What Skills Do Cyber Security Professionals Need?
- URL: http://arxiv.org/abs/2502.13658v2
- Date: Thu, 20 Feb 2025 10:56:59 GMT
- Title: What Skills Do Cyber Security Professionals Need?
- Authors: Faheem Ullah, Xiaohan Ye, Uswa Fatima, Zahid Akhtar, Yuxi Wu, Hussain Ahmad,
- Abstract summary: The increasing number of cyber-attacks has elevated the importance of cybersecurity for organizations.
Many individuals are looking to enter the field of cybersecurity.
However, there is a lack of clear understanding of the skills required for a successful career in this field.
- Score: 10.615987702194944
- License:
- Abstract: Purpose: The increasing number of cyber-attacks has elevated the importance of cybersecurity for organizations. This has also increased the demand for professionals with the necessary skills to protect these organizations. As a result, many individuals are looking to enter the field of cybersecurity. However, there is a lack of clear understanding of the skills required for a successful career in this field. In this paper, we identify the skills required for cybersecurity professionals. We also determine how the demand for cyber skills relates to various cyber roles such as security analyst and security architect. Furthermore, we identify the programming languages that are important for cybersecurity professionals. Design/Methodology: For this study, we have collected and analyzed data from 12,161 job ads and 49,002 Stack Overflow posts. By examining this, we identified patterns and trends related to skill requirements, role-specific demands, and programming languages in cybersecurity. Findings: Our results reveal that (i) communication skills and project management skills are the most important soft skills, (ii) as compared to soft skills, the demand for technical skills varies more across various cyber roles, and (iii) Java is the most commonly used programming language. Originality: Our findings serve as a guideline for individuals aiming to get into the field of cybersecurity. Moreover, our findings are useful in terms of informing educational institutes to teach the correct set of skills to students doing degrees in cybersecurity.
Related papers
- CyberMentor: AI Powered Learning Tool Platform to Address Diverse Student Needs in Cybersecurity Education [6.267144136593821]
Many non-traditional students in cybersecurity programs often lack access to advice from peers, family members and professors.
This paper introduces an application designed to provide comprehensive support by answering questions related to knowledge, skills, and career preparation advice.
We developed a learning tool platform, CyberMentor, to address the diverse needs and pain points of students in cybersecurity.
arXiv Detail & Related papers (2025-01-16T18:00:06Z) - Open Problems in Machine Unlearning for AI Safety [61.43515658834902]
Machine unlearning -- the ability to selectively forget or suppress specific types of knowledge -- has shown promise for privacy and data removal tasks.
In this paper, we identify key limitations that prevent unlearning from serving as a comprehensive solution for AI safety.
arXiv Detail & Related papers (2025-01-09T03:59:10Z) - Towards Type Agnostic Cyber Defense Agents [0.0]
Cyber threats have continued to grow, leading to labor shortages and a skills gap in cybersecurity.
Many cybersecurity product vendors and security organizations have looked to artificial intelligence to shore up their defenses.
This work considers how to characterize attackers and defenders in one approach to the automation of cyber defense.
arXiv Detail & Related papers (2024-12-02T14:32:18Z) - CyberPal.AI: Empowering LLMs with Expert-Driven Cybersecurity Instructions [0.2999888908665658]
Large Language Models (LLMs) have significantly advanced natural language processing (NLP) capabilities, providing versatile capabilities across various applications.
However, their application to complex, domain-specific tasks, such as cyber-security, often faces substantial challenges.
In this study, we introduce SecKnowledge and CyberPal.AI to address these challenges and train security-expert LLMs.
arXiv Detail & Related papers (2024-08-17T22:37:39Z) - An Actionable Framework for Understanding and Improving Talent Retention
as a Competitive Advantage in IT Organizations [44.342141516382284]
This work presents an actionable framework for Talent Retention (TR) used in IT organizations.
Our framework encompasses a set of factors, contextual characteristics, barriers, strategies, and coping mechanisms.
Our findings indicated that software engineers can be differentiated from other professional groups.
arXiv Detail & Related papers (2024-02-02T17:08:14Z) - Requirements for a Career in Information Security: A Comprehensive
Review [0.0]
The primary objective is to increase public awareness regarding the diverse opportunities available in the Information Security (IS) field.
Thematic analysis was conducted on these studies to identify and delineate the crucial knowledge and skills that an IS professional should possess.
The study recognizes the existence of gender-related obstacles for women pursuing cybersecurity careers due to the field's unique requirements.
arXiv Detail & Related papers (2024-01-07T16:41:13Z) - Cybersecurity Career Requirements: A Literature Review [0.0]
The research found that a considerable investment in time is necessary for cybersecurity professionals to reach the required technical proficiency.
It also identified female gender barriers to cybersecurity careers due to the unique requirements of the field.
arXiv Detail & Related papers (2023-06-16T02:58:29Z) - Graph Mining for Cybersecurity: A Survey [61.505995908021525]
The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society.
Traditional Machine Learning (ML) based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities.
With the proliferation of graph mining techniques, many researchers investigated these techniques for capturing correlations between cyber entities and achieving high performance.
arXiv Detail & Related papers (2023-04-02T08:43:03Z) - Proceedings of the Artificial Intelligence for Cyber Security (AICS)
Workshop at AAAI 2022 [55.573187938617636]
The workshop will focus on the application of AI to problems in cyber security.
Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
arXiv Detail & Related papers (2022-02-28T18:27:41Z) - 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) - Adversarial Machine Learning Attacks and Defense Methods in the Cyber
Security Domain [58.30296637276011]
This paper summarizes the latest research on adversarial attacks against security solutions based on machine learning techniques.
It is the first to discuss the unique challenges of implementing end-to-end adversarial attacks in the cyber security domain.
arXiv Detail & Related papers (2020-07-05T18:22:40Z)
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.