PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA
and SSDF Attacks in Energy Constrained Cognitive Radio Networks

J 2019

PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks

PATNAIK, Milan, V. KAMAKOTI, Václav MATYÁŠ and Vojtěch ŘEHÁK

Basic information

Original name

PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks

Authors

PATNAIK, Milan (356 India, guarantor, belonging to the institution), V. KAMAKOTI (356 India), Václav MATYÁŠ (203 Czech Republic, belonging to the institution) and Vojtěch ŘEHÁK (203 Czech Republic, belonging to the institution)

Edition

IEEE Transactions on Cognitive Communications and Networking, 2019, 2332-7731

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 4.574

RIV identification code

RIV/00216224:14330/19:00107446

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1109/TCCN.2019.2913397

UT WoS

000471115000017

Keywords in English

Cognitive Radio (CR); Primary User Emulation; Attack (PUEA); Spectrum Sensing Data Falsification (SSDF); Denial of Service (DoS); Model Predictive Control (MPC); Chernoff Bounds

Abstract

V originále

Malicious users can exploit vulnerabilities in Cognitive Radio Networks (CRNs) and cause heavy performance degradation by Denial of Service (DoS) attacks. During operation, Cognitive Radios (CRs) spend a considerable amount of time to identify idle (free) channels for transmission. In addition, CRs also need additional security mechanisms to prevent malicious attacks. Proactive Model Predictive Control (MPC) based medium access control (MAC) protocols for CRs can quicken the idle channel identification by predicting future states of channels in advance. This provides enough time for CRs to carry out other calculations like DoS attack detection. However, such external detection techniques use additional power that makes them inappropriate for energy constrained applications. As a solution, this paper proposes a proactive learning based MAC protocol (PROLEMus) that shows immunity to two prominent CR based DoS attacks, namely Primary User Emulation Attack (PUEA) and Spectrum Sensing Data Falsification (SSDF) attack, without any external detection mechanism. PROLEMus shows an average of 6:2%, 8:9% and 12:4% improvement in channel utilization, backoff rate and sensing delay, respectively, with low prediction errors ( 1:8%) saving 19:65% energy, when compared to recently proposed MAC protocols like ProMAC aided with additional DoS attack detection mechanism.

Links

GBP202/12/G061, research and development project

Name: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Acronym: CE-ITI)

Investor: Czech Science Foundation

Citovat

PATNAIK, Milan, V. KAMAKOTI, Václav MATYÁŠ and Vojtěch ŘEHÁK. PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks. IEEE Transactions on Cognitive Communications and Networking. 2019, vol. 5, No 2, p. 400-412. ISSN 2332-7731. Available from: https://dx.doi.org/10.1109/TCCN.2019.2913397.

@article{1537756,
   author = {Patnaik, Milan and Kamakoti, V. and Matyáš, Václav and Řehák, Vojtěch},
   article_number = {2},
   doi = {http://dx.doi.org/10.1109/TCCN.2019.2913397},
   keywords = {Cognitive Radio (CR); Primary User Emulation; Attack (PUEA); Spectrum Sensing Data Falsification (SSDF); Denial of Service (DoS); Model Predictive Control (MPC); Chernoff Bounds},
   language = {eng},
   issn = {2332-7731},
   journal = {IEEE Transactions on Cognitive Communications and Networking},
   title = {PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks},
   url = {http://dx.doi.org/10.1109/TCCN.2019.2913397},
   volume = {5},
   year = {2019}
}

TY  - JOUR
ID  - 1537756
AU  - Patnaik, Milan - Kamakoti, V. - Matyáš, Václav - Řehák, Vojtěch
PY  - 2019
TI  - PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks
JF  - IEEE Transactions on Cognitive Communications and Networking
VL  - 5
IS  - 2
SP  - 400-412
EP  - 400-412
SN  - 23327731
KW  - Cognitive Radio (CR)
KW  - Primary User Emulation
KW  - Attack (PUEA)
KW  - Spectrum Sensing Data Falsification (SSDF)
KW  - Denial of Service (DoS)
KW  - Model Predictive Control (MPC)
KW  - Chernoff Bounds
UR  - http://dx.doi.org/10.1109/TCCN.2019.2913397
L2  - http://dx.doi.org/10.1109/TCCN.2019.2913397
N2  - Malicious users can exploit vulnerabilities in Cognitive Radio Networks (CRNs) and cause heavy performance degradation by Denial of Service (DoS) attacks. During operation, Cognitive Radios (CRs) spend a considerable amount of time to identify idle (free) channels for transmission. In addition, CRs also need additional security mechanisms to prevent malicious attacks. Proactive Model Predictive Control (MPC) based medium access control (MAC) protocols for CRs can quicken the idle channel identification by predicting future states of channels in advance. This provides enough time for CRs to carry out other calculations like DoS attack detection. However, such external detection techniques use additional power that makes them inappropriate for energy constrained applications. As a solution, this paper proposes a proactive learning based MAC protocol (PROLEMus) that shows immunity to two prominent CR based DoS attacks, namely Primary User Emulation Attack (PUEA) and Spectrum Sensing Data Falsification (SSDF) attack, without any external detection mechanism. PROLEMus shows an average of 6:2%, 8:9% and 12:4% improvement in channel utilization, backoff rate and sensing delay, respectively, with low prediction errors ( 1:8%) saving 19:65% energy, when compared to recently proposed MAC protocols like ProMAC aided with additional DoS attack detection mechanism.
ER  -

PATNAIK, Milan, V. KAMAKOTI, Václav MATYÁŠ and Vojtěch ŘEHÁK. PROLEMus: A Proactive Learning-Based MAC Protocol Against PUEA and SSDF Attacks in Energy Constrained Cognitive Radio Networks. \textit{IEEE Transactions on Cognitive Communications and Networking}. 2019, vol.~5, No~2, p.~400-412. ISSN~2332-7731. Available from: https://dx.doi.org/10.1109/TCCN.2019.2913397.

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