Standard

Incorporating Attack-Type Uncertainty into Network Protection. / Garnaev, A.; Baykal-Gursoy, M.; Poor, H.V.

в: IEEE Transactions on Information Forensics and Security, Том 9, № 8, 2014, стр. 1278-1287.

Результаты исследований: Научные публикации в периодических изданияхстатья

Harvard

Garnaev, A, Baykal-Gursoy, M & Poor, HV 2014, 'Incorporating Attack-Type Uncertainty into Network Protection', IEEE Transactions on Information Forensics and Security, Том. 9, № 8, стр. 1278-1287. https://doi.org/10.1109/TIFS.2014.2329241

APA

Garnaev, A., Baykal-Gursoy, M., & Poor, H. V. (2014). Incorporating Attack-Type Uncertainty into Network Protection. IEEE Transactions on Information Forensics and Security, 9(8), 1278-1287. https://doi.org/10.1109/TIFS.2014.2329241

Vancouver

Garnaev A, Baykal-Gursoy M, Poor HV. Incorporating Attack-Type Uncertainty into Network Protection. IEEE Transactions on Information Forensics and Security. 2014;9(8):1278-1287. https://doi.org/10.1109/TIFS.2014.2329241

Author

Garnaev, A. ; Baykal-Gursoy, M. ; Poor, H.V. / Incorporating Attack-Type Uncertainty into Network Protection. в: IEEE Transactions on Information Forensics and Security. 2014 ; Том 9, № 8. стр. 1278-1287.

BibTeX

@article{7336a67f456b4ecd80050fbf99842de1,
title = "Incorporating Attack-Type Uncertainty into Network Protection",
abstract = "Network security against possible attacks involves making decisions under uncertainty. Not only may one be ignorant of the place, the power, or the time of potential attacks, one may also be largely ignorant of the attacker's purpose. To illustrate this phenomenon, this paper proposes a simple Bayesian game-theoretic model of allocating defensive (scanning) effort among nodes of a network in which a network's defender does not know the adversary's motivation for intruding on the network, e.g., to bring the maximal damage to the network (for example, to steal credit card numbers or information on bank accounts stored there) or to infiltrate the network for other purposes (for example, to corrupt nodes for a further distributed denial of service botnet attack on servers). Due to limited defensive capabilities, the defender faces the dilemma of either: 1) focusing on increasing defense of the most valuable nodes, and in turn, increasing the chance for the adversary to sneak into the network through less valuable",
author = "A. Garnaev and M. Baykal-Gursoy and H.V. Poor",
year = "2014",
doi = "10.1109/TIFS.2014.2329241",
language = "English",
volume = "9",
pages = "1278--1287",
journal = "IEEE Transactions on Information Forensics and Security",
issn = "1556-6013",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "8",

}

RIS

TY - JOUR

T1 - Incorporating Attack-Type Uncertainty into Network Protection

AU - Garnaev, A.

AU - Baykal-Gursoy, M.

AU - Poor, H.V.

PY - 2014

Y1 - 2014

N2 - Network security against possible attacks involves making decisions under uncertainty. Not only may one be ignorant of the place, the power, or the time of potential attacks, one may also be largely ignorant of the attacker's purpose. To illustrate this phenomenon, this paper proposes a simple Bayesian game-theoretic model of allocating defensive (scanning) effort among nodes of a network in which a network's defender does not know the adversary's motivation for intruding on the network, e.g., to bring the maximal damage to the network (for example, to steal credit card numbers or information on bank accounts stored there) or to infiltrate the network for other purposes (for example, to corrupt nodes for a further distributed denial of service botnet attack on servers). Due to limited defensive capabilities, the defender faces the dilemma of either: 1) focusing on increasing defense of the most valuable nodes, and in turn, increasing the chance for the adversary to sneak into the network through less valuable

AB - Network security against possible attacks involves making decisions under uncertainty. Not only may one be ignorant of the place, the power, or the time of potential attacks, one may also be largely ignorant of the attacker's purpose. To illustrate this phenomenon, this paper proposes a simple Bayesian game-theoretic model of allocating defensive (scanning) effort among nodes of a network in which a network's defender does not know the adversary's motivation for intruding on the network, e.g., to bring the maximal damage to the network (for example, to steal credit card numbers or information on bank accounts stored there) or to infiltrate the network for other purposes (for example, to corrupt nodes for a further distributed denial of service botnet attack on servers). Due to limited defensive capabilities, the defender faces the dilemma of either: 1) focusing on increasing defense of the most valuable nodes, and in turn, increasing the chance for the adversary to sneak into the network through less valuable

U2 - 10.1109/TIFS.2014.2329241

DO - 10.1109/TIFS.2014.2329241

M3 - Article

VL - 9

SP - 1278

EP - 1287

JO - IEEE Transactions on Information Forensics and Security

JF - IEEE Transactions on Information Forensics and Security

SN - 1556-6013

IS - 8

ER -

ID: 5733817