Abstract
With a rapid accumulation of cyberspace digital virtual assets (CDVA), the serious security risks of CDVA appear since the lack of security protection methods for CDVA application systems. The present CDVA security systems mainly adopt the general network threat detection methods, do not deal with the specifics of CDVA, thus, they are not suitable for CDVA security threat detection. This paper presents an immune-based security threat detection system (IBSTDS) for CDVA. The system collects the data flow of fundamental infrastructure from Internet, extracts and formalizes the features to form antigens. The antigens are sequentially sent to the memory detectors and mature detectors for known and unknown threat detection. The immune detectors are optimized by detector dynamic evolution and immune feedback mechanism. The experiment proves that the system has the ability of threat-recognition and self-learning. Compared with the current CDVA security systems, IBSTDS supports adaptability, self-organization, robustness and self-learning, and provides a good solution to detect the security threat to digital virtual assets.
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Acknowledgment
This work is supported by National Key Research and Development Program of China (Grant No. 2016YFB0800604 and No. 2016YFB0800605), Natural Science Foundation of China (Grant No. U1736212 and No. 61572334), and Sichuan Province Key Research and Development Project of China (Grant No. 2018GZ0183).
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Lin, P., Li, T., Liu, X., Zhao, H., Yang, J., Zhu, F. (2018). An Immunity-Based Security Threat Detection System for Cyberspace Digital Virtual Assets. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11064. Springer, Cham. https://doi.org/10.1007/978-3-030-00009-7_54
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DOI: https://doi.org/10.1007/978-3-030-00009-7_54
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