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Aspirations for a boundless communication paradigm for future generation networks have changed the conventional way of looking at network security. With such a vision, security techniques should not only be securing local end-users but also be protecting entire networks from malicious adversaries. Unfortunately, providing security protection for such gigantic networks is a very challenging task. Based on the analogous relationships of various cell interactions in a metabolic network and a complex heterogeneous network, we explore the possibilities of human immune system (HIS) inspired anomaly detection for protecting interworked heterogeneous networks. In light of this, the applicability of two key schools of thought on how the HIS detects anomalies; namely, the Negative Selection (NS) and the Danger Theory (DT) are discussed in this article. While the NS theory is the traditional understanding of anomaly detection in the HIS, the DT is a radical new concept that challenges the main fundamentals of the NS theory, which is currently being hotly debated among immunologists. Based on this, the article highlights the applicability and the limitations of these two theories in detecting malicious anomalies in heterogeneous networks. From our analysis, we establish a doctrine that the DT outperforms its counterpart (the NS theory) in detecting anomalies in a complex heterogeneous network. Our analysis also indicates that the DT inspired anomaly detection is efficient in detecting malicious network adversaries and updating network segments that are under attack, thereby increasing the survivability of heterogeneous networks.