# A Survey on Energy Drainage Attacks and Countermeasures in Wireless Sensor Networks
## 4 Recent Review Based on State-of-the-Art Works for Energy Drain Attack
### Physical Layer  
Jamming and its variants attack and exploit the shared nature of the wireless medium as well as interrupt receiving by reducing the receiver's signal-to-noise ratio. Jamming attacks can rapidly lead to energy depletion in WSNs. Therefore, the implementation of countermeasures against jamming is crucial in WSNs. In this section, we review state-of-the-art measures to counter jamming attacks in the physical layer. [PERSON] et al. [25] investigated jamming attacks in WSNs in the aspects of technologies, impact, and available countermeasures. They analyzed current approaches and discussed unsolved research challenges and issues. To address jamming attacks on physical-layer authentication (PLA) [26], [PERSON] et al. suggested a jamming attack detection (JAD) and composite jamming attack detection (CJAD) scheme. JAD identifies the difference in noise variances between the handshaking and communication phases, whereas the CJAD exploits one variance between the source and destination. Moreover, a theoretical analysis of the proposed scheme for wireless fading channels was presented. Finally, real implementation for the proposed scheme rather than simulation was explained for conducting extensive performance comparisons. The proposed scheme can counter both jamming and spoofing attacks simultaneously. [PERSON] et al. [27] presented a new scheme to utilize the Stackelberg game theory to avoid jamming areas. A centralized unit identified the jamming area using the locations of the affected nodes and functions as the leader. Similar to the clustering scheme, it uses nodes around the leader function as followers and determines the mobility pattern  
Figure 5: Categorization of EDAs in [23]. to minimize unnecessary energy consumption. The proposed scheme, mobility-based jamming avoidance in WSNs (M-JAW), focused on the mobility model. Furthermore, a novel mobility model called the rational mobility model was proposed to remove the effects of jamming on affected nodes. Another research study using a novel location pinpointed anti-jammer with knowledge estimated localizer (KNOWEL) was proposed in [28]. In the proposed scheme, an energy detector sets the decision threshold, and an adaptive filter recognizes the signal variance between normal and reactive jammer traffic. Next, the jammer and its exact location with the profile of the external attacker were computed using the KNOWEL method. The KNOWL scheme consists of three major components, namely feature extraction, cluster partition, and locational process for the learning phase. The M-cluster algorithm, nonparametric CUSUM algorithm, and centroid location algorithm were used for each stage. Well-known node parameters such as the received signal strength indicator (RSSI), packet delivery ratio, and packet loss ratio were used to detect the percentage of jamming. [PERSON] et al. [29] proposed a jammer location-aware method based on a Fibonacci branch search. They extended the Fibonacci optimization method to multidimensional space search optimization problems. A novel jammer location based on FDB consists of three stages, namely selecting initial search points, the classification of the fitness function, and updating the search point iteratively. Thus, interactive global search and local optimization rules are applied alternately and iteratively to obtain the accurate location of the jammer. They demonstrated that the proposed scheme outperformed the existing scheme in many complex scenes with distinct parameter values. [PERSON] and [PERSON] [30] presented a new effective jamming localizing scheme to identify jammed regions through convex hulls using detected jammed nodes. They took several parameters, such as the jamming signal strength (JSS), the packet delivery ratio, and others, to detect jamming. In addition, a cluster-based multi-channel assignment technique was employed to avoid channels. Another work [31] for jamming countermeasures was related to channel avoidance for jamming in WirelessHART.