01-22T12:11:55Z)
• Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns [13.075370397377078]
  We use ongoing work on the Cyber Security Body of Knowledge (CyBOK) to help elicit and document the responsibilities and ethics of the profession. Based on a literature review of the ethics of cybersecurity, we use CyBOK to frame the exploration of ethical challenges in the cybersecurity profession. Our findings indicate that there are broad ethical challenges across the whole of cybersecurity, but also that different areas of cybersecurity can face specific ethical considerations.
  arXiv  Detail & Related papers  (2023-11-16T19:44:03Z)
• Unaware, Unfunded and Uneducated: A Systematic Review of SME Cybersecurity [1.556652483029531]
  We focus on research discussing cyber threats, adopted controls, challenges, and constraints SMEs face in pursuing cybersecurity resilience. Research on SMEs is shallow and has made little progress in understanding SMEs' roles, threats, and needs. Main challenges to attaining cybersecurity resilience of SMEs are a lack of awareness of the cybersecurity risks, limited cybersecurity literacy and constrained financial resources.
  arXiv  Detail & Related papers  (2023-09-29T12:32:49Z)
• On the Security Risks of Knowledge Graph Reasoning [71.64027889145261]
  We systematize the security threats to KGR according to the adversary's objectives, knowledge, and attack vectors. We present ROAR, a new class of attacks that instantiate a variety of such threats. We explore potential countermeasures against ROAR, including filtering of potentially poisoning knowledge and training with adversarially augmented queries.
  arXiv  Detail & Related papers  (2023-05-03T18:47:42Z)
• The Role of Robotics in Infectious Disease Crises [46.43737882437637]
  The recent coronavirus pandemic has highlighted the challenges faced by the healthcare, public safety, and economic systems when confronted with a surge in patients. There is a complementary need to anticipate and address the engineering challenges associated with infectious disease emergencies. As technical capabilities advance and as the installed base of robotic systems increases in the future, they could play a much more significant role in future crises.
  arXiv  Detail & Related papers  (2020-10-19T22:54:12Z)
• Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
  Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance. We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems. We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
  arXiv  Detail & Related papers  (2020-10-19T13:09:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.