On the Routing Protocol Influence on the Resilience of Wireless Sensor Networks to Jamming Attacks

Del-Valle-Soto, Carolina; Mex-Perera, Carlos; Monroy, Raúl; Nolazco-Flores, Juan Arturo

doi:10.3390/s150407619

Cited by 22 publications

(27 citation statements)

References 16 publications

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“…In reactive jamming, for MAC-layer protocols using Backward Error Correction, such as go-back-n or repetitive select, the attack would be successful if at least one bit of the packet is altered. Reactive jammer is energy efficient, because only transmits when it detects a packet, and therefore it is harder to detect since it could mimic packet collisions that are caused by normal traffic activity in the network [ 9 , 10 ].…”

Section: Reactive Jamming Attackmentioning

confidence: 99%

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MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks

Del-Valle-Soto

Mex-Perera²,

Monroy

et al. 2017

Sensors

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In this work, we present the design of a mitigation scheme for jamming attacks integrated to the routing protocols MPH, AODV, and DSR. The resulting protocols are named MPH-M (Multi-Parent Hierarchical - Modified), AODV-M (Ad hoc On Demand Distance Vector - Modified), and DSR-M (Dynamic Source Routing - Modified). For the mitigation algorithm, if the detection algorithm running locally in each node produces a positive result then the node is isolated; second, the routing protocol adapts their paths avoiding the isolated nodes. We evaluated how jamming attacks affect different metrics for all these modified protocols. The metrics we employ to detect jamming attack are number of packet retransmissions, number of CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) retries while waiting for an idle channel and the energy wasted by the node. The metrics to evaluate the performance of the modified routing protocols are the throughput and resilience of the system and the energy used by the nodes. We evaluated all the modified protocols when the attacker position was set near, middle and far of the collector node. The results of our evaluation show that performance for MPH-M is much better than AODV-M and DSR-M. For example, the node energy for MPH-M is 138.13% better than AODV-M and 126.07% better than DSR-M. Moreover, we also find that MPH-M benefits much more of the mitigation scheme than AODV-M and DSR-M. For example, the node energy consumption is 34.61% lower for MPH-M and only 3.92% and 3.42% for AODV-M and DSR-M, respectively. On throughput, the MPH protocol presents a packet reception efficiency at the collector node of 16.4% on to AODV and DSR when there is no mitigation mechanism. Moreover, MPH-M has an efficiency greater than 7.7% with respect to AODV-M and DSR-M when there is a mitigation scheme. In addition, we have that with the mitigation mechanism AODV-M and DSR-M do not present noticeable modification. However, MPH-M improves its efficiency by 8.4%. We also measure the resilience of these algorithms from the average packet re-transmissions perspective, and we find that MPH-M has around a 15% lower change rate than AODV-M and DSR-M. The MPH-M recovery time is 5 s faster than AODV-M and 2 s faster than DSR-M.

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Section: Reactive Jamming Attackmentioning

confidence: 99%

“…The jamming detection model considers energy consumption, an average number of packet re-transmissions and the average number of retrials in the inner loop of the CSMA/CA algorithm. These three metrics have previously shown to be affected by jamming conditions [ 10 , 11 ].…”

Section: Proposed Mitigation Mechanism For Jamming Attacksmentioning

confidence: 99%

MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks

Del-Valle-Soto

Mex-Perera²,

Monroy

et al. 2017

Sensors

Self Cite

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“…This process helps: i) To filter out external malicious clients from entering the network; and, ii) To bind a unique IP address with the ad hoc ID of the client. IP address is not only useful to uniquely identify the client in the global communication scenario but also helps to fix accountability to the participating clients [12]. Any registered client found guilty can be fixed and such clients can be eliminated from the network.…”

Section: Requirement and Challenges Of Proposed Protocolmentioning

confidence: 99%

Secure ID-Based Routing for Data Communication in IoT

Singh¹

2017

EAI Endorsed Trans IoT

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Internet of Things is rising technology that could inspire the way wireless network access is provided. In IoT, secure data communication has lot of research scope. Especially message authentication, authorization cure path for IoT devices still remains as an open research problem. Some researcher proposed security mechanism without certification, MIC and token but still we didn’t find standard security mechanism for data communication between sensor nodes. In this article author has proposed an Identity based security (IBS) mechanism for IoT devices during data communication in IoT networks. IBS mechanism uses identity-based cryptography (IBC) to avoid certificates, MIC and tokens to minimize the computational overhead. IBS Mechanism is resistant to most common security attacks such as modification, fabrication, replay attacks and it can also protect hop count. It does provide secure data communication between sensor nodes. The results, based on NS-3 simulation, reveal that proposed mechanism is effectively able to protect the black hole attacks. In results, we have shown the packet delivery ratio, quality of services (QoS), and throughput between IBS mechanism, AODV path and AODV with black hole.

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“…For LTE systems, jamming is also regarded as a major attack that causes significant DoS [7,8]. While most works have focused on the physical-layer aspects of jamming attacks, reference [9] evaluates the resilience of WSNs to jamming attacks in the aspect of the routing protocol.…”

Section: Introductionmentioning

confidence: 99%

Random Access Performance of Distributed Sensors Attacked by Unknown Jammers

Jeong

Wui

Kim

2017

Sensors

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In this paper, we model and investigate the random access (RA) performance of sensor nodes (SN) in a wireless sensor network (WSN). In the WSN, a central head sensor (HS) collects the information from distributed SNs, and jammers disturb the information transmission primarily by generating interference. In this paper, two jamming attacks are considered: power and code jamming. Power jammers (if they are friendly jammers) generate noises and, as a result, degrade the quality of the signal from SNs. Power jamming is equally harmful to all the SNs that are accessing HS and simply induces denial of service (DoS) without any need to hack HS or SNs. On the other hand, code jammers mimic legitimate SNs by sending fake signals and thus need to know certain system parameters that are used by the legitimate SNs. As a result of code jamming, HS falsely allocates radio resources to SNs. The code jamming hence increases the failure probability in sending the information messages, as well as misleads the usage of radio resources. In this paper, we present the probabilities of successful preamble transmission with power ramping according to the jammer types and provide the resulting throughput and delay of information transmission by SNs, respectively. The effect of two jamming attacks on the RA performances is compared with numerical investigation. The results show that, compared to RA without jammers, power and code jamming degrade the throughput by up to 30.3% and 40.5%, respectively, while the delay performance by up to 40.1% and 65.6%, respectively.

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On the Routing Protocol Influence on the Resilience of Wireless Sensor Networks to Jamming Attacks

Cited by 22 publications

References 16 publications

MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks

MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks

Secure ID-Based Routing for Data Communication in IoT

Random Access Performance of Distributed Sensors Attacked by Unknown Jammers

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