IEEE Circuits and Systems Magazine - Q1 2023 - 34

[83] S.-M. Chen, Y.-F. Xu, and S. Nie, " Robustness of network controllability
in cascading failure,'' Phys. A, Stat. Mech. Appl., vol. 471,
pp. 536-539, Apr. 2017.
[84] L.-L. Hou, Y.-D. Xiao, and L. Lu, " Robustness of network controllability
against cascading failure,'' in Proc. Int. Conf. Intell. Sci. Big Data
Eng. Springer, 2019, pp. 347-355.
[85] L. Ma et al., " Enhancing community integrity of networks against
multilevel targeted attacks,'' Phys. Rev. E, Stat. Phys. Plasmas Fluids
Relat. Interdiscip. Top., vol. 88, no. 2, Aug. 2013, Art. no. 022810.
[86] S. Wang, J. Liu, and X. Wang, " Mitigation of attacks and errors on
community structure in complex networks,'' J. Stat. Mech., Theory Exp.,
vol. 2017, no. 4, 2017, Art. no. 043405.
[87] S. Scellato et al., " Evaluating temporal robustness of mobile networks,''
IEEE Trans. Mobile Comput., vol. 12, no. 1, pp. 105-117, Jan. 2013.
[88] T. Nie et al., " New attack strategies for complex networks,'' Phys. A,
Stat. Mech. Appl., vol. 424, pp. 248-253, Apr. 2015.
[89] Y.-L. Gao et al., " Robustness analysis of interdependent networks
under multiple-attacking strategies,'' Phys. A, Stat. Mech. Appl., vol. 496,
pp. 495-504, Apr. 2018.
[90] Y. Hao, L. Jia, and Y. Wang, " Edge attack strategies in interdependent
scale-free networks,'' Phys. A, Stat. Mech. Appl., vol. 540, Feb. 2020,
Art. no. 122759.
[91] Q. Nguyen et al., " Conditional attack strategy for real-world complex
networks,'' Phys. A, Stat. Mech. Appl., vol. 530, Sep. 2019, Art. no. 121561.
[92] X. Huang et al., " Robustness of interdependent networks under targeted
attack,'' Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip.
Top., vol. 83, no. 6, 2011, Art. no. 065101.
[93] G. Dong et al., " Percolation of partially interdependent networks
under targeted attack,'' Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat.
Interdiscip. Top., vol. 85, no. 1, Jan. 2012, Art. no. 016112.
[94] P. Cui et al., " Enhancing robustness of interdependent network by
adding connectivity and dependence links,'' Phys. A, Stat. Mech. Appl.,
vol. 497, pp. 185-197, May 2018.
[95] G. Dong et al., " Robustness of network of networks under targeted
attack,'' Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top.,
vol. 87, no. 5, 2013, Art. no. 052804.
[96] X. Liu, H. Peng, and J. Gao, " Vulnerability and controllability of networks
of networks,'' Chaos, Solitons Fractals, vol. 80, pp. 125-138, Nov.
2015.
[97] M. Bellingeri and D. Cassi, " Robustness of weighted networks,''
Phys. A, Stat. Mech. Appl., vol. 489, pp. 47-55, Jan. 2018.
[98] G. Chen, Y. Lou, and L. Wang, " A comparative study on controllability
robustness of complex networks,'' IEEE Trans. Circuits Syst. II, Exp.
Briefs, vol. 66, no. 5, pp. 828-832, May 2019.
[99] S. P. Borgatti, " Centrality and network flow,'' Social Netw., vol. 27,
no. 1, pp. 55-71, 2005.
[100] L. Katz, " A new status index derived from sociometric analysis,''
Psychometrika, vol. 18, no. 1, pp. 39-43, 1953.
[101] R. Yi-Run et al., " Node importance measurement based on neighborhood
similarity in complex network,'' Acta Phys. Sinica, vol. 66, no. 3,
2017, Art. no. 038902.
[102] M. Šimon et al., " Combined heuristic attack strategy on complex
networks,'' Math. Problems Eng., vol. 2017, pp. 1-9, Sep. 2017.
[103] H. Yang and S. An, " Critical nodes identification in complex networks,''
Symmetry, vol. 12, no. 1, p. 123, Jan. 2020.
[104] B. R. D. Cunha, J. C. González-Avella, and S. Gonçalves, " Fast fragmentation
of networks using module-based attacks,'' PLoS ONE, vol. 10,
no. 11, Nov. 2015, Art. no. e0142824.
[105] S. Shai et al., " Critical tipping point distinguishing two types of
transitions in modular network structures,'' Phys. Rev. E, Stat. Phys.
Plasmas Fluids Relat. Interdiscip. Top., vol. 92, no. 6, 2015, Art. no. 062805.
[106] X. Ren et al., " Generalized network dismantling,'' Proc. Nat. Acad.
Sci. USA, vol. 116, no. 14, pp. 6554-6559, Apr. 2019.
[107] Z.-M. Lu and X.-F. Li, " Attack vulnerability of network controllability,''
PLoS ONE, vol. 11, no. 9, Sep. 2016, Art. no. e0162289.
[108] Y. Hao et al., " Vulnerability of complex networks under threelevel-tree
attacks,'' Phys. A, Stat. Mech. Appl., vol. 462, pp. 674-683,
Apr. 016.
[109] C.-L. Pu and W. Cui, " Vulnerability of complex networks under
pathbased attacks,'' Phys. A, Stat. Mech. Appl., vol. 328, nos. 1-2,
pp. 274-286, 2003.
