What do incident response practitioners need to know? A skillmap for the years ahead

Hranický, Radek; Breitinger, Frank; Ryšavý, Ondřej; Sheppard, John; Schaedler, Florin; Morgenstern, Holger; Malik, Simon

doi:10.1016/j.fsidi.2021.301184

Cited by 7 publications

(12 citation statements)

References 6 publications

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“…However, the results do not match each other [46]. There is another study that uses a skill map to calculate skill rankings from frequencies of crucial skills [47]. Also, the skill evaluation tool is introduced based on the 1-5 point rating scale for the future work skill profile for software engineer and developer skills, without considering the role or level [25].…”

Section: Skill Evaluationmentioning

confidence: 99%

“…However, there were less than 100 data available as a total for both SME and WDA categories in the initial stage and they were collected later before starting their analysis. Also, another study found that entry-level data availability on LinkedIn was small compared with senior levels [47]. The sample size was calculated using an online tool by adding the LinkedIn estimated interested population size as 3689, where the confidence level and margin of error were set as 95% and 3%, respectively.…”

Section: Datasetmentioning

confidence: 99%

“…A similar kind of structure was used to list data extracted from LinkedIn in Ref. [47]. Salary was recorded into minimum and maximum as a range.…”

Section: Data Cleansingmentioning

confidence: 99%

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The Impact of a Skill-Driven Model on Scrum Teams in Software Projects: A Catalyst for Digital Transformation

Haputhanthrige,

Asghar,

Saleem

et al. 2024

Systems

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Human skills are a critical factor in the success or failure of a digital project. Limited studies have been conducted to identify the industry demand for skills of scrum roles (product owner, scrum master, web developer) and levels (entry, associate, mid-senior). The evaluation of skills over time benefits both decision-makers and associated team members, which leads to successful project completions. The aim of this research is to improve decision making concerning the level-specific skills of selected scrum roles for digital projects. The study identifies major and minor skills, patterns, and relationships between levels, and formulates the mathematical equations as the most important inputs to the skill-driven model’s implementation and evaluation. Both qualitative and quantitative research methods were used to analyse 900 surveyed job advertisements published on LinkedIn in Europe. Descriptive analysis was used to analyse quantitative data while the deductive approach was followed with thematic analysis. There are required skill sets for each level of roles, level-specific skills, industry-demanded skills, and formulas related to the initial and individual skill ratings that are investigated. A new mechanism for evaluation is introduced based on “the time spent with skills”. As a result, the proposed model is implemented by feeding research findings into the Mendix programming platform. The skill-driven model is a decision-support solution in software project management to evaluate skills which assist in assigning the right person to the right digital project. Further investigation on different job portals can help to improve the accuracy of industry standards and reduce the lack of progression skills by overcoming limitations identified in this paper.

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Section: Skill Evaluationmentioning

confidence: 99%

Section: Datasetmentioning

confidence: 99%

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The Impact of a Skill-Driven Model on Scrum Teams in Software Projects: A Catalyst for Digital Transformation

Haputhanthrige,

Asghar,

Saleem

et al. 2024

Systems

View full text Add to dashboard Cite

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“…Text mining approaches have also been used to compare skill sets in different branches of the IT industry [11], mapping skills to different professional roles [13], design and analysis of curricula [14], as well as for longitudinal studies of industrial skill demands [16], to name only a few exemplary works. An example of a hybrid approach combining surveys with job ad and curricula analysis based on a manual skill taxonomy can be found in recent work on skill requirements in digital forensics [17].…”

Section: Related Workmentioning

confidence: 99%

Towards Understanding the Skill Gap in Cybersecurity

Goupil¹,

Laskov²,

Pekaric³

et al. 2022

Preprint

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Given the ongoing "arms race" in cybersecurity, the shortage of skilled professionals in this field is one of the strongest in computer science. The currently unmet staffing demand in cybersecurity is estimated at over 3 million jobs worldwide. Furthermore, the qualifications of the existing workforce are largely believed to be insufficient. We attempt to gain deeper insights into the nature of the current skill gap in cybersecurity. To this end, we correlate data from job ads and academic curricula using two kinds of skill characterizations: manual definitions from established skill frameworks as well as "skill topics" automatically derived by text mining tools. Our analysis shows a strong agreement between these two analysis techniques and reveals a substantial undersupply in several crucial skill categories, e.g., software and application security, security management, requirements engineering, compliance and certification. Based on the results of our analysis, we provide recommendations for future curricula development in cybersecurity so as to decrease the identified skill gaps.

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“…On the academic side, the UK Cyber Security Council (2023) references "problem solving" and "logical thinking" as required skills. Hranický et al (2021) work to develop a skillsmap in the incident response arena has highlighted critical thinking as an important non-technical skill and Salt et al (2011) provide emphasis on "investigative skills rather than investigative tools" in their curriculum. Sachowski's (2019) educational roadmap highlights critical thinking and analytical skills as important facets of the practitioner.…”

Section: Introductionmentioning

confidence: 99%

Fostering an “investigating mindset”: Why is it important in digital forensic science education?

Horsman,

Ryser,

Shavers

2023

WIREs Forensic Science

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The importance of the field of digital forensics (DF) is growing, where digital evidence is increasingly recognized as a crucial part of many investigations. As a result, criminal justice systems rely on DF practitioners to conduct robust investigations of digital devices and their data, and interpret and present these results in a way that can be relied upon. Undertaking this task appropriately requires a practitioner to have a range of skills; however, focus is often placed on the need for and importance of technical competency. Technical skills are vital in this role, that cannot be in dispute; however, this work discusses the need for practitioners to also have an “investigative mindset.”This article is categorized under: Digital and Multimedia Science > Cybercrime Investigation

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What do incident response practitioners need to know? A skillmap for the years ahead

Cited by 7 publications

References 6 publications

The Impact of a Skill-Driven Model on Scrum Teams in Software Projects: A Catalyst for Digital Transformation

The Impact of a Skill-Driven Model on Scrum Teams in Software Projects: A Catalyst for Digital Transformation

Towards Understanding the Skill Gap in Cybersecurity

Fostering an “investigating mindset”: Why is it important in digital forensic science education?

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