The gender gap in cybersecurity remains a persistent and concerning issue. Despite efforts to promote diversity and inclusivity, women remain significantly underrepresented in cybersecurity roles. One of the primary factors contributing to the gender gap in cybersecurity is the lack of female representation and encouragement in STEM (Science, Technology, Engineering, and Mathematics) fields. Stereotypes and societal biases often dissuade girls and young women from pursuing careers in these fields, leading to a smaller pool of women candidates entering the cybersecurity workforce.

The gender gap is one of the main concerns in the IT sector, in general, and in cybersecurity, in particular. Although well known, the problem is multifaceted and some of its root causes may be found in the education system. In the last years, many initiatives have been proposed targeting high-school students that might be interested in cybersecurity. Many of these programs rely on capture-the-flag (CTF) competitions to gradually form technical skills in an entertaining way. Despite these efforts, however, the number of girls that attend and complete these programs is still often unsatisfactory.

Abstract This paper advocates the use of compositional specifications based on formal languages as a means of modelling and analysing sophisticated collective behaviour in natural systems. With the use of appropriate linguistic constructs, models can be developed that are both compact and intuitive, and can be easily refined and extended in small steps. Automated workflows can be implemented on top of this methodology to provide quick feedback, enabling rapid design iterations. To support our argument, we present three examples from the natural world, focusing on flocks of birds and colonies of ants, which feature well-known examples of emergent behaviour in collective adaptive systems. We use an agent-based language to develop simple models that aim at capturing these collective phenomena, and discuss the specific language constructs that we use in the process. Then, we adapt an existing verification tool for the language to simulate our models, and show that our simulations do display emergent behaviour.