Gokul CJ (TCS Research, Tata Consultancy Services Ltd., Pune), Vijayanand Banahatti (TCS Research, Tata Consultancy Services Ltd., Pune), Sachin Lodha (TCS Research, Tata Consultancy Services Ltd., Pune)

Phishing threats are on the rise, especially through Business Email Compromise (BEC). Despite having several tools for phishing email detection, the attacks are becoming smarter and personal, targeting individuals to gain access to personal and organizational information. Game-based cybersecurity training methods are found to have positive results in educating users. Along this line, we introduce PickMail, an anti-phishing awareness game that simulates typical real-life email scenarios to train an organization’s employees. In PickMail, we train participants to judge the legitimacy of an email by inspecting its various parts, such as the sender’s email domain, hyperlinks, attachments, and forms. The game also records participants’ decision-making steps that lead to their final judgment. Our study with 478 participants shows how the serious game-based training helped the participants make better judgments on emails, with the correctness in identifying email legitimacy reaching 92.62%. The study also provided us with insights that could help develop better training methods and user interfaces.

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P4DDPI: Securing P4-Programmable Data Plane Networks via DNS Deep...

Ali AlSabeh (University of South Carolina), Elie Kfoury (University of South Carolina), Jorge Crichigno (University of South Carolina) and Elias Bou-Harb (University of Texas at San Antonio)

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PoF: Proof-of-Following for Vehicle Platoons

Ziqi Xu (University of Arizona), Jingcheng Li (University of Arizona), Yanjun Pan (University of Arizona), Loukas Lazos (University of Arizona, Tucson), Ming Li (University of Arizona, Tucson), Nirnimesh Ghose (University of Nebraska–Lincoln)

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RVPLAYER: Robotic Vehicle Forensics by Replay with What-if Reasoning

Hongjun Choi (Purdue University), Zhiyuan Cheng (Purdue University), Xiangyu Zhang (Purdue University)

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DrawnApart: A Deep-Learning Enhanced GPU Fingerprinting Technique

Naif Mehanna (University of Lille, CNRS, Inria), Tomer Laor (Ben-Gurion University of the Negev)

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