# A Statistical Approach to Detect Jamming Attacks in Wireless Sensor Networks
## 3 Jamming Attack Models in WSN  
Jamming can be described as any disruption or interference with the physical transmission and reception of wireless signals. This can either be intentional, in the form of radio frequency interference,unintentional in cases of collision and noise interference at the receiver, or in the context of an attack [5]. During a jamming attack, the jammers aim is to disrupt communication between the transmitter and receiver using minimal power. This attack is catastrophic as the jammer exploits the open and shared nature of the wireless medium to disrupt communications by reducing the signal to noise ratio (SNR). An attacker with enormous resources can continually jam the spectrum band to disrupt communication in the band. Additionally, an attacker can decide to jam the band intermittently, thereby forcing the receiving node to drop packets due to alteration [25]. The jamming device often used to perpetrate this attack selects a common channel that is currently been occupied by the nodes to block data from being successfully transmitted. The main aim of the jamming device is to occupy the channel and ensure that network is not available for legitimate nodes, while these nodes, on the other hand, attempts to maximize the use of the network. One of the key components in determining a successful jamming attack is the SNR, defined as \(P_{signal}/P_{noise}\), where \(P\) is the average power. The noise here can be described as an undesirable fluctuation of the electromagnetic spectrum from the antenna. A jamming attack is deemed successful if the SNR < 1. Two types of jamming attack have been described in [26], namely physical and virtual jamming. Practical examples of physical jamming attacks are radio jamming and collision attacks while virtual jamming attack consists of network allocation vector attacks and Request-To-Send/Clear-To-Send attack. [PERSON] et al. [27] in their work analysed the effects of jamming attacks on underwater sensor networks, while a further study into the effect of controllable jamming attacks on WSNs was presented in [5]. Mobile jamming attacks that can dynamically jam the critical path of WSNs have also been discussed in [28] while an energy efficient periodic jamming that attacks when the nodes are in listening state and sleeps at other times has been described in [15]. From the literature, four common jamming strategies have been identified, namely: constant jammer, deceptive jammer, reactive and random jammer [29; 30]. Here, we briefly discuss each of these strategies:  
_Constant jammer_: In a constant jammer attack, the jamming devices do not follow the laid down protocol before continually transmitting series of radio signals, electromagnetic waves or radio sequence of bits to interfere with legitimate transmitted signals in the network. The consequence of continually transmitting these malicious signals is that these random bits occupy the transmission channel of the network to starve transmissions initiated by legitimate nodes. Furthermore, constant jammer attacks can cause interference at the transmitting nodes to corrupt the signals received by the receiving nodes. One of the main disadvantages of constant jammer attack is the enormous energy consumption which drains the battery life of the node due to the continuous emission of signals. Constant jammers, therefore require a high amount of power to carry out this attack. _Deceptive jammer_: Just as in the case of the constant jamming attack, a deceptive jammer continuously injects regular radio sequence of bits into the communication channel without gaps in between. However, different from a continuous jammer, it does not emit random bits but legitimate bit sequences. This often leads the network to believe that a normal transmission is taking place by legitimate nodes, thereby causing the legitimate nodes to wait indiscriminately in the listening state.