Abstract Digital virtual assets are playing an increasingly important role and have become an indispensable part of people’s lives. However, due to the characteristics of network, virtuality, and openness, digital virtual assets are extremely vulnerable to attack. Meanwhile, it is difficult to guarantee the security of digital virtual assets based on advanced encryption technology and game theory-based asset security recognition and protection methods. Therefore, how to identify the possible attacks of digital virtual assets and timely accurate assessment the risks are the urgent problems to be solved. In this paper, we design an immune-based risk assessment method for digital virtual assets by simulating the mechanism of the human immune system ”synchronous dynamic evolution of antibody concentration with invasion virus”. First, we propose a negative selection algorithm based on the ”Designated + Random” mode by hierarchical division (HD-NSA), which can efficiently generate high-performance immune detectors to identify attack risks. Then a threat risk assessment model for digital virtual assets by simulating the concentration change of antibody in the immune system is established to assess the risk of attacks. Experiments on bitcoin dusting attack show that, the method proposed in this paper can detect attacks more quickly and accurately, and can also assess the risk of different users being attacked in real time.

中文翻译：

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一种基于免疫的数字虚拟资产风险评估方法

摘要 数字虚拟资产发挥着越来越重要的作用，已经成为人们生活中不可或缺的一部分。但是，由于网络性、虚拟性和开放性的特点，数字虚拟资产极易受到攻击。同时，基于先进的加密技术和基于博弈论的资产安全识别和保护方法，难以保证数字虚拟资产的安全。因此，如何识别数字虚拟资产可能遭受的攻击，及时准确评估风险是亟待解决的问题。在本文中，我们通过模拟人体免疫系统“抗体浓度与入侵病毒同步动态进化”的机制，设计了一种基于免疫的数字虚拟资产风险评估方法。第一的，我们提出了一种基于分层划分的“指定+随机”模式（HD-NSA）的否定选择算法，可以有效地生成高性能的免疫检测器来识别攻击风险。然后通过模拟免疫系统中抗体浓度的变化建立数字虚拟资产威胁风险评估模型来评估攻击风险。对比特币除尘攻击的实验表明，本文提出的方法可以更快、更准确地检测攻击，还可以实时评估不同用户受到攻击的风险。然后通过模拟免疫系统中抗体浓度的变化建立数字虚拟资产威胁风险评估模型来评估攻击风险。对比特币除尘攻击的实验表明，本文提出的方法可以更快、更准确地检测攻击，还可以实时评估不同用户受到攻击的风险。然后通过模拟免疫系统中抗体浓度的变化建立数字虚拟资产威胁风险评估模型来评估攻击风险。对比特币除尘攻击的实验表明，本文提出的方法可以更快、更准确地检测攻击，还可以实时评估不同用户受到攻击的风险。