Abstract
Heterogeneous networks are powerful tools for describing different types of entities and relationships and are more relevant models of complex networks. The study of heterogeneous network defense is of great practical significance for protecting useful networks such as military combat networks and critical infrastructure networks. However, a large amount of current research on complex network defense focuses on homogeneous networks under complete information conditions, which often ignore the real conditions such as incomplete information and heterogeneous networks. In this paper, we propose firstly a new adversarial hiding deception strategy for heterogeneous network defense under incomplete information conditions. Secondly, we propose an adversarial hiding deception network optimization method based on a genetic algorithm and design node importance index and a fitness function, which take into account the graph structure information and information about the type of nodes. Finally, we conduct comparison experiments for different defense strategies, and the results show that the proposed strategy and network optimization method are effective at hiding the critical nodes and inducing the attacker to attack the non-important nodes. The generated adversarial hiding deception network has a similar graph structure to the real network.
Highlights
The defense effect of the adversarial hiding deception network and the defense effect of the random disguise defense network are basically the same as the real network at the beginning of the disintegration phase, and the analysis is because we limit the number of hidden edges and deceptive edges set in the process of generating the adversarial hiding deception network
We first proposed a heterogeneous network defense strategy based on hiding and deception under incomplete information, that is, an adversarial hiding deception strategy
We build an adversarial hiding deception network to hide the critical nodes in the network and induce the attacker to attack the non-important nodes, which breaks the limitation of the traditional passive defense strategy and realizes the active defense of the network; This paper proposed the adversarial hidden spoofing strategy
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Complex networks are a research paradigm that represents complex systems as network structures. Complex networks have been studied mainly as homogeneous networks. In the real world, heterogeneous networks consisting of different types of entities and relationships are prevalent. In the real world, citation networks [1], social networks [2], recommender systems [3], cybersecurity [4] and military combat networks are composed of networks of different types of entities and relationships. Heterogeneous networks can more accurately describe the different types of entities and relationships in these networks
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