Node injection attack on Graph Neural Networks (GNNs) is an emerging and practical attack scenario that the attacker injects malicious nodes rather than modifying original nodes or edges to affect the performance of GNNs. However, existing node injection attacks ignore extremely limited scenarios, namely the injected nodes might be excessive such that they may be perceptible to the target GNN. In this paper, we focus on an extremely limited scenario of single node injection evasion attack, i.e., the attacker is only allowed to inject one single node during the test phase to hurt GNN's performance. The discreteness of network structure and the coupling effect between network structure and node features bring great challenges to this extremely limited scenario. We first propose an optimization-based method to explore the performance upper bound of single node injection evasion attack. Experimental results show that 100%, 98.60%, and 94.98% nodes on three public datasets are successfully attacked even when only injecting one node with one edge, confirming the feasibility of single node injection evasion attack. However, such an optimization-based method needs to be re-optimized for each attack, which is computationally unbearable. To solve the dilemma, we further propose a Generalizable Node Injection Attack model, namely G-NIA, to improve the attack efficiency while ensuring the attack performance. Experiments are conducted across three well-known GNNs. Our proposed G-NIA significantly outperforms state-of-the-art baselines and is 500 times faster than the optimization-based method when inferring. CCS CONCEPTS• Information systems → Data mining.
In "Distributed quantum sensing with mode-entangled spin-squeezed atomic states" Nature (2022) [1], Malia et. al. claim to improve the precision of a network of clocks by using entanglement. In particular, by entangling a clock network with up to four nodes, a precision 11.6 dB better than the quantum projection noise limit (i.e. precision without any entanglement) is reported. These claims are incorrect, Malia et. al. do not achieve an improved precision with entanglement. Here we show their demonstration is more than two orders of magnitude worse than the quantum projection noise limit.The central message in "Distributed quantum sensing with mode-entangled spin-squeezed atomic states" Nature (2022) [1] is that by entangling atoms in an atomic clock network, a precision is demonstrated that is impossible to attain using the same number of atoms and time without entanglement. Should we accept this message? Putting aside the impressive technical achievements in the paper, we can objectively assess whether the experimental data are in agreement with the claim.The final two figures of the paper present the supporting data. In Fig. 3, ∆( θ) is plotted as a function of the number of clocks M, each with N = 45, 000 atoms, where the black line (1/ √ MN ) is supposed to denote a limit that cannot be surpassed without entanglementthe quantum projection noise limit (QPN). One point should be made clear, ∆( θ) > 1/ √ MN is very definitively not the limit without entanglement. To see this requires an explanation of what ∆( θ) is. Despite the authors calling ∆( θ) the 'measured sensitivity', it is not a sensitivity at all. θ is simply the difference in values between two measurements (for M = 1).
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