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 a Vojtěch ŘEHÁK

Základní údaje

Originální název

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

Autoři

PATNAIK, Milan (356 Indie, garant, domácí), V. KAMAKOTI (356 Indie), Václav MATYÁŠ (203 Česká republika, domácí) a Vojtěch ŘEHÁK (203 Česká republika, domácí)

Vydání

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

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 4.574

Kód RIV

RIV/00216224:14330/19:00107446

Organizační jednotka

Fakulta informatiky

UT WoS

000471115000017

Klíčová slova anglicky

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

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 28. 4. 2020 07:36, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

GBP202/12/G061, projekt VaV
Název: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Akronym: CE-ITI)
Investor: Grantová agentura ČR, Centrum excelence - Institut teoretické informatiky