Confidence Skewing Problem and Its Correction Method in Mimic Arbitration Mechanism

GUO Wei; ZHANG Fan; WU Zhaoqi; WEI Jin; WU Jiangxing; ZHOU Wenle

doi:10.1049/cje.2020.03.010

Volume 29 Issue 3

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Article Navigation > Chinese Journal of Electronics > 2020 > 29(3): 547-553

GUO Wei, ZHANG Fan, WU Zhaoqi, et al. “Confidence Skewing Problem and Its Correction Method in Mimic Arbitration Mechanism”. Chinese Journal of Electronics, vol. 29 no. 3. doi: 10.1049/cje.2020.03.010

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GUO Wei, ZHANG Fan, WU Zhaoqi, et al. “Confidence Skewing Problem and Its Correction Method in Mimic Arbitration Mechanism”. Chinese Journal of Electronics, vol. 29 no. 3. doi: 10.1049/cje.2020.03.010

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Confidence Skewing Problem and Its Correction Method in Mimic Arbitration Mechanism

doi: 10.1049/cje.2020.03.010

1.
PLA Strategic Support Force Information Engineering University, Zhengzhou 450002, China;
2.
School of Computer Science, Fudan University, Shanghai 200433, China;
3.
The Institute of North Electronic Equipment, Beijing 100083, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61572520), the National Natural Science Foundation of China for Innovative Research Groups (No.61521003), and the Special Fund for Informatization Projects of Shanghai (No.201701046).

More Information

Corresponding author: ZHANG Fan (corresponding author) was born in 1981. He received the Ph.D. degrees in information and communication engineering in 2013 from Information Engineering University. He is currently an associate researcher. His research interests include proactive defense, high-performance computing, and big data processing. (Email:17034203@qq.com)
Received Date: 2019-10-07
Rev Recd Date: 2019-12-30
Publish Date: 2020-05-10

Abstract

Abstract

Arbitration mechanism is the core element of Cyberspace mimic defense (CMD) scheme, providing the security effect of exception perception and exception shielding for the protected system. The existing arbitration methods confront the problem of confidence skewing caused by attack changes when calculating confidence. This paper proposes a correction method for confidence calculation based on Logistic function (Lcorrection). The method makes a grading on influence for different historical periods and filters the noise of “overheating” exception outputs so that the confidence calculation process can adapt to the attack changes in real applications. The evaluations show that the L-correction can adequately handle the confidence skewing and skewingbased confidence cheating, improving the security of mimic arbitration mechanism.
- Cyberspace mimic defense,
- Arbitration mechanism,
- Confidence skewing,
- Logistic function,
- Influence grading,
- Noise filtering

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References(23)

References

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