• We are currently working on a Decepti-Box build
for a Windows client.
• We will be utilizing machine learning and artifi-
cial intelligence capabilities to enable decoys to
be more active and dynamic thus creating im-
proved realism.
• We continue to profile various equipment compo-
nents from multiple vendors in order to create a
more diverse set of decoys.
• We are actively studying ways to create more de-
coys while maintaining system fidelity.
• We are beginning to study game theoretic and log-
ical tools to more effectively camouflage Decepti-
SCADA honeypots among legitimate SCADA
network assets. This might be accomplished
through the implementation of deceptive network
scan results (Jajodia et al., 2017).
• We are conducting is an implementation of an at-
tacker engagement strategy (Bilinski et al., 2019)
in a SCADA network environment. The exper-
iment would have a real device and a decoy on
a SCADA network and test to see how a Rein-
forcement Learning (RL) agent would be perform
in determining which of the two devices are real.
Instead of using a simulated environment to give
signals to the RL agent, our experiment would use
real signals from the real machine and decoys.
This experiment will give us insight on how our
decoy system will influence an attacker given they
are aware of the techniques deployed by Decepti-
SCADA.
Beyond the areas described above, the Decepti-
SCADA Team continues to work on more refined test-
ing of the various components as well as develop a
case study which involves red team involvement in or-
der to determine the utility of deception for SCADA.
ACKNOWLEDGEMENTS
Roger A. Hallman is supported by the United States
Department of Defense SMART Scholarship for Ser-
vice Program funded by USD/R&E (The Under Sec-
retary of Defense-Research and Engineering), Na-
tional Defense Education Program (NDEP) / BA-1,
Basic Research.
REFERENCES
AlSabah, M. and Goldberg, I. (2016). Performance and se-
curity improvements for tor: A survey. ACM Comput-
ing Surveys (CSUR), 49(2):32.
Araujo, F., Hamlen, K. W., Biedermann, S., and Katzen-
beisser, S. (2014). From patches to honey-patches:
Lightweight attacker misdirection, deception, and
disinformation. In Proceedings of the 2014 ACM
SIGSAC conference on computer and communications
security, pages 942–953. ACM.
Arghira, N., Hossu, D., Fagarasan, I., Iliescu, S. S., and
Costianu, D. R. (2011). Modern scada philosophy
in power system operation-a survey. University” Po-
litehnica” of Bucharest Scientific Bulletin, Series C:
Electrical Engineering, 73(2):153–166.
Bilinski, M., Ferguson-Walter, K., Fugate, S., Gabrys, R.,
Mauger, J., and Souza, B. (2019). You only lie twice:
A multi-round cyber deception game of questionable
veracity. In International Conference on Decision and
Game Theory for Security, pages 65–84. Springer.
Buller, D. B. and Burgoon, J. K. (1996). Interpersonal de-
ception theory. Communication theory, 6(3):203–242.
Chakraborty, T., Jajodia, S., Katz, J., Picariello, A., Sperli,
G., and Subrahmanian, V. (2019). Forge: A fake on-
line repository generation engine for cyber deception.
IEEE Transactions on Dependable and Secure Com-
puting.
Denning, D. E. (2014). Framework and principles for active
cyber defense. Computers & Security, 40:108–113.
Denning, P. J. and Denning, D. E. (2016). Cybersecurity
is harder than building bridges. American Scientist,
104(3):155.
Dwork, C. (2011). Differential privacy. Encyclopedia of
Cryptography and Security, pages 338–340.
Fan, W., Du, Z., Fern
´
andez, D., and Villagr
´
a, V. A.
(2017). Enabling an anatomic view to investigate
honeypot systems: A survey. IEEE Systems Journal,
12(4):3906–3919.
Galloway, B. and Hancke, G. P. (2012). Introduction to
industrial control networks. IEEE Communications
surveys & tutorials, 15(2):860–880.
Gutzwiller, R., Ferguson-Walter, K., Fugate, S., and
Rogers, A. (2018). “oh, look, a butterfly!” a frame-
work for distracting attackers to improve cyber de-
fense. In Proceedings of the Human Factors and Er-
gonomics Society Annual Meeting, volume 62, pages
272–276. SAGE Publications Sage CA: Los Angeles,
CA.
Jajodia, S., Ghosh, A. K., Subrahmanian, V., Swarup, V.,
Wang, C., and Wang, X. S. (2012). Moving Target
Defense II: Application of Game Theory and Adver-
sarial Modeling, volume 100. Springer.
Jajodia, S., Park, N., Pierazzi, F., Pugliese, A., Serra, E.,
Simari, G. I., and Subrahmanian, V. (2017). A prob-
abilistic logic of cyber deception. IEEE Transactions
on Information Forensics and Security, 12(11):2532–
2544.
Latimer, J. (2003). Deception in War: Art Bluff Value De-
ceit Most Thrilling Episodes Cunning mil hist from
The Trojan. Abrams.
Merkel, D. (2014). Docker: lightweight linux containers for
consistent development and deployment. Linux jour-
nal, 2014(239):2.
IoTBDS 2020 - 5th International Conference on Internet of Things, Big Data and Security
76