An artificial sequential immune responses model for anomaly detection

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Abstract

Self-non-self discrimination and danger theory have long been the fundamental model of modern theoretical immunology. Based on these principles, some effective and efficient artificial immune algorithms have been proposed and applied to a wide range of engineering applications. Over the past years, a new idea called sequential immune responses (SIR) has been developed to challenge the classical negative selection model and danger theory. In this conceptual paper, we look at SIR from the perspective of artificial immune system (AIS) practitioners. An overview of the SIR is presented with particular emphasis on analogies in the AIS world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for AIS.

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Zhou, W., & Liang, Y. (2020). An artificial sequential immune responses model for anomaly detection. In GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 95–96). Association for Computing Machinery, Inc. https://doi.org/10.1145/3377929.3389995

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