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Differential Security Game in Heterogeneous Device-to-Device Offloading Network under Epidemic Risks
IEEE Transactions on Network Science and Engineering ( IF 6.7 ) Pub Date : 2020-07-01 , DOI: 10.1109/tnse.2019.2955036
Letian Zhang , Jie Xu

Cooperative computation among peer mobile devices via device-to-device (D2D) links, a.k.a. D2D offloading, is a promising technology to enhance mobile computing performance and reduce core wireless network traffic. However, D2D offloading also creates new security risks as malware can relatively easily compromise mobile devices participating in D2D offloading and propagate across the entire network. In this article, we build an epidemic model to understand the malware propagation process in the D2D offloading-enabled mobile network where devices have heterogeneous computation demand and new devices can enter the system over time. This model also allows mobile devices to intentionally enter a “non-cooperative” state as a preventive defense strategy to thwart malware propagation. We prove a thresholding result of the malware propagation similar to that in classic epidemic models under given static defender (i.e. the network operator) and attacker strategies. We further model the strategic interaction between the defender and the attacker as a zero-sum differential game. The existence of a saddle-point equilibrium is proved, and the optimal dynamic defense and attack strategies are derived based on the Pontryagin's maximum principle, which are proven to be a bang-bang control strategy. Simulation results validate the proposed model and show that the dynamic optimal strategies significantly improve the system utility compared with baseline strategies.

中文翻译:

流行风险下异构设备到设备卸载网络中的差异化安全博弈

通过设备到设备 (D2D) 链路在对等移动设备之间进行协作计算,又名 D2D 卸载,是一种很有前途的技术,可增强移动计算性能并减少核心无线网络流量。然而,D2D 卸载也会带来新的安全风险,因为恶意软件可以相对容易地危害参与 D2D 卸载的移动设备并在整个网络中传播。在本文中,我们构建了一个流行模型来了解支持 D2D 卸载的移动网络中的恶意软件传播过程,其中设备具有异构计算需求,并且随着时间的推移新设备可以进入系统。该模型还允许移动设备有意进入“非合作”状态,作为阻止恶意软件传播的预防性防御策略。我们证明了在给定静态防御者(即网络运营商)和攻击者策略下,恶意软件传播的阈值结果类似于经典流行病模型中的阈值结果。我们进一步将防御者和攻击者之间的战略互动建模为零和微分博弈。证明了鞍点平衡的存在性,并基于庞特里亚金极大值原理推导出最优动态防御和攻击策略,证明是一种bang-bang控制策略。仿真结果验证了所提出的模型,并表明与基线策略相比,动态优化策略显着提高了系统效用。我们进一步将防御者和攻击者之间的战略互动建模为零和微分博弈。证明了鞍点平衡的存在性,并基于庞特里亚金极大值原理推导出最优动态防御和攻击策略,证明是一种bang-bang控制策略。仿真结果验证了所提出的模型,并表明动态优化策略与基线策略相比显着提高了系统效用。我们进一步将防御者和攻击者之间的战略互动建模为零和微分博弈。证明了鞍点平衡的存在性,并基于庞特里亚金极大值原理推导出最优动态防御和攻击策略,证明是一种bang-bang控制策略。仿真结果验证了所提出的模型,并表明动态优化策略与基线策略相比显着提高了系统效用。
更新日期:2020-07-01
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