IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v466y2017icp211-223.html
   My bibliography  Save this article

Resistance maximization principle for defending networks against virus attack

Author

Listed:
  • Li, Angsheng
  • Zhang, Xiaohui
  • Pan, Yicheng

Abstract

We investigate the defending of networks against virus attack. We define the resistance of a network to be the maximum number of bits required to determine the code of the module that is accessible from random walk, from which random walk cannot escape. We show that for any network G, R(G)=H1(G)−H2(G), where R(G) is the resistance of G, H1(G) and H2(G) are the one- and two-dimensional structural information of G, respectively, and that resistance maximization is the principle for defending networks against virus attack. By using the theory, we investigate the defending of real world networks and of the networks generated by the preferential attachment and the security models. We show that there exist networks that are defensible by a small number of controllers from cascading failure of any virus attack. Our theory demonstrates that resistance maximization is the principle for defending networks against virus attacks.

Suggested Citation

  • Li, Angsheng & Zhang, Xiaohui & Pan, Yicheng, 2017. "Resistance maximization principle for defending networks against virus attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 211-223.
    • Handle: RePEc:eee:phsmap:v:466:y:2017:i:c:p:211-223
    DOI: 10.1016/j.physa.2016.09.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116306252
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.09.009?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. Li, Angsheng & Li, Jiankou & Pan, Yicheng, 2015. "Discovering natural communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 878-896.
    2. Jianxi Gao & Baruch Barzel & Albert-László Barabási, 2016. "Universal resilience patterns in complex networks," Nature, Nature, vol. 530(7590), pages 307-312, February.
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    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. Yin, Likang & Deng, Yong, 2018. "Toward uncertainty of weighted networks: An entropy-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 176-186.

    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. 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).
    2. Hayato Goto & Hideki Takayasu & Misako Takayasu, 2017. "Estimating risk propagation between interacting firms on inter-firm complex network," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    3. Aura Reggiani, 2022. "The Architecture of Connectivity: A Key to Network Vulnerability, Complexity and Resilience," Networks and Spatial Economics, Springer, vol. 22(3), pages 415-437, September.
    4. Cerqueti, Roy & Ferraro, Giovanna & Iovanella, Antonio, 2019. "Measuring network resilience through connection patterns," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 320-329.
    5. Wu, Chengxing & Duan, Dongli, 2024. "Collapse process prediction of mutualistic dynamical networks with k-core and dimension reduction method," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    6. Pramesh Singh & Jayaram Uparna & Panagiotis Karampourniotis & Emoke-Agnes Horvat & Boleslaw Szymanski & Gyorgy Korniss & Jonathan Z Bakdash & Brian Uzzi, 2018. "Peer-to-peer lending and bias in crowd decision-making," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-18, March.
    7. Zhang, Jianhua & Hu, Funian & Wang, Shuliang & Dai, Yang & Wang, Yixing, 2016. "Structural vulnerability and intervention of high speed railway networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 743-751.
    8. Rui Ding, 2019. "The Complex Network Theory-Based Urban Land-Use and Transport Interaction Studies," Complexity, Hindawi, vol. 2019, pages 1-14, June.
    9. Lv, Changchun & Yuan, Ziwei & Si, Shubin & Duan, Dongli, 2021. "Robustness of scale-free networks with dynamical behavior against multi-node perturbation," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    10. Yu, Yang & Deng, Ye & Tan, Suo-Yi & Wu, Jun, 2018. "Efficient disintegration strategy in directed networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 435-442.
    11. Gao, Yan-Li & Chen, Shi-Ming & Nie, Sen & Ma, Fei & Guan, Jun-Jie, 2018. "Robustness analysis of interdependent networks under multiple-attacking strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 495-504.
    12. Didier Wernli & Lucas Böttcher & Flore Vanackere & Yuliya Kaspiarovich & Maria Masood & Nicolas Levrat, 2023. "Understanding and governing global systemic crises in the 21st century: A complexity perspective," Global Policy, London School of Economics and Political Science, vol. 14(2), pages 207-228, May.
    13. Prasan Ratnayake & Sugandima Weragoda & Janaka Wansapura & Dharshana Kasthurirathna & Mahendra Piraveenan, 2021. "Quantifying the Robustness of Complex Networks with Heterogeneous Nodes," Mathematics, MDPI, vol. 9(21), pages 1-20, November.
    14. Matteo Cinelli & Giovanna Ferraro & Antonio Iovanella, 2017. "Resilience of Core-Periphery Networks in the Case of Rich-Club," Complexity, Hindawi, vol. 2017, pages 1-12, December.
    15. Fabrizio Lillo & Giorgio Rizzini, 2024. "Modelling shock propagation and resilience in financial temporal networks," Papers 2407.09340, arXiv.org.
    16. Marcus Engsig & Alejandro Tejedor & Yamir Moreno & Efi Foufoula-Georgiou & Chaouki Kasmi, 2024. "DomiRank Centrality reveals structural fragility of complex networks via node dominance," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    17. Lv, Changchun & Yuan, Ziwei & Si, Shubin & Duan, Dongli & Yao, Shirui, 2022. "Cascading failure in networks with dynamical behavior against multi-node removal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    18. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    19. Ryan M. Hynes & Bernardo S. Buarque & Ronald B. Davies & Dieter F. Kogler, 2020. "Hops, Skip & a Jump - The Regional Uniqueness of Beer Styles," Working Papers 202013, Geary Institute, University College Dublin.
    20. Lenore Newman & Ann Dale, 2007. "Homophily and Agency: Creating Effective Sustainable Development Networks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 9(1), pages 79-90, February.

    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:phsmap:v:466:y:2017:i:c:p:211-223. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.