# A Statistical Approach to Detect Jamming Attacks in Wireless Sensor Networks
## 2 Related Work  
With the widespread deployment of WSNs, jamming attacks that send malicious radio signals to disrupt legitimate communication and consume resources, and its countermeasures have been studied in the literature. This is necessary as sensor nodes are vulnerable to this type of attack due to their architecture, hostile deployment and insecure routing protocols. [PERSON] et al. [15] propose a centralised approach, a fuzzy inference-based system, to detect jamming attacks in the base stations by using three inputs received from each sensor node in the network. These inputs are the total packets received during a specific period, the number of dropped packets during that period and the received signal strength (RSS). The base station computes the power received during the jamming attack to find any difference in value between the current RSS and the normal RSS. These values are used by the base station to compute the packet drop per terminal (PDPT) and signal-to-noise ratio (SNR) which is further used as inputs for the fuzzy inference system to obtain the jamming index. The jamming index varies from 0 to 100 and is used to determine the intensity of the jamming attack, which can range between a situation of 'no jamming' to absolute jamming'. [PERSON] et al. [16] in their work identified the cause of bit errors for individual packets by analysing the RSS during the reception of these bits to detect reactive jamming attacks in sensor networks. This detection technique was based on predetermined knowledge, limited node wiring and error correction codes. Experimental results on Chipcon radios show its efficiency in detecting complex reactive jamming attacks without introducing additional overhead. In an attempt to detect complex reactive jamming attacks, [PERSON] et al. [17] proposed a technique that estimates the probability of packet delivery during the synchronization stage of packet transmission. This technique ensures that jammers that target the physical layer of the WSN are detected by predicting the packet delivery probability using the chip error rate in the received preamble symbols. A distributed approach to detect multichannel jamming attacks in WSN has been proposed by [PERSON] and [PERSON] [18]. In their approach, a piecewise homogenous Markov chain consisting of a complex two-level switching multichannel jamming attack model was developed by using multiple measurement channels to detect random attacks. Each state space of the Markov chain corresponds to the possible jamming attack modes. At a high level, the variations in probability of transition probability can be categorized into two, namely; stochastic switching and deterministic average dwell time switching. [PERSON] and [PERSON] [19] in their work analysed a heterogenous WSN under jamming attack using a two-player non-cooperative game chance constrained problem. The utility function used here is based on both signal interference and noise ratio at the receiver and a second order cone programme has been used to solve the game problem. Numerical results obtained show that the communication distance between the network elements must be put into consideration during the design of a detection technique for jamming attack. [PERSON] and [PERSON] [20] propose a prototype node, Ares, which is a hybrid of frequency hopping spread spectrum (FHSS) and direct sequence spread spectrum (DSSS) to defend against jamming attacks in WSNs. In the proposed technique, the FHSS is used in the 5 GHz band with 51 frequency channels to generate a channel sequence using a key known only by the sensor nodes and the sink node. Each of these channel use DSSS modulation with 16-bits pseudo noise code which are derived from the same key used during FHSS channel generation. Simulation results show that Ares nodes can ensure satisfactory packet delivery rate with reduced energy requirements in a jammed WSN environment, as opposed to ordinary sensor network schemes.