Standard
A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks. / D'Antonio, Salvatore; Romano, Simon
; Simpson, Steven et al.
Self-Organizing Systems: Third International Workshop, IWSOS 2008, Vienna, Austria, December 10-12, 2008. Proceedings. ed. / Karin Anna Hummel; James P.G. Sterbenz. Berlin: Springer, 2008. p. 230-241 (Lecture Notes in Computer Science; Vol. 5343).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
D'Antonio, S, Romano, S
, Simpson, S, Smith, P & Hutchison, D 2008,
A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks. in KA Hummel & JPG Sterbenz (eds),
Self-Organizing Systems: Third International Workshop, IWSOS 2008, Vienna, Austria, December 10-12, 2008. Proceedings. Lecture Notes in Computer Science, vol. 5343, Springer, Berlin, pp. 230-241, Third International Workshop on Self-Organising Systems, Vienna, Austria,
10/12/08.
https://doi.org/10.1007/978-3-540-92157-8_20
APA
D'Antonio, S., Romano, S.
, Simpson, S., Smith, P., & Hutchison, D. (2008).
A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks. In K. A. Hummel, & J. P. G. Sterbenz (Eds.),
Self-Organizing Systems: Third International Workshop, IWSOS 2008, Vienna, Austria, December 10-12, 2008. Proceedings (pp. 230-241). (Lecture Notes in Computer Science; Vol. 5343). Springer.
https://doi.org/10.1007/978-3-540-92157-8_20
Vancouver
D'Antonio S, Romano S
, Simpson S, Smith P, Hutchison D.
A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks. In Hummel KA, Sterbenz JPG, editors, Self-Organizing Systems: Third International Workshop, IWSOS 2008, Vienna, Austria, December 10-12, 2008. Proceedings. Berlin: Springer. 2008. p. 230-241. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-92157-8_20
Author
Bibtex
@inproceedings{036e5bc353ad4676800b30029bc4d673,
title = "A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks",
abstract = "A suitable strategy for network intrusion tolerance—detecting intrusions and remedying them—depends on aspects of the domain being protected, such as the kinds of intrusion faced, the resources available for monitoring and remediation, and the level at which automated remediation can be carried out. The decision to remediate autonomically will have to consider the relative costs of performing a potentially disruptive remedy in the wrong circumstances and leaving it up to a slow, but more accurate, human operator. Autonomic remediation also needs to be withdrawn at some point {\^a} a phase of recovery to the normal network state. In this paper, we present a framework for deploying domain-adaptable intrusion-tolerance strategies in heterogeneous networks. Functionality is divided into that which is fixed by the domain and that which should adapt, in order to cope with heterogeneity. The interactions between detection and remediation are considered in order to make a stable recovery decision. We also present a model for combining diverse sources of monitoring to improve accurate decision making, an important pre-requisite to automated remediation. ",
keywords = "network resilience, intersection project",
author = "Salvatore D'Antonio and Simon Romano and Steven Simpson and Paul Smith and David Hutchison",
year = "2008",
month = oct,
doi = "10.1007/978-3-540-92157-8_20",
language = "English",
isbn = "9783540921561",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "230--241",
editor = "Hummel, {Karin Anna} and Sterbenz, {James P.G.}",
booktitle = "Self-Organizing Systems",
note = "Third International Workshop on Self-Organising Systems ; Conference date: 10-12-2008 Through 12-12-2008",
}
RIS
TY - GEN
T1 - A Semi-autonomic Framework for Intrusion Tolerance in Heterogeneous Networks
AU - D'Antonio, Salvatore
AU - Romano, Simon
AU - Simpson, Steven
AU - Smith, Paul
AU - Hutchison, David
PY - 2008/10
Y1 - 2008/10
N2 - A suitable strategy for network intrusion tolerance—detecting intrusions and remedying them—depends on aspects of the domain being protected, such as the kinds of intrusion faced, the resources available for monitoring and remediation, and the level at which automated remediation can be carried out. The decision to remediate autonomically will have to consider the relative costs of performing a potentially disruptive remedy in the wrong circumstances and leaving it up to a slow, but more accurate, human operator. Autonomic remediation also needs to be withdrawn at some point â a phase of recovery to the normal network state. In this paper, we present a framework for deploying domain-adaptable intrusion-tolerance strategies in heterogeneous networks. Functionality is divided into that which is fixed by the domain and that which should adapt, in order to cope with heterogeneity. The interactions between detection and remediation are considered in order to make a stable recovery decision. We also present a model for combining diverse sources of monitoring to improve accurate decision making, an important pre-requisite to automated remediation.
AB - A suitable strategy for network intrusion tolerance—detecting intrusions and remedying them—depends on aspects of the domain being protected, such as the kinds of intrusion faced, the resources available for monitoring and remediation, and the level at which automated remediation can be carried out. The decision to remediate autonomically will have to consider the relative costs of performing a potentially disruptive remedy in the wrong circumstances and leaving it up to a slow, but more accurate, human operator. Autonomic remediation also needs to be withdrawn at some point â a phase of recovery to the normal network state. In this paper, we present a framework for deploying domain-adaptable intrusion-tolerance strategies in heterogeneous networks. Functionality is divided into that which is fixed by the domain and that which should adapt, in order to cope with heterogeneity. The interactions between detection and remediation are considered in order to make a stable recovery decision. We also present a model for combining diverse sources of monitoring to improve accurate decision making, an important pre-requisite to automated remediation.
KW - network resilience
KW - intersection project
U2 - 10.1007/978-3-540-92157-8_20
DO - 10.1007/978-3-540-92157-8_20
M3 - Conference contribution/Paper
SN - 9783540921561
T3 - Lecture Notes in Computer Science
SP - 230
EP - 241
BT - Self-Organizing Systems
A2 - Hummel, Karin Anna
A2 - Sterbenz, James P.G.
PB - Springer
CY - Berlin
T2 - Third International Workshop on Self-Organising Systems
Y2 - 10 December 2008 through 12 December 2008
ER -