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Network Strengthening Against Malicious Attacks

机译:网络加强恶意攻击

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摘要

Robustness measures the toleration of complex networks against random failures and malicious attacks. A malicious attack removes the most important node iteratively and destroys the network quickly. It is crucial to strengthen the network robustness against malicious attacks. In this paper, we propose an algorithm to strengthen the robustness with reduced change of network structure compared to state-of-the-art algorithms. The algorithm is called targeted variable neighborhood search (TVNS) algorithm. Experiments on real-world and random networks show that TVNS is efficient on strengthening the robustness against malicious attacks. The strengthened network against high degree adaptive attack shows an onion-like structure where nodes prefeito connect with similar degree nodes; while for the strengthened network against high betweenness adaptive attack, nodes prefer to connect with similar betweenness nodes.
机译:稳健性测量复杂网络免受随机失败和恶意攻击的容击。恶意攻击迭代地删除最重要的节点并快速销毁网络。强化对恶意攻击的网络稳健性至关重要。在本文中,我们提出了一种算法,以加强与最先进的算法相比降低网络结构变化的鲁棒性。该算法称为目标变量邻域搜索(TVNS)算法。现实世界和随机网络的实验表明,TVNS是有效地加强对恶意攻击的鲁棒性。强化网络对抗高度自适应攻击,显示了一种类似洋葱结构,其中节点PrefeITO与类似程度节点连接;虽然对于强化网络在高度之间的自适应攻击中,节点更喜欢与相似的之间的节点连接。

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