On the Robustness of Cascade Diffusion under Node Attacks

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Standard

On the Robustness of Cascade Diffusion under Node Attacks. / Logins, Alvis; Li, Yuchen; Karras, Panagiotis.

WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery, 2020. p. 2711–2717.

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Harvard

Logins, A, Li, Y & Karras, P 2020, On the Robustness of Cascade Diffusion under Node Attacks. in WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery, pp. 2711–2717, WWW '20, Taipei , Taiwan, 20/04/2020. https://doi.org/10.1145/3366423.3380028

APA

Logins, A., Li, Y., & Karras, P. (2020). On the Robustness of Cascade Diffusion under Node Attacks. In WWW'20 : Proceedings of the Web Conference 2020 (pp. 2711–2717). Association for Computing Machinery. https://doi.org/10.1145/3366423.3380028

CBE

Logins A, Li Y, Karras P. 2020. On the Robustness of Cascade Diffusion under Node Attacks. In WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery. pp. 2711–2717. https://doi.org/10.1145/3366423.3380028

MLA

Logins, Alvis, Yuchen Li, and Panagiotis Karras "On the Robustness of Cascade Diffusion under Node Attacks". WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery. 2020, 2711–2717. https://doi.org/10.1145/3366423.3380028

Vancouver

Logins A, Li Y, Karras P. On the Robustness of Cascade Diffusion under Node Attacks. In WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery. 2020. p. 2711–2717 https://doi.org/10.1145/3366423.3380028

Author

Logins, Alvis ; Li, Yuchen ; Karras, Panagiotis. / On the Robustness of Cascade Diffusion under Node Attacks. WWW'20 : Proceedings of the Web Conference 2020. Association for Computing Machinery, 2020. pp. 2711–2717

Bibtex

@inproceedings{5a9427c3004b4db7a4b94e8e42a6a29c,
title = "On the Robustness of Cascade Diffusion under Node Attacks",
abstract = "How can we assess a network's ability to maintain its functionality under attacks? Network robustness has been studied extensively in the case of deterministic networks. However, applications such as online information diffusion and the behavior of networked public raise a question of robustness in probabilistic networks. We propose three novel robustness measures for networks hosting a diffusion under the Independent Cascade (IC) model, susceptible to node attacks. The outcome of such a process depends on the selection of its initiators, or seeds, by the seeder, as well as on two factors outside the seeder's discretion: the attack strategy and the probabilistic diffusion outcome. We consider three levels of seeder awareness regarding these two uncontrolled factors, and evaluate the network's viability aggregated over all possible extents of node attacks. We introduce novel algorithms from building blocks found in previous works to evaluate the proposed measures. A thorough experimental study with synthetic and real, scale-free and homogeneous networks establishes that these algorithms are effective and efficient, while the proposed measures highlight differences among networks in terms of robustness and the surprise they furnish when attacked. Last, we devise a new measure of diffusion entropy that can inform the design of probabilistically robust networks.",
author = "Alvis Logins and Yuchen Li and Panagiotis Karras",
year = "2020",
month = apr,
doi = "10.1145/3366423.3380028",
language = "English",
pages = "2711–2717",
booktitle = "WWW'20",
publisher = "Association for Computing Machinery",
note = "WWW '20 : The Web Conference 2020 ; Conference date: 20-04-2020 Through 24-04-2020",

}

RIS

TY - GEN

T1 - On the Robustness of Cascade Diffusion under Node Attacks

AU - Logins, Alvis

AU - Li, Yuchen

AU - Karras, Panagiotis

PY - 2020/4

Y1 - 2020/4

N2 - How can we assess a network's ability to maintain its functionality under attacks? Network robustness has been studied extensively in the case of deterministic networks. However, applications such as online information diffusion and the behavior of networked public raise a question of robustness in probabilistic networks. We propose three novel robustness measures for networks hosting a diffusion under the Independent Cascade (IC) model, susceptible to node attacks. The outcome of such a process depends on the selection of its initiators, or seeds, by the seeder, as well as on two factors outside the seeder's discretion: the attack strategy and the probabilistic diffusion outcome. We consider three levels of seeder awareness regarding these two uncontrolled factors, and evaluate the network's viability aggregated over all possible extents of node attacks. We introduce novel algorithms from building blocks found in previous works to evaluate the proposed measures. A thorough experimental study with synthetic and real, scale-free and homogeneous networks establishes that these algorithms are effective and efficient, while the proposed measures highlight differences among networks in terms of robustness and the surprise they furnish when attacked. Last, we devise a new measure of diffusion entropy that can inform the design of probabilistically robust networks.

AB - How can we assess a network's ability to maintain its functionality under attacks? Network robustness has been studied extensively in the case of deterministic networks. However, applications such as online information diffusion and the behavior of networked public raise a question of robustness in probabilistic networks. We propose three novel robustness measures for networks hosting a diffusion under the Independent Cascade (IC) model, susceptible to node attacks. The outcome of such a process depends on the selection of its initiators, or seeds, by the seeder, as well as on two factors outside the seeder's discretion: the attack strategy and the probabilistic diffusion outcome. We consider three levels of seeder awareness regarding these two uncontrolled factors, and evaluate the network's viability aggregated over all possible extents of node attacks. We introduce novel algorithms from building blocks found in previous works to evaluate the proposed measures. A thorough experimental study with synthetic and real, scale-free and homogeneous networks establishes that these algorithms are effective and efficient, while the proposed measures highlight differences among networks in terms of robustness and the surprise they furnish when attacked. Last, we devise a new measure of diffusion entropy that can inform the design of probabilistically robust networks.

U2 - 10.1145/3366423.3380028

DO - 10.1145/3366423.3380028

M3 - Article in proceedings

SP - 2711

EP - 2717

BT - WWW'20

PB - Association for Computing Machinery

T2 - WWW '20

Y2 - 20 April 2020 through 24 April 2020

ER -