An Efficient Authentication Scheme Based on Deployment Knowledge Against Mobile Sink Replication Attack in UWSNs

Abstract

Unattended wireless sensor networks (UWSNs) are vulnerable to mobile sink (MS) replication attack. In this attack, using the compromised key information, an attacker can collect data from networks by impersonating sinks. To resist such an attack, some schemes have been proposed. To improve the resilience of MS replication attack of these schemes, we can integrate them with schemes based on deployment knowledge. However, there are the following defects: 1) the probability of mutual authentication between a MS and a sensor node is less than 1 and 2) during the authentication phase, the energy consumption of sensor nodes increases significantly as the deployment area expands. In this paper, we construct 3-D backward key chains based on deployment knowledge and propose a new authentication scheme based on these. As compared with these existing related schemes, the detailed theory analysis and simulation results indicate that the scheme can ensure that a MS can be authenticated by sensor nodes, and can improve the resilience of networks' MS replication attack with low energy consumption. Index Terms-3-D backward key chain based on deployment knowledge, authentication, mobile sink (MS) replication attack, unattended wireless sensor networks (UWSNs).

An AODV Based Multifactor Authentication Scheme for Wireless Sensor Network

“…Then, as the rapid development on technology in IR4.0 transition, the old technique in manufacturing industry is gradually moving into wireless sensor network (WSN) (Ahmad et al, 2019). WSN is a type of wireless network that is fast getting a lot of attention in scientific and industrial applications, and it is a network of decentralized autonomous standalone sensor devices (Zhou et al, 2019). For example, the sensor devices can be used to monitor physical or environmental factors such as temperature, pressure, humidity, and pollution levels while transmit the information to a base station (Durugkar & Poonia, 2017;Ezhilazhahi & Bhuvaneswari, 2017;Nooriman et al, 2018;Guanochanga et al, 2018;Gope et al, 2019;Ferentinos et al, 2017;Chen et al, 2019).…”