IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v106y2018icp61-66.html
   My bibliography  Save this article

Multi-node attack strategy of complex networks due to cascading breakdown

Author

Listed:
  • Chaoqi, Fu
  • Ying, Wang
  • Xiaoyang, Wang
  • Yangjun, Gao

Abstract

Studying attack strategy of complex networks is the basis of investigating network characteristics such as robustness, invulnerability, and network security. Knowing means of attack can help us take more effective measures to ensure network security. Presently, most research conclusions focus on a single vertex being attacked, and the choice of a set of attack nodes is also limited to a complete understanding of network information. In this paper, considering the effect of cascading failure, we focus on the multi-node attack strategy. Our results showed that the distance between attack targets has a great effect on the attacking effect. Taking both the average avalanche scale and maximum destruction size into account, when the distance between attack targets was 2, the network suffered the most serious damage. If the information about the network was unclear, we presented 3 kinds of conditional attack strategies. Under the condition of different tolerance coefficients and different degrees of known information, each strategy had its own unique advantages. In conclusion, the research in this paper supports the easy and quick selection of attack targets under the condition of incomplete information.

Suggested Citation

  • Chaoqi, Fu & Ying, Wang & Xiaoyang, Wang & Yangjun, Gao, 2018. "Multi-node attack strategy of complex networks due to cascading breakdown," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 61-66.
    • Handle: RePEc:eee:chsofr:v:106:y:2018:i:c:p:61-66
    DOI: 10.1016/j.chaos.2017.11.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077917304654
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2017.11.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    2. Flaviano Morone & Hernán A. Makse, 2015. "Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 524(7563), pages 65-68, August.
    3. Wang, Jianwei & Rong, Lili & Zhang, Liang & Zhang, Zhongzhi, 2008. "Attack vulnerability of scale-free networks due to cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6671-6678.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Wensheng & Karimi, Faezeh & Khalilpour, Kaveh & Green, David & Varvarigos, Manos, 2023. "Robustness analysis of electricity networks against failure or attack: The case of the Australian National Electricity Market (NEM)," International Journal of Critical Infrastructure Protection, Elsevier, vol. 41(C).
    2. Wu, Tao & Xian, Xingping & Zhong, Linfeng & Xiong, Xi & Stanley, H. Eugene, 2018. "Power iteration ranking via hybrid diffusion for vital nodes identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 802-815.
    3. Ma, Lili, 2019. "Studying node centrality based on the hidden hyperbolic metric space of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 426-434.
    4. Xia, Ling-Ling & Song, Yu-Rong & Li, Chan-Chan & Jiang, Guo-Ping, 2018. "Improved targeted immunization strategies based on two rounds of selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 540-547.
    5. Yibo Dong & Jin Liu & Jiaqi Ren & Zhe Li & Weili Li, 2023. "Protecting Infrastructure Networks: Solving the Stackelberg Game with Interval-Valued Intuitionistic Fuzzy Number Payoffs," Mathematics, MDPI, vol. 11(24), pages 1-18, December.
    6. Gangwal, Utkarsh & Singh, Mayank & Pandey, Pradumn Kumar & Kamboj, Deepak & Chatterjee, Samrat & Bhatia, Udit, 2022. "Identifying early-warning indicators of onset of sudden collapse in networked infrastructure systems against sequential disruptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    7. Ma, Xiangyu & Zhou, Huijie & Li, Zhiyi, 2021. "On the resilience of modern power systems: A complex network perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    8. Wu, Jiajing & You, Wei & Wu, Taocheng & Xia, Yongxiang, 2018. "Abnormal phenomenon in robustness of complex networks with heterogeneous node functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 451-461.
    9. Peng, Peng & Poon, Jessie P.H. & Yang, Yu & Lu, Feng & Cheng, Shifen, 2019. "Global oil traffic network and diffusion of influence among ports using real time data," Energy, Elsevier, vol. 172(C), pages 333-342.
    10. Meisam Akbarzadeh & Soroush Memarmontazerin & Sybil Derrible & Sayed Farzin Salehi Reihani, 2019. "The role of travel demand and network centrality on the connectivity and resilience of an urban street system," Transportation, Springer, vol. 46(4), pages 1127-1141, August.
    11. Wang, Jianwei & Jiang, Chen & Qian, Jianfei, 2014. "Robustness of interdependent networks with different link patterns against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 535-541.
    12. Wang, Zhixiao & Zhao, Ya & Xi, Jingke & Du, Changjiang, 2016. "Fast ranking influential nodes in complex networks using a k-shell iteration factor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 171-181.
    13. Feng, Zhidan & Song, Huimin & Qi, Xingqin, 2024. "A novel algorithm for the generalized network dismantling problem based on dynamic programming," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    14. Ping Pei & Haihan Zhang & Huizhen Zhang & Chen Yang & Tianbo An, 2024. "Network Synchronization via Pinning Control from an Attacker-Defender Game Perspective," Mathematics, MDPI, vol. 12(12), pages 1-17, June.
    15. Zhu, Weihua & Liu, Kai & Wang, Ming & Yan, Xiaoyong, 2018. "Enhancing robustness of metro networks using strategic defense," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1081-1091.
    16. Kizhakkedath, A. & Tai, K., 2021. "Vulnerability analysis of critical infrastructure network," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    17. Xiao-Long Ren & Niels Gleinig & Dijana Tolić & Nino Antulov-Fantulin, 2018. "Underestimated Cost of Targeted Attacks on Complex Networks," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    18. Li Zeng & Changjun Fan & Chao Chen, 2023. "Leveraging Minimum Nodes for Optimum Key Player Identification in Complex Networks: A Deep Reinforcement Learning Strategy with Structured Reward Shaping," Mathematics, MDPI, vol. 11(17), pages 1-13, August.
    19. Alexandru Topîrceanu, 2022. "Benchmarking Cost-Effective Opinion Injection Strategies in Complex Networks," Mathematics, MDPI, vol. 10(12), pages 1-16, June.
    20. Peng, Xingzhao & Yao, Hong & Du, Jun & Wang, Zhe & Ding, Chao, 2015. "Invulnerability of scale-free network against critical node failures based on a renewed cascading failure model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 69-77.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:106:y:2018:i:c:p:61-66. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.