2019
DOI: 10.1016/j.ifacol.2019.12.169
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Using Technical Cybersecurity Exercises in University Admissions and Skill Evaluation

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Cited by 4 publications
(3 citation statements)
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“…Throughout this section, we refer to Table 1 and Table 2, which summarize the results. Burket, Chapman, Becker, Ganas, and Brumley (2015) offense detect cheating in a CTF by analyzing sharing of solutions P7 Weiss, Locasto, and Mache (2016) offense assess learners by visualizing their command history as a directed graph P9 Vykopal and Barták (2016) offense determine what information can be predicted from logs of 260 trainees P11 Tseng et al (2017) offense analyze learners' behavior in a CTF to reveal their misconceptions P12 Caliskan, Tatar, Bahsi, Ottis, and Vaarandi (2017) offense determine metrics from exercise logs that will predict students' grade P14 Andreatos (2017) offense analyze students' network activity in a lab to review their actions P16 Kont, Pihelgas, Maennel, Blumbergs, and Lepik (2017) offense provide and evaluate feedback for the attacking teams in a CDX P18 Chothia, Holdcroft, Radu, and Thomas (2017) offense determine if storyline in a cybersecurity training improves learning P19 Tian et al (2018) offense provide trainees with situational awareness of the training P21 Švábenský and Vykopal (2018a) offense determine if trainees fulfill prerequisites of security training P22 Švábenský and Vykopal (2018b) offense analyze how trainees interact with security training tasks and tools P25 Andreolini, Colacino, Colajanni, and Marchetti (2019) offense assess trainees by comparing their actions to a reference solution P26 Falah, Pan, and Chen (2019) offense estimate the difficulty of attacks and measure skills of trainees P28 Maennel, Mäses, Sütterlin, Ernits, and Maennel (2019) offense, network security assess students who apply to a cybersecurity master degree program P31 offense, forensics, network security compare assessment of students who did / did not participate in a CTF P34 Kaneko et al (2020) offense, forensics evaluate an intensive cybersecurity course based on student performance P35 Yett et al (2020) offense, secure programming analyze how students collaborate in group programming tasks P2 Reed, Nauer, and Silva (2013) forensics analyze score distribution, submission delay, and frustration in a CTF P6 Abbott et al (2015) forensics quantitatively analyze student actions and performance in security training P1 Rupp et al (2012) network security identify skill profiles of students based on logs and submitted commands P23 Zeng, Deng, Hsiao, Huang, and Chung (2018) network security compare student grades with the time they spent working on lab tasks P24 Deng, Lu, Chung, Huang, and network security adapt instruction to...…”
Section: Resultsmentioning
confidence: 99%
“…Throughout this section, we refer to Table 1 and Table 2, which summarize the results. Burket, Chapman, Becker, Ganas, and Brumley (2015) offense detect cheating in a CTF by analyzing sharing of solutions P7 Weiss, Locasto, and Mache (2016) offense assess learners by visualizing their command history as a directed graph P9 Vykopal and Barták (2016) offense determine what information can be predicted from logs of 260 trainees P11 Tseng et al (2017) offense analyze learners' behavior in a CTF to reveal their misconceptions P12 Caliskan, Tatar, Bahsi, Ottis, and Vaarandi (2017) offense determine metrics from exercise logs that will predict students' grade P14 Andreatos (2017) offense analyze students' network activity in a lab to review their actions P16 Kont, Pihelgas, Maennel, Blumbergs, and Lepik (2017) offense provide and evaluate feedback for the attacking teams in a CDX P18 Chothia, Holdcroft, Radu, and Thomas (2017) offense determine if storyline in a cybersecurity training improves learning P19 Tian et al (2018) offense provide trainees with situational awareness of the training P21 Švábenský and Vykopal (2018a) offense determine if trainees fulfill prerequisites of security training P22 Švábenský and Vykopal (2018b) offense analyze how trainees interact with security training tasks and tools P25 Andreolini, Colacino, Colajanni, and Marchetti (2019) offense assess trainees by comparing their actions to a reference solution P26 Falah, Pan, and Chen (2019) offense estimate the difficulty of attacks and measure skills of trainees P28 Maennel, Mäses, Sütterlin, Ernits, and Maennel (2019) offense, network security assess students who apply to a cybersecurity master degree program P31 offense, forensics, network security compare assessment of students who did / did not participate in a CTF P34 Kaneko et al (2020) offense, forensics evaluate an intensive cybersecurity course based on student performance P35 Yett et al (2020) offense, secure programming analyze how students collaborate in group programming tasks P2 Reed, Nauer, and Silva (2013) forensics analyze score distribution, submission delay, and frustration in a CTF P6 Abbott et al (2015) forensics quantitatively analyze student actions and performance in security training P1 Rupp et al (2012) network security identify skill profiles of students based on logs and submitted commands P23 Zeng, Deng, Hsiao, Huang, and Chung (2018) network security compare student grades with the time they spent working on lab tasks P24 Deng, Lu, Chung, Huang, and network security adapt instruction to...…”
Section: Resultsmentioning
confidence: 99%
“…The second literature category focuses on the investigation and education of teenagers' ISA. Maennel et al (2019) believe that it is far from enough to put ISA education at the college level. Both the awareness and ability of cybersecurity should be taught and developed as an essential skill among children.…”
Section: Related Studiesmentioning
confidence: 99%
“…Without independent object or methods, fuelled by political ambitions, this quasi-discipline trends towards Virilio's (2000, p. 3) extreme science, exiling other disciplines from their reason. Maennel's (2019) thoughts help illustrate the composition of cybersecurity: from computer science it takes secure software design, or understanding how to build intrusion detection systems as well as methods for vulnerability testing; cryptography is rooted in mathematics; psychology helps to understand human factors; aspects of forensic science are used by law enforcement agencies; social sciences, business and economic understanding are essential to the design and marketing IT products and services; operational and strategic risk management models and audits help with reducing the threats in day-to-day operations; legal and political disciplines offer frameworks for directing broader societal trends and addressing unwanted consequences. This analysis leads Maennel to conclude that cybersecurity has become simply an expression for interdisciplinary attention to the development and use of ICTs.…”
Section: The Influence Of China On Cybersecurity In Africamentioning
confidence: 99%