  Deceptive patterns are design practices embedded in digital platforms to
manipulate users, representing a widespread and long-standing issue in the web
and mobile software development industry. Legislative actions highlight the
urgency of globally regulating deceptive patterns. However, despite
advancements in detection tools, a significant gap exists in assessing
deceptive pattern risks. In this study, we introduce a comprehensive approach
involving the interactions between the Adversary, Watchdog (e.g., detection
tools), and Challengers (e.g., users) to formalize and decode deceptive pattern
threats. Based on this, we propose a quantitative risk assessment system.
Representative cases are analyzed to showcase the practicability of the
proposed risk scoring system, emphasizing the importance of involving human
factors in deceptive pattern risk assessment.
