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Biologically inspired model for computer virus detection

机译:受生物启发的计算机病毒检测模型

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摘要

Internet provides a fertile medium for new breeds of computer viruses. Many people who have access to a wealth of information via Internet are attacked by more computer viruses than they can effectively process. We present a dynamic computer virus detection model that can detect known viruses and previously unknown viruses to prevent information systems from damage. This model is inspired by biological immune systems that protect the body against damage from pathogens. The architecture of this model, the formal definitions of self, nonself, antigen, antibody, and vaccine gene library are introduced. Furthermore, the evolution of self and nonself, the generation of the antibody, the evolution of the virus vaccine gene, and the detection of the antigen are depicted. Experiment results show that this model has better capacity of self-adaptability and self-learning in detecting unknown viruses than traditional models..
机译:互联网为新型计算机病毒提供了肥沃的媒体。许多通过Internet访问大量信息的人受到的计算机病毒攻击数量超出其有效处理范围。我们提供了一种动态计算机病毒检测模型,该模型可以检测已知病毒和以前未知的病毒,以防止信息系统受到破坏。该模型的灵感来自保护人体免受病原体损害的生物免疫系统。介绍了该模型的体系结构,自身,非自身,抗原,抗体和疫苗基因文库的正式定义。此外,还描述了自身和非自身的进化,抗体的生成,病毒疫苗基因的进化以及抗原的检测。实验结果表明,该模型在检测未知病毒方面具有比传统模型更好的自适应性和自学习能力。

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