TY - GEN
T1 - ConGISATA
T2 - 28th European Symposium on Research in Computer Security, ESORICS 2023
AU - Cohen, Ofir
AU - Bitton, Ron
AU - Shabtai, Asaf
AU - Puzis, Rami
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - The incidence of cybersecurity attacks utilizing social engineering techniques has increased. Such attacks exploit the fact that in every secure system, there is at least one individual with the means to access sensitive information. Since it is easier to deceive a person than it is to bypass the defense mechanisms in place, these types of attacks have gained popularity. This situation is exacerbated by the fact that people are more likely to take risks in their passive form, i.e., risks that arise due to the failure to perform an action. Passive risk has been identified as a significant threat to cybersecurity. To address these threats, there is a need to strengthen individuals’ information security awareness (ISA). Therefore, we developed ConGISATA - a continuous gamified ISA training and assessment framework based on embedded mobile sensors; a taxonomy for evaluating mobile users’ security awareness served as the basis for the sensors’ design. ConGISATA’s continuous and gradual training process enables users to learn from their real-life mistakes and adapt their behavior accordingly. ConGISATA aims to transform passive risk situations (as perceived by an individual) into active risk situations, as people tend to underestimate the potential impact of passive risks. Our evaluation of the proposed framework demonstrates its ability to improve individuals’ ISA, as assessed by the sensors and in simulations of common attack vectors.
AB - The incidence of cybersecurity attacks utilizing social engineering techniques has increased. Such attacks exploit the fact that in every secure system, there is at least one individual with the means to access sensitive information. Since it is easier to deceive a person than it is to bypass the defense mechanisms in place, these types of attacks have gained popularity. This situation is exacerbated by the fact that people are more likely to take risks in their passive form, i.e., risks that arise due to the failure to perform an action. Passive risk has been identified as a significant threat to cybersecurity. To address these threats, there is a need to strengthen individuals’ information security awareness (ISA). Therefore, we developed ConGISATA - a continuous gamified ISA training and assessment framework based on embedded mobile sensors; a taxonomy for evaluating mobile users’ security awareness served as the basis for the sensors’ design. ConGISATA’s continuous and gradual training process enables users to learn from their real-life mistakes and adapt their behavior accordingly. ConGISATA aims to transform passive risk situations (as perceived by an individual) into active risk situations, as people tend to underestimate the potential impact of passive risks. Our evaluation of the proposed framework demonstrates its ability to improve individuals’ ISA, as assessed by the sensors and in simulations of common attack vectors.
KW - Cybersecurity Training
KW - Gamification
KW - Human Factors
KW - Information Security Awareness
KW - Mobile Devices
KW - Social Engineering
UR - http://www.scopus.com/inward/record.url?scp=85184091066&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-51479-1_22
DO - 10.1007/978-3-031-51479-1_22
M3 - Conference contribution
AN - SCOPUS:85184091066
SN - 9783031514784
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 431
EP - 451
BT - Computer Security – ESORICS 2023 - 28th European Symposium on Research in Computer Security, 2023, Proceedings
A2 - Tsudik, Gene
A2 - Conti, Mauro
A2 - Liang, Kaitai
A2 - Smaragdakis, Georgios
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 25 September 2023 through 29 September 2023
ER -