Noticeable key points and issues of sensor deployment for large area Wireless Sensor Network: A survey

Gupta, Pallavi; Prakash, Vinay; Suman, Preetam

doi:10.1109/sysmart.2016.7894511

Cited by 7 publications

(4 citation statements)

References 20 publications

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“…In [ 98 ], some challenges, such as security, routing of data, etc., were studied in addition to application types of WSN. Reference [ 99 ] discussed most of the factors that should be considered when planning WSN deployment for targeted usage. These factors include the communication range of nodes, sensing range, deployment strategy, etc.…”

Section: State-of-the-artmentioning

confidence: 99%

Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights

Dangana

Ansari

Abbasi

et al. 2021

Sensors

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The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications.

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Section: State-of-the-artmentioning

confidence: 99%

Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights

Dangana

Ansari

Abbasi

et al. 2021

Sensors

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“…If a WSN consists of a cluster, false report insertion attacks are divided into two cases when the cluster head (CH) node that generates the report is compromised and when the member (MB) node that creates the authentication key is compromised. If the CH node is compromised, the attacker generates an arbitrary report and transmits it to the next node, causing false notification and energy exhaustion problems of intermediate nodes in the routing path [5][6]. If the MB node is compromised, it can generate a false event notification to the CH node, depleting the node energy of the cluster region and deploy incapacitating nodes.…”

Section: Figure 1: False Report Injection Attackmentioning

confidence: 99%

Method for the Period Determination of Security Level Update in Statistical en-Route Filtering

Cho

Ahn

2017

Int. J. Res. Granthaalayah

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Energy management of WSN is one of the major issues. Many kind of attacks in WSN paralyze the network by exhausting node energy. Especially false report insertion attack, which is one of the several WSN attacks, is to inform users of false alarms as well as unnecessary energy consumption. F. Ye et al. proposed statistical en-route filtering to prevent false report injection attacks. In order to effectively use their scheme, techniques for determining thresholds using fuzzy logic have been studied. To effectively apply these techniques to the network, an appropriate security level period update should be set according to the network environments. In this paper, we propose a security period update method using fuzzy logic in order to improve the lifetime of the network in the statistical en-route filtering approach based on a wireless sensor network of the cluster environment. Normally SEF thresholds should be changed by a user according to the network environment. Our proposed method allows automatically setting the effective threshold for the environment by fuzzy logic. The experimental results show that the energy efficiency increased by 26.5%.

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“…False Report Injection attacks can exhaust all the energy of the all nodes in repetitive attacks. This problem reduces the networks lifetime or disables the networks [10][11][12]. In addition, The BS informs the user of the wrong information and causes confusion and time loss.…”

Section: Introductionmentioning

confidence: 99%

Prevention Method of False Report Generation in Cluser Heads for Dynamic En-Route Filtering of Wireless Sensor Networks

Ahn¹,

Cho²

2017

IJCSIT

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Wireless sensor networks collect data through collaborative communication between sensor nodes. sensor nodes of wireless sensor networks are deployed in open environments. Hence, an attacker can easily compromise the node. An attacker can compromise a node to generate false reports and inject into the network. This causes unnecessary energy consumption in the process of transmitting false alarm messages and false data reports to the system. If the attacker keeps repeatedly attacking thereby causing problems such as reduction in the entire network life or disabling the networks. Yu and Guan proposed a dynamic en-route filtering scheme to detect and drop these false reports before reaching to the Base station. In the dynamic en-route filtering, the energy waste of the intermediate nodes occurs until it is detected early. In this paper, we propose a method to save the energy of the intermediate nodes by searching for the compromised node and blocking the reports generated at that node. When verifying a false report at the verification node, it can know report information. The base station is able to find the cluster of compromised nodes using that information. In particular, the base station can know the location of the node that has been compromised, we can block false alarms and energy losses by blocking reports generated in that cluster.

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Noticeable key points and issues of sensor deployment for large area Wireless Sensor Network: A survey

Cited by 7 publications

References 20 publications

Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights

Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights

Method for the Period Determination of Security Level Update in Statistical en-Route Filtering

Prevention Method of False Report Generation in Cluser Heads for Dynamic En-Route Filtering of Wireless Sensor Networks

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