# 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
### Data Link Layer
In [42], [PERSON] et al. proposed a novel countermeasure named abnormal sensor detection accuracy (ASDA)-RSA to reduce the amount of consumed energy by introducing clustering and authentication through the RSA cryptography algorithm and interlock protocol. Each node measured the energy and distance of each node from the cluster to determine the cluster header. Each cluster member was authenticated by a cluster header. If a node was verified as valid, then RSA key generation and key distribution by interlock protocol were accomplished. [PERSON] [43] specified a novel algorithm to detect malicious attacks for the wake-up radio protocol (WUR). If an attack was detected by the anti-malicious attack WUR (AMA-WUR), then further operation procedures responded to malicious attacks and notified other nodes for them. To detect malicious attacks, the load capacity of the network in the normal state was set. If the measured value was greater than one in normal value, then it was considered an attack. For example, the average utilization rate and instantaneous utilization rate can be used for comparative parameters. The author obtained two main characteristics for attacks. One characteristic was for the destination address such that numerous packets can be directed to a specific target device, whereas the other was for network traffic to be focused on a certain host. Another paper [44] mentioning WUR was presented by [PERSON] and [PERSON]. They combined and distributed the cooperation model and dynamic elliptic curves-RSA (DECRSA) by selecting a novel supervisor node with traffic parameters. [PERSON] and [PERSON] [45] introduced firefly and Hopfield neural network (HNN) algorithm RSA optimization against denial-of-sleepattacks. In this study, the firefly algorithm was used for clustering, and the RSA algorithm and interlock protocol were used for authentication. Furthermore, to track sink movement, HNN detected the sink movement to send data of the cluster header. The proposed scheme prevents the denial-of-sleep attack by validating all nodes that transmit synchronization messages. If validation fails, the message is rejected. Battery-draining attacks in Wi-Fi-enabled sensor networks were addressed and studied in [46]. Wi-Fi-enabled sensor networks are easily attacked by triggering frames. Because of this fake frame, a node cannot turn into a sleep mode, which results in continuously replying to a signal and consuming a large amount of energy. To prevent this problem, the authors proposed a novel scheme named the secure triggering frame-based dynamic power-saving mechanism (STF-DPSM) for multi-link environments to simultaneously transmit and receive across multiple links. However, this approach is typically more susceptible to battery-draining attacks than the conventional single-link case. Battery-draining attacks can be incorporated into a masquerading attack by forcing a legitimate access point to deceive wireless terminals. If an access point sends a forged trigger frame continuously, then a station cannot go to the sleep mode because it should send back the replay packet accordingly and persistently. Because previous approaches based on encryption/decryption schemes for denial of sleep can cause overheads in normal scenarios without attacks, a novel scheme with a low overhead is desirable. The proposed scheme adjusts the power-saving time appropriately and applies STF. When an AP detects a denial-of-sleep attack and the situation goes further, the target window time period for the victim device decreases. Throughout this procedure, the STF algorithm is implemented to verify the integrity of the trigger frames. For energy drain attacks, in [47], the authors focus on wireless body area networks, specifically, the network of WSNs that forms around the human body. The proposed framework increases energy utilization, detecting repetitive events, and controlling transmissions to finally increase network lifetime. To achieve them, a backoff factor based on the amount of current residual energy was selected.