ing and costly signaling. Our computational simulations uncovered several
interesting information flow properties
that may be leveraged to deter deception, specifically by enhancing the flow
of information regarding cooperative
strategies while reinforcing the cooperative group’s identity. Interestingly,
this result indicates an identity management system, typically thought to hinge
on the precision of true positives and
astronomical unlikeliness of false-pos-itive recognition, may rather critically
depend on how learned behavior and
strategic information can be shared.
Our computational experiment offers new insights for achieving strong
deterrence of identity deception within ad hoc networks such as WANETs,
however much is left as future work.
Our larger practical goal is M-coin, a
design strategy and system for cooperation enhancing technologies. M-coin
may be thought of as an abstract currency guiding an open recommender-verification system that incorporates
new agent types (to verify identities,
behavior histories, and cooperative
strategies as well as the consistency
of distrusted information); the new
types promote efficiencies supporting cooperative coalitions. The main
step forward, as demonstrated here, is
recognizing the effects of pooled and
verified strategic information, and its
flow constraints (as well as its capabilities to operate in the open). Vetted
strategic information assists cooperators to rapidly adapt to and out-com-pete deceptive strategies.
Still, many challenges remain outstanding. The possibility of an agent
not compelled by utility presents a
problem, as that agent may persist
within the network indefinitely to
form effective attacks. Future work
may focus on how the expression of
rationality could be fortified for iden-tities/nodes. Critically, deceptively
minded actors will need to prefer a
base level of utility, and this remains
an open challenge (although the solution could lie in the many possibilities suggested by biological systems).
Additionally, technologies supporting the tedious aspects of information gathering and validation must be
aligned to user incentives.
Properly constructed recommender-
verifier architectures could be used in
WANETS, HFNs, and other fluid-iden-
tity cyber-social and cyber-physical
systems to reliably verify private but
trustworthy identities and limit the
damage of deceptive attack strategies.
Starting with WANETs, we motivate
an elegant solution using formalisms
we originally developed for signaling
games. Nonetheless, we are encour-
aged by analogous biological solu-
tions derived naturally under Darwin-
Acknowledgments. We thank the
anonymous reviewers for their insightful comments. This material is
based upon work funded and supported by U.S. Department of Defense
Contract No. FA8702-15-D-0002 with
Carnegie Mellon University Software
Engineering Institute and New York
University and ARO grant A18-0613-
00 (B.M.). This material has been approved for public release and unlimited distribution, ref DM17-0409.
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William Casey ( firstname.lastname@example.org) is a senior member
of Carnegie Mellon University, Software Engineering
Institute, Pittsburgh, PA, USA.
Ansgar Kellner is a research fellow at the Institute of
System Security at Technische Universität Braunschweig,
Parisa Memarmoshrefi is a research staff member at
University of Göttingen, Germany.
Jose Andre Morales is a researcher at the Software
Engineering Insitute, Carnegie Mellon University,
Pittsburgh, PA, USA.
Bud Mishra ( email@example.com) is a professor at New
York University Courant Institute, Tandon School of
Engineering and School of Medicine, New York, NY, USA.
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