A Model for Evaluating and Comparing Moving Target Defense Techniques Based on Generalized Stochastic Petri Net

Cai, Guojun; Wang, Baosheng; Luo, Yao; Hu, Wei

doi:10.1007/978-981-10-2209-8_16

Cited by 13 publications

(7 citation statements)

References 17 publications

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“…1 Network address shuffling has been classified as two patterns: hopping and mutation. 19 In the hopping pattern, both clients and servers are aware of the network address changing. On the contrary, in the mutation pattern, only the server side is aware.…”

Section: Ip Shuffling As Mtdmentioning

confidence: 99%

Performance impact analysis of services under a time-based moving target defense mechanism

Mendonca

Cho

Moore

et al. 2021

Journal of Defense Modeling & Simulation

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Moving target defense (MTD) is a promising proactive defense technique to enhance system or network security. One caveat in developing a time-based MTD-enabled system is the potential performance degradation due to MTD operations being triggered periodically. In this work, we present our developed stochastic models based on deterministic stochastic Petri net (DSPN) formalism to assess the performance degradation introduced by periodic MTD operations. In addition, we demonstrate the effect of triggering a time-based MTD operation on performance degradation (e.g., jobs dropped or response time) and quality-of-service (QoS) of the system. We conducted comparative performance analysis with five DSPN models implemented in software packages such as TimeNet and Mercury under five different system configuration scenarios. Our key findings from this study include the following: (1) the deployment of MTD with the switchover strategy can improve the performance of services; (2) the switchover strategy showed the best cost-effectiveness among all strategies considered in this work; and (3) the interval of triggering MTD operations introduced a modest impact on job completion probability.

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Section: Ip Shuffling As Mtdmentioning

confidence: 99%

Performance impact analysis of services under a time-based moving target defense mechanism

Mendonca

Cho

Moore

et al. 2021

Journal of Defense Modeling & Simulation

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“…They analyzed the availability of MTD under different system parameters such as software age rate and different workloads. Cai et al [26] also used SRN models for evaluating the effectiveness of MTD. However, those works only focused on the effectiveness of MTD but ignored the job performance in the protected system.…”

Section: Related Workmentioning

confidence: 99%

Numerical Evaluation of Job Finish Time Under MTD Environment

et al. 2020

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Moving target defense (MTD) has recently emerged as a game-changer in the confrontation between cyberattack and defense. MTD mechanism constantly and randomly changes the system configurations to create uncertainty of the attack surface against cyber-adversaries. To date, researches on the evaluation of MTD techniques either focused on analyzing the effectiveness of MTD or studying the system performance loss due to the use of MTD. The impact on job/service running on the protected system is always ignored. In this paper, we propose an SRN (Stochastic reward net) based analytical modeling approach to investigate how MTD techniques influence the job running on protected system from the perspective of job finish time. The SRN model developed in this paper captures the behaviors of both the adversary and the job execution process. Furthermore, we carry out numerical analysis to study the impact of different system parameters on job finish time and other evaluation metrics. The results in this paper can help defenders choose a better MTD configuration to complete the job execution as soon as possible. INDEX TERMS Moving target defense, job migration, stochastic reward net, job finish time.

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“…Therefore, we choose GSPN as the modeling tool. The places correspond to the system state in the process of attack, defense and service, and the transitions correspond to the actions in the process of attack, defense and service [26] . 3.…”

Section: Description Of the Overall Architecture Of Mimic Dns Servicementioning

confidence: 99%

“…Guilin Cai, et al [25] develops a generalized abstract performance evaluation model for Moving target defense using Generalized stochastic petri net (GSPN). Thomas M. Chen, et al [26] propose a novel hierarchical method to construct large Petri nets from a number of smaller Petri nets that can be created separately by different domain experts, and it represents the actions of simultaneous attackers more flexible and expressive than traditional attack trees. However, the above models do not give the overall characteristics of attack disturbance, defense and service.…”

Section: Introductionmentioning

confidence: 99%

Performance Modeling Based on GSPN for Cyberspace Mimic DNS

Ren

2020

Chin. j. electron.

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A Model for Evaluating and Comparing Moving Target Defense Techniques Based on Generalized Stochastic Petri Net

Cited by 13 publications

References 17 publications

Performance impact analysis of services under a time-based moving target defense mechanism

Performance impact analysis of services under a time-based moving target defense mechanism

Numerical Evaluation of Job Finish Time Under MTD Environment

Performance Modeling Based on GSPN for Cyberspace Mimic DNS

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