Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Measuring robustness of complex networks is a fundamental task for analyzing the structure and function of complex networks. ,  study the network robustness under the maximal vertex coverage (MVC) attack, where the attacker aims to delete as many edges of the network as possible by attacking a small fraction of nodes. First,  present two robustness metrics of complex networks based on MVC attack.  then propose an efficient randomized greedy algorithm with near-optimal performance guarantee for computing the proposed metrics. Finally,  conduct extensive experiments on 20 real datasets. The results show that P2P and co-authorship networks are extremely robust under the MVC attack while both the online social networks and the Email communication networks exhibit vulnerability under the MVC attack. In addition, the results demonstrate the efficiency and effectiveness of our proposed algorithms for computing the corresponding robustness metrics.
['Rong-Hua Li', 'Jeffrey Xu Yu', 'Xin Huang', 'Hong Cheng', 'Zechao Shang']
I am writing a research paper on a idea Measuring robustness of complex networks under MVC attack
[{"from": "human", "value": "I am writing a research paper on a idea Measuring robustness of complex networks under MVC attack"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Measuring robustness of complex networks is a fundamental task for analyzing the structure and function of complex networks. ,  study the network robustness under the maximal vertex coverage (MVC) attack, where the attacker aims to delete as many edges of the network as possible by attacking a small fraction of nodes. First,  present two robustness metrics of complex networks based on MVC attack.  then propose an efficient randomized greedy algorithm with near-optimal performance guarantee for computing the proposed metrics. Finally,  conduct extensive experiments on 20 real datasets. The results show that P2P and co-authorship networks are extremely robust under the MVC attack while both the online social networks and the Email communication networks exhibit vulnerability under the MVC attack. In addition, the results demonstrate the efficiency and effectiveness of our proposed algorithms for computing the corresponding robustness metrics."}]