Abstract
Dynamic spectrum access has been proposed as a means to share scarce radio resources, and requires devices to follow protocols that use resources in a proper, disciplined manner. For a cognitive radio network to achieve this goal, spectrum policies and the ability to enforce them are necessary. Detection of an unauthorized (anomalous) usage is one of the critical issues in spectrum etiquette enforcement. In this paper, we present a network structure for dynamic spectrum access and formulate the anomalous usage detection problem using statistical significance testing. The detection problem is classified into two subproblems. For the case where no authorized signal is present, we describe the existing cooperative sensing schemes and investigate the impact of signal path loss on their performance. For the case where an authorized signal is present, we propose three methods that detect anomalous transmissions by making use of the characteristics of radio propagation. Analytical models are formulated for two special cases and, due to the intractability of the general problem, we present an algorithm using machine learning techniques to solve the general case. Our simulation results show that our approaches can effectively detect unauthorized spectrum usage with high detection rate and low false positive rate.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE INFOCOM 2009 - The 28th Conference on Computer Communications |
| Pages | 675-683 |
| Number of pages | 9 |
| DOIs | |
| State | Published - Oct 12 2009 |
| Event | 28th Conference on Computer Communications, IEEE INFOCOM 2009 - Rio de Janeiro, Brazil Duration: Apr 19 2009 → Apr 25 2009 |
Publication series
| Name | Proceedings - IEEE INFOCOM |
|---|---|
| ISSN (Print) | 0743-166X |
Other
| Other | 28th Conference on Computer Communications, IEEE INFOCOM 2009 |
|---|---|
| Country | Brazil |
| City | Rio de Janeiro |
| Period | 4/19/09 → 4/25/09 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Electrical and Electronic Engineering
Cite this
}
ALDO : An anomaly detection framework for dynamic spectrum access networks. / Liu, Song; Chen, Yingying; Trappe, Wade; Greenstein, Larry J.
IEEE INFOCOM 2009 - The 28th Conference on Computer Communications. 2009. p. 675-683 5061975 (Proceedings - IEEE INFOCOM).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - ALDO
T2 - An anomaly detection framework for dynamic spectrum access networks
AU - Liu, Song
AU - Chen, Yingying
AU - Trappe, Wade
AU - Greenstein, Larry J.
PY - 2009/10/12
Y1 - 2009/10/12
N2 - Dynamic spectrum access has been proposed as a means to share scarce radio resources, and requires devices to follow protocols that use resources in a proper, disciplined manner. For a cognitive radio network to achieve this goal, spectrum policies and the ability to enforce them are necessary. Detection of an unauthorized (anomalous) usage is one of the critical issues in spectrum etiquette enforcement. In this paper, we present a network structure for dynamic spectrum access and formulate the anomalous usage detection problem using statistical significance testing. The detection problem is classified into two subproblems. For the case where no authorized signal is present, we describe the existing cooperative sensing schemes and investigate the impact of signal path loss on their performance. For the case where an authorized signal is present, we propose three methods that detect anomalous transmissions by making use of the characteristics of radio propagation. Analytical models are formulated for two special cases and, due to the intractability of the general problem, we present an algorithm using machine learning techniques to solve the general case. Our simulation results show that our approaches can effectively detect unauthorized spectrum usage with high detection rate and low false positive rate.
AB - Dynamic spectrum access has been proposed as a means to share scarce radio resources, and requires devices to follow protocols that use resources in a proper, disciplined manner. For a cognitive radio network to achieve this goal, spectrum policies and the ability to enforce them are necessary. Detection of an unauthorized (anomalous) usage is one of the critical issues in spectrum etiquette enforcement. In this paper, we present a network structure for dynamic spectrum access and formulate the anomalous usage detection problem using statistical significance testing. The detection problem is classified into two subproblems. For the case where no authorized signal is present, we describe the existing cooperative sensing schemes and investigate the impact of signal path loss on their performance. For the case where an authorized signal is present, we propose three methods that detect anomalous transmissions by making use of the characteristics of radio propagation. Analytical models are formulated for two special cases and, due to the intractability of the general problem, we present an algorithm using machine learning techniques to solve the general case. Our simulation results show that our approaches can effectively detect unauthorized spectrum usage with high detection rate and low false positive rate.
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UR - http://www.scopus.com/inward/citedby.url?scp=70349696172&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2009.5061975
DO - 10.1109/INFCOM.2009.5061975
M3 - Conference contribution
AN - SCOPUS:70349696172
SN - 9781424435135
T3 - Proceedings - IEEE INFOCOM
SP - 675
EP - 683
BT - IEEE INFOCOM 2009 - The 28th Conference on Computer Communications
ER -