Detection of jammer in Wireless Sensor Network

Nancy, J. Thangapoo; Vijayakumar, K. P.; Kumar, Pankaj

doi:10.1109/iccsp.2014.6950086

Cited by 7 publications

(5 citation statements)

References 3 publications

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“…Hence, our approach increases the jamming detection rate or credible of jamming detection. Figures 10,11,and 12 show the comparison of TDR with various configurations of 5, 25, and 50 members of proposed system with the existing systems. The comparison result represents that the proposed approach has improved the TDR and negligible FDR than the existing approaches.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…9 The various possible metrics 10 explored for jamming detection. These metrics are, PDR, 11 PLR, carrier sensing time (CST), packet sent ratio (PSR), bit error rate (BER), received signal strength indicator (RSSI), and bad packet ratio (BPR). The author used packets dropped per terminal (PDPT) and SNR metrics for detection of jamming in sensor network.…”

Section: Related Workmentioning

confidence: 99%

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Rapid jamming detection approach based on fuzzy in WSN

Kanagasabapathy

Poornachary

Murugan

et al. 2019

Int J Communication

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It is necessary for securing wireless sensor networks from jamming, since these networks are easily attacked by jammers. Jamming may be made by either external jammer node or internal node, which may become as an adversary in future. In this paper, two approaches are proposed in the cluster-based sensor network to detect the maliciousness level of nodes to secure sensor networks from jamming attacks. First approach detects maliciousness level of nodes using two modules, namely, certification module and monitoring module. Certification module defends the network from the jammers. Monitoring module discovers the sensor nodes that are jammed by a jammer. Second approach uses fuzzy logic for optimizing the jamming metrics to determine the occurrence of jamming accurately. The proposed system achieves 99.58% detection ratio to determine node's maliciousness level.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Rapid jamming detection approach based on fuzzy in WSN

Kanagasabapathy

Poornachary

Murugan

et al. 2019

Int J Communication

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show abstract

“…Some of papers show attacks classified on pasive and active (Shahzad et al, 2017). Radio interference attack is described in Hamieh et al (2009), Nancy et al (2014) and Hamza et al (2016).…”

Section: Related Workmentioning

confidence: 99%

“…Such as putting node into sleep mode during the duration of jam signal, in order to preserve power efficiency, also periodically waking up nodes in order to check if the jamming signal is still active (Ghildiyal et al, 2014). In the paper (Nancy et al, 2014), the new approach for detection and protection from jamming attacks, is described. This approach uses two modules which determine the level of interference in WSN.…”

Section: Gavrić and Simićmentioning

confidence: 99%

Overview of DOS attacks on wireless sensor networks and experimental results for simulation of interference attacks

Gavrić

Simić

2018

Ing. Inv.

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Wireless sensor networks are now used in various fields. The information transmitted in the wireless sensor networks is very sensitive, so the security issue is very important. DOS (denial of service) attacks are a fundamental threat to the functioning of wireless sensor networks. This paper describes some of the most common DOS attacks and potential methods of protection against them. The case study shows one of the most frequent attacks on wireless sensor networks -the interference attack. In the introduction of this paper authors assume that the attack interference can cause significant obstruction of wireless sensor networks. This assumption has been proved in the case study through simulation scenario and simulation results. RESUMENLas redes de sensores inalámbricos se utilizan ahora en varios campos. La información transmitida en las redes de sensores inalámbricos es muy delicada, por lo que el tema de la seguridad es muy importante. Los ataques de DOS (Denegación de servicio) son una amenaza fundamental para el funcionamiento de las redes de sensores inalámbricos. Este documento describe algunos de los ataques DOS más comunes y los posibles métodos de protección contra ellos. El estudio de caso muestra uno de los ataques más frecuentes a las redes de sensores inalámbricos: el ataque de interferencia. En la introducción de este artículo, los autores suponen que la interferencia de ataque puede causar una obstrucción significativa de las redes de sensores inalámbricos. Esta suposición se ha demostrado en el estudio de caso a través de escenarios de simulación y los resultados de estas simulaciones.Palabras clave: Redes de sensores inalámbricos, detección de intrusión, comunicación inalámbrica, seguridad del sistema de comunicación, interferencia de radiofrecuencia.

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“…Due to this Jammers attack, the efficiency of the wireless communication drastically decreases. Thus different methods are need to be found to detect the presence of the jammers or the jamming device, to avoid them in the transmission process [1][2].…”

Section: Introductionmentioning

confidence: 99%

Broadcasting the Message Over the Network Using Different Frequency and Timing Technique to Bypass the Jammers

Pooja.S¹

2016

IJRET

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The author addresses the problem of Jammers present in wireless network by jamming the user signals by adding more interference signals. This paper gives the solution to recover the jamming signals to receive the emergency broadcasting message. This paper implements a novel time-delayed broadcast scheme (TDBS). The transmissions are unicast and are broadcasted in a series in consideration with time and frequency. TDBS neither reckons on the secrets that are shared nor on the controlling channels of the jammer system for coordinating the broadcasts. Instead there is presence of Pseudo Noise (PN) frequency hopping system which is unique and followed by every single node. TDBS is divergent from the designs of Frequency Hopping Spread Spectrum (FHSS) and these nodes do not follow the same Frequency Hopping (FH) sequence, instead they are deputized with unique ones. Contradicting to every other typical broadcast where all the receivers have similar channels, TDBS have the transmissions that are unicast and present in series to broadcast the messages using time and frequency. For the flexibility of the jammers present inside, the unicast transmissions location that is defined by the frequency band are partially known to the subset of receivers. By making an assumption that the jammers can thwart with very few number of frequency bands, the subset of transmissions are thwart-free and thus proliferating the broadcasted messages.

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Detection of jammer in Wireless Sensor Network

Cited by 7 publications

References 3 publications

Rapid jamming detection approach based on fuzzy in WSN

Rapid jamming detection approach based on fuzzy in WSN

Overview of DOS attacks on wireless sensor networks and experimental results for simulation of interference attacks

Broadcasting the Message Over the Network Using Different Frequency and Timing Technique to Bypass the Jammers

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