  How can we best address the dangerous impact that deep learning-generated
fake audios, photographs, and videos (a.k.a. deepfakes) may have in personal
and societal life? We foresee that the availability of cheap deepfake
technology will create a second wave of disinformation where people will
receive specific, personalized disinformation through different channels,
making the current approaches to fight disinformation obsolete. We argue that
fake media has to be seen as an upcoming cybersecurity problem, and we have to
shift from combating its spread to a prevention and cure framework where users
have available ways to verify, challenge, and argue against the veracity of
each piece of media they are exposed to. To create the technologies behind this
framework, we propose that a new Science of Disinformation is needed, one which
creates a theoretical framework both for the processes of communication and
consumption of false content. Key scientific and technological challenges
facing this research agenda are listed and discussed in the light of
state-of-art technologies for fake media generation and detection, argument
finding and construction, and how to effectively engage users in the prevention
and cure processes.
