The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'identification des sources d'infection dans un réseau, y compris le sponsor d'une rumeur sur le réseau, les serveurs qui injectent des virus informatiques dans un réseau informatique ou le patient zéro dans un réseau de maladies infectieuses, joue un rôle essentiel dans la limitation des dommages causés par l'infection. . Dans cet article, un estimateur à deux sources est d'abord construit sur la base de partitions de régions d'infection. Pendant ce temps, le problème d'estimation à deux sources est transformé en calcul de l'attente du nombre de permutations autorisées qui peut être simplifié en un problème d'estimation à source unique dans une région d'infection déterminée. Un algorithme heuristique est également proposé pour promouvoir l'estimateur vers des graphiques généraux selon une méthode de recherche en largeur d'abord (BFS). Des résultats expérimentaux sont fournis pour vérifier les performances de notre méthode et illustrer les variations de détection d'erreurs dans différents réseaux.
Liang ZHU
Nanjing University of Posts and Telecommunications
Youguo WANG
Nanjing University of Posts and Telecommunications
Jian LIU
Nanjing University of Finance and Economics
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Liang ZHU, Youguo WANG, Jian LIU, "A Two-Sources Estimator Based on the Expectation of Permitted Permutations Count in Complex Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E104-A, no. 2, pp. 576-581, February 2021, doi: 10.1587/transfun.2020EAL2035.
Abstract: Identifying the infection sources in a network, including the sponsor of a network rumor, the servers that inject computer virus into a computer network, or the zero-patient in an infectious disease network, plays a critical role in limiting the damage caused by the infection. A two-source estimator is firstly constructed on basis of partitions of infection regions in this paper. Meanwhile, the two-source estimation problem is transformed into calculating the expectation of permitted permutations count which can be simplified to a single-source estimation problem under determined infection region. A heuristic algorithm is also proposed to promote the estimator to general graphs in a Breadth-First-Search (BFS) fashion. Experimental results are provided to verify the performance of our method and illustrate variations of error detection in different networks.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2035/_p
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@ARTICLE{e104-a_2_576,
author={Liang ZHU, Youguo WANG, Jian LIU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Two-Sources Estimator Based on the Expectation of Permitted Permutations Count in Complex Networks},
year={2021},
volume={E104-A},
number={2},
pages={576-581},
abstract={Identifying the infection sources in a network, including the sponsor of a network rumor, the servers that inject computer virus into a computer network, or the zero-patient in an infectious disease network, plays a critical role in limiting the damage caused by the infection. A two-source estimator is firstly constructed on basis of partitions of infection regions in this paper. Meanwhile, the two-source estimation problem is transformed into calculating the expectation of permitted permutations count which can be simplified to a single-source estimation problem under determined infection region. A heuristic algorithm is also proposed to promote the estimator to general graphs in a Breadth-First-Search (BFS) fashion. Experimental results are provided to verify the performance of our method and illustrate variations of error detection in different networks.},
keywords={},
doi={10.1587/transfun.2020EAL2035},
ISSN={1745-1337},
month={February},}
Copier
TY - JOUR
TI - A Two-Sources Estimator Based on the Expectation of Permitted Permutations Count in Complex Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 576
EP - 581
AU - Liang ZHU
AU - Youguo WANG
AU - Jian LIU
PY - 2021
DO - 10.1587/transfun.2020EAL2035
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2021
AB - Identifying the infection sources in a network, including the sponsor of a network rumor, the servers that inject computer virus into a computer network, or the zero-patient in an infectious disease network, plays a critical role in limiting the damage caused by the infection. A two-source estimator is firstly constructed on basis of partitions of infection regions in this paper. Meanwhile, the two-source estimation problem is transformed into calculating the expectation of permitted permutations count which can be simplified to a single-source estimation problem under determined infection region. A heuristic algorithm is also proposed to promote the estimator to general graphs in a Breadth-First-Search (BFS) fashion. Experimental results are provided to verify the performance of our method and illustrate variations of error detection in different networks.
ER -