A Decentralized Multi-ruling Arbiter for Cyberspace Mimicry Defense

Shen, Congqi; Chen, Shuang-Xi; Wu, Chunming

doi:10.1109/isncc.2019.8909197

Cited by 5 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fei Yu et al conducted a series of experiments on basic, common-mode, and differential-mode attacks to obtain the defense success rate and analyzed the delay and throughput to reflect their performance loss [28]. Congqi Shen et al proposed a decentralized multi-adjudicator arbiter approach to determine the defense effectiveness using the consistent convergence of subarbiters after data injection attacks [29]. Quan Ren et al analyzed the applicability of cyber mimic defense in a software-defined network from the aspects of availability, response time, compromise tolerance, and performance [30].…”

Section: Simulationmentioning

confidence: 99%

Location-Aware Measurement for Cyber Mimic Defense: You Cannot Improve What You Cannot Measure

Huang,

Yuan,

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Cyber mimic defense is designed to ensure endogenous security, effectively countering unknown vulnerabilities and backdoors, thereby addressing a significant challenge in cyberspace. However, the immense scale of real-world networks and their intricate topology pose challenges for measuring the efficacy of cyber mimic defense. To capture and quantify defense performance within specific segments of these expansive networks, we embrace a partitioning approach that subdivides large networks into smaller regions. Metrics are then established within an objective space constructed on these smaller regions. This approach enables the establishment of several fine-grained metrics that offer a more nuanced measurement of cyber mimic defense deployed in complex networks. For example, the common-mode index is introduced to highlight shared vulnerabilities among diverse nodes, the transfer probability computes the likelihood of risk propagation among nodes, and the failure risk assesses the likelihood of cyber mimic defense technology failure within individual nodes or entire communities. Furthermore, we provide proof of the convergence of the transfer probability. A multitude of simulations are conducted to validate the reliability and applicability of the proposed metrics.

show abstract

Section: Simulationmentioning

confidence: 99%