A Fog Computing Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks

Yaseen, Qussai; Albalas, Firas; Jararweh, Yaser; Al‐Ayyoub, Mahmoud

doi:10.1109/fas-w.2016.60

Cited by 50 publications

(35 citation statements)

References 12 publications

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“…The paper is an extension to a previous study . This version provides complete and comprehensive details about the contribution by extending the proposed model and all sections.…”

Section: Introductionmentioning

confidence: 99%

Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks

Yaseen

Albalas

Jararwah

et al. 2017

Trans Emerging Tel Tech

Self Cite

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Selective forwarding is a major problem in wireless sensor networks (WSNs). The nature of sensor environments and the sensitivity of collected measurements in some fields such as war fields increase the need to prevent, detect, or mitigate the problem. One of the most used countermeasures for such problem is the use of voting system based on watchdogs' votes. However, this approach is not applicable in the case of mobile sensors. Mobile WSNs (MWSNs) is growing immensely due to the exposure of applications of mobile computing, vehicular networks, and Internet of things. This exposure has shed light on the security of using mobile sensors and raises the need to set appropriate methods for securing MWSNs against many attacks such as selective forwarding attacks. This paper introduces the problem of selective forwarding in MWSNs and discusses how the voting system used for mitigation; this problem in WSNs is not applicable in handling the problem in MWSNs due to sensors mobility. Therefore, the paper proposes a model that provides a global monitoring capability for tracing moving sensors and detecting malicious ones. The model leverages the infrastructure of fog computing to achieve this purpose. In addition, the paper suggests using software defined systems to be used along with the proposed model, which generalize the model to be used to secure MWSNs against other types of attacks easily and flexibly. The paper provides a complete algorithm, a comprehensive discussion and experiments that show the correctness and importance of the proposed approach.

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“…The paper is an extension to a previous study . This version provides complete and comprehensive details about the contribution by extending the proposed model and all sections.…”

Section: Introductionmentioning

confidence: 99%

Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks

Yaseen

Albalas

Jararwah

et al. 2017

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, fog computing framework has been more and more popular in IoT applications [26][27][28][29]. In [30], a mobile WSN is applied to intrusion detection, and fog computing is applied to improve the network performance. A three-tier model is proposed where WSN is a bottom tier.…”

Section: Related Workmentioning

confidence: 99%

Boundary Region Detection for Continuous Objects in Wireless Sensor Networks

Zhang

Wang

Meng

et al. 2018

Wireless Communications and Mobile Computing

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Industrial Internet of Things has been widely used to facilitate disaster monitoring applications, such as liquid leakage and toxic gas detection. Since disasters are usually harmful to the environment, detecting accurate boundary regions for continuous objects in an energy-efficient and timely fashion is a long-standing research challenge. This article proposes a novel mechanism for continuous object boundary region detection in a fog computing environment, where sensing holes may exist in the deployed network region. Leveraging sensory data that have been gathered, interpolation algorithms have been applied to estimate sensory data at certain geographical locations, in order to estimate a more accurate boundary line. To examine whether estimated sensory data reflect that fact, mobile sensors are adopted to traverse these locations for gathering their sensory data, and the boundary region is calibrated accordingly. Experimental evaluation shows that this technique can generate a precise object boundary region with certain time constraints, and the network lifetime can be prolonged significantly.

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“…Because of this problem, a new MWSN detection scheme is needed. Qussai Yaseen et al proposed fog computing-based selective forwarding attack detection [6]. This technique detects selective forwarding attacks in MWSNs using fog computing and watchdog.…”

Section: B Selective Forwarding Attack Detectionmentioning

confidence: 99%

“…This attack can be seen as a threatening attack in a military or hostile environment because important packets are lost. Selective forwarding attack detection based on fog computing is a technique to detect selective forwarding attacks using a fog server and watchdog in a MWSN environment [6]. However, since a single path is used, important packets are dropped during selective forwarding attack detection.…”

Section: Introductionmentioning

confidence: 99%

Improving the Energy Efficiency of Fog Computing-Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks Using Multipath Route

Chung

2017

ijarcs

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Selective forwarding attacks in mobile wireless sensor networks are difficult to detect because they selectively delete packets. Such attacks are more dangerous than selective forwarding attacks in wireless sensor networks because it is difficult to detect a selective forwarding attack that occurs on sensor nodes with high mobility. In order to detect such attacks, a fog computing-based selective forwarding attack detection technique has been proposed. However, in the ad hoc on-demand distance vector (AODV) routing scheme using a single path, all packets are dropped until a selective forwarding attack is detected. In addition, energy consumption for path re-setting is significant because sensor nodes move frequently. To solve this problem, we propose a selective forwarding attack detection method using an ad hoc on-demand multipath distance vector (AOMDV) routing technique. The proposed scheme increases the packet transmission probability to the BS and increases the energy efficiency of the sensor network. Experiments with the proposed method show that the energy efficiency of the sensor network is improved by about 10%.

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A Fog Computing Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks

Cited by 50 publications

References 12 publications

Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks

Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks

Boundary Region Detection for Continuous Objects in Wireless Sensor Networks

Improving the Energy Efficiency of Fog Computing-Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks Using Multipath Route

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