Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense

George Kesidis; Takis Konstantopoulos; Michael Zazanis

doi:10.1007/978-3-032-09315-8_1

Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense

George Kesidis
, Takis Konstantopoulos
, Michael Zazanis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In cybersecurity, moving-target defense (MTD) mitigates reconnaissance attacks from botnets by periodically resetting server identities, disrupting adversarial intelligence gathering. We model this defense mechanism as a dynamic coupon collection process, where servers correspond to coupon types and botnet attacks to coupon acquisitions. The defender’s intervention (removing collected coupons) represents server resets, restoring their uncompromised state. In this paper, we derive various results regarding the number of compromised servers under various stochastic attack-defense dynamics.

Original language	English (US)
Title of host publication	Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings
Editors	Josu Doncel, Nicolas Gast, Yezekael Hayel, Vincenzo Mancuso, Vincenzo Mancuso
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1-12
Number of pages	12
ISBN (Print)	9783032093141
DOIs	https://doi.org/10.1007/978-3-032-09315-8_1
State	Published - 2026
Event	12th International Conference on Network Games, Artificial Intelligence, Control and Optimization, NETGCOOP 2025 - Bilbao, Spain Duration: Oct 8 2025 → Oct 10 2025

Publication series

Name	Lecture Notes in Computer Science
Volume	16173 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Network Games, Artificial Intelligence, Control and Optimization, NETGCOOP 2025
Country/Territory	Spain
City	Bilbao
Period	10/8/25 → 10/10/25

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-032-09315-8_1

Cite this

Kesidis, G., Konstantopoulos, T., & Zazanis, M. (2026). Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense. In J. Doncel, N. Gast, Y. Hayel, V. Mancuso, & V. Mancuso (Eds.), Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings (pp. 1-12). (Lecture Notes in Computer Science; Vol. 16173 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-032-09315-8_1

Kesidis, George ; Konstantopoulos, Takis ; Zazanis, Michael. / Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense. Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings. editor / Josu Doncel ; Nicolas Gast ; Yezekael Hayel ; Vincenzo Mancuso ; Vincenzo Mancuso. Springer Science and Business Media Deutschland GmbH, 2026. pp. 1-12 (Lecture Notes in Computer Science).

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abstract = "In cybersecurity, moving-target defense (MTD) mitigates reconnaissance attacks from botnets by periodically resetting server identities, disrupting adversarial intelligence gathering. We model this defense mechanism as a dynamic coupon collection process, where servers correspond to coupon types and botnet attacks to coupon acquisitions. The defender{\textquoteright}s intervention (removing collected coupons) represents server resets, restoring their uncompromised state. In this paper, we derive various results regarding the number of compromised servers under various stochastic attack-defense dynamics.",

author = "George Kesidis and Takis Konstantopoulos and Michael Zazanis",

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Kesidis, G, Konstantopoulos, T & Zazanis, M 2026, Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense. in J Doncel, N Gast, Y Hayel, V Mancuso & V Mancuso (eds), Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings. Lecture Notes in Computer Science, vol. 16173 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 1-12, 12th International Conference on Network Games, Artificial Intelligence, Control and Optimization, NETGCOOP 2025, Bilbao, Spain, 10/8/25. https://doi.org/10.1007/978-3-032-09315-8_1

Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense. / Kesidis, George; Konstantopoulos, Takis; Zazanis, Michael.
Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings. ed. / Josu Doncel; Nicolas Gast; Yezekael Hayel; Vincenzo Mancuso; Vincenzo Mancuso. Springer Science and Business Media Deutschland GmbH, 2026. p. 1-12 (Lecture Notes in Computer Science; Vol. 16173 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - In cybersecurity, moving-target defense (MTD) mitigates reconnaissance attacks from botnets by periodically resetting server identities, disrupting adversarial intelligence gathering. We model this defense mechanism as a dynamic coupon collection process, where servers correspond to coupon types and botnet attacks to coupon acquisitions. The defender’s intervention (removing collected coupons) represents server resets, restoring their uncompromised state. In this paper, we derive various results regarding the number of compromised servers under various stochastic attack-defense dynamics.

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Kesidis G, Konstantopoulos T, Zazanis M. Stationary Models of Adversarial Coupon Collection with an Application to Moving-Target Defense. In Doncel J, Gast N, Hayel Y, Mancuso V, Mancuso V, editors, Network Games, Artificial Intelligence, Control and Optimization - 12th International Conference, NETGCOOP 2025, Proceedings. Springer Science and Business Media Deutschland GmbH. 2026. p. 1-12. (Lecture Notes in Computer Science). doi: 10.1007/978-3-032-09315-8_1