  With the rapid diffusion of social networks in combination with mobile
phones, a new social threat of sextortion has emerged, in which vulnerable
young women are essentially blackmailed with their explicit shared multimedia
content. The phenomenon of sextortion is now widely studied by psychologists,
sociologists, criminologists, etc. The findings have been translated into
scattered help from NGOs, specialized law enforcement units, and therapists,
who usually do not coordinate their efforts among each other. This paper
addresses the gap of lacking coordination systems to effectively and
efficiently use modern information technologies that align the efforts of
scattered and non-aligned sextortion help organizations. Consequently, this
paper not only investigates the goals, incentives, and disincentives for a
system design and development that not only governs effectively and efficiently
diverse cases of sextortion victims, but also leverages artificial intelligence
in a targeted manner. It explores how AI and, in particular, autonomous
cognitive entities can improve victim profiles analysis, streamline support
mechanisms, and provide intelligent insight into sextortion cases. Furthermore,
the paper conceptually studies the extent to which such efforts can be
monetized in a sustainable way. Following a novel design methodology for the
design of trusted blockchain decentralized applications, the paper presents a
set of conceptual requirements and system models based on which it is possible
to deduce a best-practice technology stack for rapid implementation deployment.
