Jasmin Schwab (German Aerospace Center (DLR)), Alexander Nussbaum (University of the Bundeswehr Munich), Anastasia Sergeeva (University of Luxembourg), Florian Alt (University of the Bundeswehr Munich and Ludwig Maximilian University of Munich), and Verena Distler (Aalto University)

Organizations depend on their employees’ long-term cooperation to help protect the organization from cybersecurity threats. Phishing attacks are the entry point for harmful followup attacks. The acceptance of training measures is thus crucial. Many organizations use simulated phishing campaigns to train employees to adopt secure behaviors. We conducted a preregistered vignette experiment (N=793), investigating the factors that make a simulated phishing campaign seem (un)acceptable, and their influence on employees’ intention to manipulate the campaign. In the experiment, we varied whether employees gave prior consent, whether the phishing email promised a financial incentive and the consequences for employees who clicked on the phishing link. We found that employees’ prior consent positively affected the acceptance of a simulated phishing campaign. The consequences of “employee interview” and “termination of the work contract” negatively affected acceptance. We found no statistically significant effects of consent, monetary incentive, and consequences on manipulation probability. Our results shed light on the factors influencing the acceptance of simulated phishing campaigns. Based on our findings, we recommend that organizations prioritize obtaining informed consent from employees before including them in simulated phishing campaigns and that they clearly describe their consequences. Organizations should carefully evaluate the acceptance of simulated phishing campaigns and consider alternative anti-phishing measures.

View More Papers

AegisSat: A Satellite Cybersecurity Testbed

Roee Idan, Roy Peled, Aviel Ben Siman Tov, Eli Markus, Boris Zadov, Ofir Chodeda, Yohai Fadida (Ben Gurion University of the Negev), Oliver Holschke, Jan Plachy (T-Labs (Research & Innovation)), Yuval Elovici, Asaf Shabtai (Ben Gurion University of the Negev)

Read More

SketchFeature: High-Quality Per-Flow Feature Extractor Towards Security-Aware Data Plane

Sian Kim (Ewha Womans University), Seyed Mohammad Mehdi Mirnajafizadeh (Wayne State University), Bara Kim (Korea University), Rhongho Jang (Wayne State University), DaeHun Nyang (Ewha Womans University)

Read More

Automatic Library Fuzzing through API Relation Evolvement

Jiayi Lin (The University of Hong Kong), Qingyu Zhang (The University of Hong Kong), Junzhe Li (The University of Hong Kong), Chenxin Sun (The University of Hong Kong), Hao Zhou (The Hong Kong Polytechnic University), Changhua Luo (The University of Hong Kong), Chenxiong Qian (The University of Hong Kong)

Read More