For undergraduate students of computing, learning to solve complex practical problems in a team is an essential skill for their future careers. This skill is needed in various fields, such as in cybersecurity and IT governance. Tabletop exercises are an innovative teaching method used in practice for training teams in incident response and evaluation of contingency plans. However, tabletop exercises are not yet widely established in university education. This paper presents data and teaching experience from a cybersecurity course that introduces tabletop exercises in classrooms using a novel technology: INJECT Exercise Platform (IXP), a web-based learning environment for delivering and evaluating the exercises. This technology substantially improves the prior practice, since tabletop exercises worldwide have usually been conducted using pen and paper. Unlike in traditional tabletop exercises, which are difficult to evaluate manually, IXP provides insights into students' behavior and learning based on automated analysis of interaction data. We demonstrate IXP's capabilities and evolution by comparing exercise sessions hosted throughout three years at different stages of the platform's readiness. The analysis of student data is supplemented by the discussion of the lessons learned from employing IXP in computing education contexts. The data analytics enabled a detailed comparison of the teams' performance and behavior. Instructors who consider innovating their classes with tabletop exercises may use IXP and benefit from the insights in this paper.

Tabletop exercises are used to train personnel in the efficient mitigation and resolution of incidents. They are applied in practice to support the preparedness of organizations and to highlight inefficient processes. Since tabletop exercises train competencies required in the workplace, they have been introduced into computing courses at universities as an innovation, especially within cybersecurity curricula. To help computing educators adopt this innovative method, we survey academic publications that deal with tabletop exercises. From 140 papers we identified and examined, we selected 14 papers for a detailed review. The results show that the existing research deals predominantly with exercises that follow a linear format and exercises that do not systematically collect data about trainees' learning. Computing education researchers can investigate novel approaches to instruction and assessment in the context of tabletop exercises to maximize the impact of this teaching method. Due to the relatively low number of published papers, the potential for future research is immense. Our review provides researchers, tool developers, and educators with an orientation in the area, a synthesis of trends, and implications for further work.

As cyber threats endanger everyone, from regular users to computing professionals, spreading cybersecurity awareness becomes increasingly critical. Therefore, our university designed an innovative cybersecurity awareness course that is freely available online for students, employees, and the general public. The course offers simple, actionable steps that anyone can use to implement defensive countermeasures. Compared to other resources, the course not only suggests learners what to do, but explains why and how to do it. To measure the course impact, we administered it to 138 computer science undergraduates within a compulsory information security and cryptography course. They completed the course as a part of their homework and filled out a questionnaire after each lesson. Analysis of the questionnaire responses revealed that the students valued the course highly. They reported new learning, perspective changes, and transfer to practice. Moreover, they suggested suitable improvements to the course. Based on the results, we have distilled specific insights to help security educators design similar courses. Lessons learned from this study are relevant for cybersecurity instructors, course designers, and educational managers.

In this article, we discuss the issues of GDPR's impact on cyber-security software and operations, namely automated information sharing. We illustrate the topic on an example of an intrusion detection alert sharing platform. First, we had to investigate the risks to privacy in the alert sharing platform and ensure its compliance with the GDPR's obligations. Second, fears and uncertainties emerged in the alert sharing community regarding the GDPR and its obligations and, thus, willingness to share the information was negatively impacted. We conducted DPIA to investigate risks related to information sharing in cyber security and dismiss doubts within the community. Although our results suggest that the risks are not high, we point out that the hype around GDPR caused substantial development of the sharing platform. The DPIA helped in a deeper understanding of risks and their management and is a solid argument for information sharing in cyber security under GDPR.

In order to ensure confidentiality, integrity and availability (so called CIA triad) of data within network infrastructure, it is necessary to be able to detect and handle cyber security incidents. For this purpose, it is vital for Computer Security Incident Response Teams (CSIRT) to have enough data on relevant security events and threats. That is why CSIRTs share security alerts and incidents data using various sharing platforms. Even though they do so primarily to protect data and privacy of users, their use also lead to additional processing of personal data, which may cause new privacy risks. European data protection law, especially with the adoption of the new General data protection regulation, sets out very strict rules on processing of personal data which on one hand leads to greater protection of individual's rights, but on the other creates great obstacles for those who need to share any personal data. This paper analyses the General Data Protection Regulation (GDPR), relevant case-law and analyses by the Article 29 Working Party to propose optimal methods and level of personal data processing necessary for effective use of security alert sharing platforms, which would be legally compliant and lead to appropriate balance between risks.