An Efficient Trust-Based Routing Model for Clustered-Based Hetrogeneous Wireless Sensor Network

An Efficient Trust-Based Routing Model for Clustered-Based Hetrogeneous Wireless Sensor Network

Gousia Thaniyath (Visveswaraiyah, India)
DOI: 10.4018/IJBDCN.2020070105
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Wireless sensor networks (WSN) play a very important role in providing real-time data access for big data and IoT application. The open deployment, energy constraint, and lack of centralized administration makes WSN very vulnerable to various kinds of malicious attacks. In WSN, identifying malicious sensor device and eliminating their sensed information play very important roles for mission critical applications. Standard cryptography and authentication schemes cannot be directly used in WSN because of the resource constraint nature of sensor devices. Thus, energy efficient and low latency methodology is required for minimizing the impact of malicious sensor devices. This paper presents a secure and load balanced routing (SLBR) scheme for heterogeneous clustered-based WSN. SLBR present better trust-based security metric that overcomes the problem when sensor keep oscillating for good to bad state and vice versa, and also balance load among CH. Thus, they aid in achieving better security, packet transmission, and energy efficiency performance. Experiments are conducted to evaluate the performance of proposed SLBR model over existing trust-based routing model, namely exponential cat swarm optimization (ECSO). The result attained shows SLBR models attain better performance than ECSO in terms of energy efficiency (i.e., network lifetime considering first sensor device death and total sensor device death), communication overhead, throughput, packet processing latency, malicious sensor device misclassification rate, and identification.
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1. Introduction

The Internet of Things (IoT’s) is defined as the network of physical devices and other equipment embedded with internet connection and sensors (Roman et al., 2013), IoT gives the flexibility to the interconnected objects to sense and control the certain framework and this leads to the direct integration of computational model and physical world. Furthermore the interconnection between these objects has ability to transfer the data with minimal human interaction, meanwhile it also provides the unique identifiers (Middleton et al., 2013). Moreover, IoT has been applicable to our daily life scenario and its application includes such as transportation, healthcare, building management, wearable devices and smart home. IoT application can be categorized into different category such as consumer application, Industrial applications, commercial applications, Infrastructure applications, Military applications, Intelligence application. WSN (Wireless Senor Network) has been one of the important aspects of IoT applications; it constitutes several autonomous small sensor node for the data transmission. Furthermore, it also provide the access point for the humans, WSN has many applications and it is applicable almost everywhere such as in agriculture, country security and transportation to name a few. Meanwhile WSN possesses inherent features as it can be deployed in any environment (mainly hostile) and gives the unreliable transmission, such networks are vulnerable to the numerous threats (Chen et al., 2009). Let us take for an instance cyber criminals try to exploit the poorly configured terminal to corrupt the data or steal the data through placement of unauthorized hotspot and mislead the end-users. Hence, in order to overcome the problem efficient security model needs to be designed.

Cryptography based method is the conventional method to secure the network (Agrawal et al., 2019; Fröhlich et al,. 2019). Cryptography method addresses many issues such as authentication, truthfulness, confidentiality, and certification. However due to diverse nature of WSN, traditional approach fails miserably. Furthermore, the main disadvantage of cryptography technique is its complex computation, this makes the cryptographies strategies unsuitable for wireless sensor network, and it is observed that these strategies had higher energy overhead (Singh et al., 2015). Hence, for overcoming such issue IDS (Intrusion Detection System) has been employed for provisioning security mechanism (Abduvaliyev et al., 2013). Intrusion detection system aims to detect the sensor device behavior or the eminent feature related to sensor device, meanwhile trust-based model have gained popularity in P2P (Peer 2 Peer) as well as WSN networks for effective security against the internal attacks (Singh et al., 2015; Abduvaliyev et al., 2013). IDS have several application in WSN; security routing is one of them, where the designed algorithm chooses the most secured paths based on the trust evaluation of adjacent sensor devices (Khalid et al., 2013). Moreover, (Ganeriwal & Srivastava 2004) introduced the first trust model for WSN, the framework was distributed reputation (Al-Dabbagh et al., 2018) and elaborated in (Ganeriwal & Srivastava 2004) and it tried to detect the faulty sensor devices in accordance with the transactional data among the neighbor sensor devices. However, the term “cooperativeness” discusses in the (Ganeriwal & Srivastava 2004) means the data quality when delivered or the node ability to deliver the information i.e. It mainly focuses on the data accuracy in the sensor networks. Furthermore, (Bao et al., 2012) implemented IDS using QoS trust and social trust which helps in forming the trust metric. However, the familiarity evaluation depends solely on occurrence of maximum interaction among these nodes. These phenomena can be easily mislead by the dishonest sensor devices, which is crossing the limit of normal interaction. Further, with growth of Internet, huge volume of data is being generated which lead to various security threats and issues. In general, it is likely adopting IDS will lead to higher number of packet being dropped considering heavy traffic load scenario. Then, it is even more complex considering such case in BigData environment. Thus, trust evaluation using standard packet status information are difficult. Therefore, there is need for effective trust computation model that brings good-tradeoffs to establish insider attack considering BigData environment.

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