[110] X. Li and G. Chen, " A local-world evolving network model,'' Phys. A,
Stat. Mech. Appl., vol. 328, nos. 1-2, pp. 274-286, Oct. 2003.
34
IEEE CIRCUITS AND SYSTEMS MAGAZINE
[111] S. Sun et al., " Towards structural controllability of local-world networks,''
Phys. Lett. A, vol. 380, nos. 22-23, pp. 1912-1917, May 2016.
[112] H. Wang et al., " Damage attack on complex networks,'' Phys. A,
Stat. Mech. Appl., vol. 408, pp. 134-148, Aug. 2014.
[113] W. Lin, S. Wandelt, and X. Sun, " Efficient network dismantling
through genetic algorithms,'' Soft Comput., vol. 26, no. 6, pp. 3107-3125,
Mar. 2022.
[114] Z. Yang and J. Liu, " A memetic algorithm for determining the nodal
attacks with minimum cost on complex networks,'' Phys. A, Stat. Mech.
Appl., vol. 503, pp. 1041-1053, Aug. 2018.
[115] Y. Lou, L. Wang, and G. Chen, " A framework of hierarchical attacks
to network controllability,'' Commun. Nonlinear Sci. Numer. Simul.,
vol. 98, Jul. 2021, Art. no. 105780.
[116] R. M. Karp, " Reducibility among combinatorial problems,'' in Complexity
of Computer Computations. Springer, 1972, pp. 85-103.
[117] A. Braunstein et al., " Network dismantling,'' Proc. Nat. Acad. Sci.
USA, vol. 113, no. 44, pp. 12368-12373, Nov. 2016.
[118] X. Zhang et al., " Optimization of disintegration strategy for multiedges
complex networks,'' in Proc. IEEE Congr. Evol. Comput. (CEC),
Jul. 2016, pp. 522-528.
[119] M. Lozano et al., " Optimizing network attacks by artificial bee
colony,'' Inf. Sci., vol. 377, pp. 30-50, Jan. 2017.
[120] Y. Deng, J. Wu, and Y.-J. Tan, " Optimal attack strategy of complex
networks based on Tabu search,'' Phys. A, Stat. Mech. Appl., vol. 442,
pp. 74-81, Jan. 2016.
[121] M. Qi et al., " Optimal disintegration strategy in multiplex networks,''
Chaos, Interdiscipl. J. Nonlinear Sci., vol. 28, no. 12, Dec. 2018,
Art. no. 121104.
[122] M. Ventresca, " Global search algorithms using a combinatorial
unranking-based problem representation for the critical node
detection problem,'' Comput. Oper. Res., vol. 39, no. 11, pp. 2763-2775,
Nov. 2012.
[123] Q. Li, S.-Y. Liu, and X.-S. Yang, " Neighborhood information-based
probabilistic algorithm for network disintegration,'' Expert Syst. Appl.,
vol. 139, Jan. 2020, Art. no. 112853.
[124] X. Li et al., " A new complex network robustness attack algorithm,''
in Proc. ACM Int. Symp. Blockchain Secure Crit. Infrastruct., Jul. 2019,
pp. 13-17.
[125] P. Velicˇkovic´ et al., " Graph attention networks,'' 2017, arXiv:1710.10903.
[126]
M. Grassia, M. De Domenico, and G. Mangioni, " Machine learning
dismantling and early-warning signals of disintegration in complex systems,''
Nature Commun., vol. 12, no. 1, Aug. 2021, Art. no. 5190.
[127] C. Fan et al., " Finding key players in complex networks through
deep reinforcement learning,'' Nature Mach. Intell., vol. 2, no. 6,
pp. 317-324, May 2020.
[128] V. Mnih et al., " Human-level control through deep reinforcement
learning,'' Nature, vol. 518, no. 7540, pp. 529-533, 2015.
[129] R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction.
Cambridge, MA, USA: MIT Press, 2018.
[130] J. Yan et al., " Q-learning-based vulnerability analysis of smart grid
against sequential topology attacks,'' IEEE Trans. Inf. Forensics Security,
vol. 12, no. 1, pp. 200-210, Jan. 2017.
[131] M. Tian, Z. Dong, and X. Wang, " Reinforcement learning approach
for robustness analysis of complex networks with incomplete
information,'' Chaos, Solitons Fractals, vol. 144, Mar. 2021, Art.
no. 110643.
[132] D. Yan et al., " Hypernetwork dismantling via deep reinforcement
learning,'' IEEE Trans. Netw. Sci. Eng., vol. 9, no. 5, pp. 3302-3315, Sep./
Oct. 2022.
[133] T. N. Kipf and M. Welling, " Semi-supervised classification with
graph convolutional networks,'' 2016, arXiv:1609.02907.
[134] W. L. Hamilton, R. Ying, and J. Leskovec, " Inductive representation
learning on large graphs,'' in Proc. Int. Conf. Neural Inf. Process. Syst.
(NeurIPS), 2017, pp. 1025-1035.
[135] W. L. Hamilton, " Graph representation learning,'' Synth. Lectures
Artif. Intell. Mach. Learn., vol. 14, no. 3, pp. 1-159, 2020.
[136] M. Zhang et al., " A new approach for evaluating node importance
in complex networks via deep learning methods,'' Neurocomputing,
vol. 497, pp. 13-27, Aug. 2022.
[137] Q. Cai et al., " Robustness evaluation of multipartite complex networks
based on percolation theory,'' IEEE Trans. Syst., Man, Cybern.,
Syst., vol. 51, no. 10, pp. 6244-6257, Oct. 2021.
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