Details
| Original language | English |
|---|---|
| Title of host publication | Smart Information and Knowledge Management |
| Subtitle of host publication | Advances, Challenges, and Critical Issues |
| Editors | Edward Szczerbicki, Ngoc Thanh Nguyen |
| Pages | 1-26 |
| Number of pages | 26 |
| ISBN (electronic) | 978-3-642-04584-4 |
| Publication status | Published - 2010 |
Publication series
| Name | Studies in Computational Intelligence |
|---|---|
| Volume | 260 |
| ISSN (Print) | 1860-949X |
Abstract
During the last years approaches inspired by biological immune systems showed promising results in the field of misbehavior detection and classification of data in general. In this chapter we give a comprehensive overview on the recent developments in the area of biologically inspired classification approaches of possible threats and misbehavior, especially in the area of ad hoc networks. We discuss numerous immuno related approaches, such as negative selection, B-cell cloning, Dendritic cell algorithm or Danger signals. We review present approaches and address their applicability to ad hoc networks. We further discuss challenges in translating functionality of the biological immune system to technical systems.
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
Cite this
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Smart Information and Knowledge Management: Advances, Challenges, and Critical Issues. ed. / Edward Szczerbicki; Ngoc Thanh Nguyen. 2010. p. 1-26 (Studies in Computational Intelligence; Vol. 260).
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Immuno-inspired knowledge management for ad hoc wireless networks
AU - Drozda, Martin
AU - Schaust, Sven
AU - Szczerbicka, Helena
N1 - This work was supported by the German Research Foundation (DFG) under the grant no. SZ 51/24-2 (Survivable Ad Hoc Networks – SANE).
PY - 2010
Y1 - 2010
N2 - During the last years approaches inspired by biological immune systems showed promising results in the field of misbehavior detection and classification of data in general. In this chapter we give a comprehensive overview on the recent developments in the area of biologically inspired classification approaches of possible threats and misbehavior, especially in the area of ad hoc networks. We discuss numerous immuno related approaches, such as negative selection, B-cell cloning, Dendritic cell algorithm or Danger signals. We review present approaches and address their applicability to ad hoc networks. We further discuss challenges in translating functionality of the biological immune system to technical systems.
AB - During the last years approaches inspired by biological immune systems showed promising results in the field of misbehavior detection and classification of data in general. In this chapter we give a comprehensive overview on the recent developments in the area of biologically inspired classification approaches of possible threats and misbehavior, especially in the area of ad hoc networks. We discuss numerous immuno related approaches, such as negative selection, B-cell cloning, Dendritic cell algorithm or Danger signals. We review present approaches and address their applicability to ad hoc networks. We further discuss challenges in translating functionality of the biological immune system to technical systems.
UR - http://www.scopus.com/inward/record.url?scp=74049103683&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04584-4_1
DO - 10.1007/978-3-642-04584-4_1
M3 - Contribution to book/anthology
AN - SCOPUS:74049103683
SN - 9783642045837
T3 - Studies in Computational Intelligence
SP - 1
EP - 26
BT - Smart Information and Knowledge Management
A2 - Szczerbicki, Edward
A2 - Nguyen, Ngoc Thanh
ER -