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Community detection plays an important role in social networks, since it can help to naturally divide the network into smaller parts so as to simplify network analysis. However, on the other hand, it arises the concern that individual information may be over-mined, and the concept community deception has been proposed to protect individual privacy on social networks. Here, we introduce and formalize the problem of community detection attack and develop efficient strategies to attack community detection algorithms by rewiring a small number of connections, leading to privacy protection. In particular, we first give two heuristic attack strategies, i.e., Community Detection Attack (CDA) and Degree Based Attack (DBA), as baselines, utilizing the information of detected community structure and node degree, respectively. And then we propose an attack strategy called "Genetic Algorithm (GA) based Q-Attack", where the modularity Q is used to design the fitness function. We launch community detection attack based on the above three strategies against six community detection algorithms on several social networks. By comparison, our Q-Attack method achieves much better attack effects than CDA and DBA, in terms of the larger reduction of both modularity Q and Normalized Mutual Information (NMI). Besides, we further take transferability tests and find that adversarial networks obtained by Q-Attack on a specific community detection algorithm also show considerable attack effects while generalized to other algorithms.

We investigated how the stability of aqueous argon surface nanobubbles on hydrophobic surfaces depends on gas adsorption, solid−gas interaction energy, and the bulk gas concentration using molecular dynamics simulation with the SPC/E water solvent. We observed stable surface nanobubbles without surface pinning sites for longer than 160 ns, contrary to previous findings using monoatomic Lennard-Jones solvent. In addition, the hydrophobicity of a substrate has an effect to reduce the requirement degree of oversaturation on water bulk. We found that the gas enrichment layer, gas adsorption monolayer on the hydrophobic substrate, and water hydrogen bonding near the interface are likely necessary conditions for nanobubble stability. We concluded that gas nanobubble stability does not necessarily require three-phase pinning sites.