# New Detection Paradigms to Improve Wireless Sensor Network Performance under Jamming Attacks
## 2 Related Work on the Jamming Detection Problem  
Sensor networks are typically deployed in unattended and wild environments, with a shared, unprotected, wireless communication channel. Besides, the reduced computing capacity of a nodes, its strict energy management, and the complexity of the network, might result in a particularly highly vulnerable system. In addition, attackers usually have direct physical access to the hardware of each node, which provides them with many possible ways to attack either physical devices or the network. For this reason, it is necessary to introduce safety requirements in the specification of sensor networks, while improving the mechanisms used to prevent attacks. Jamming is considered one of the most harmful attacks in threats to WSNs. A jamming attack can limit the communication capabilities of a WSN by degrading the system performance interfering with signals using certain interfering devices [18]. For instance, the proposal in [19] is based on a jamming detection algorithm that employs honeynodes and response mechanism concepts. Each node cooperates with the transmitter to detect any jamming. The authors analyze network performance metrics such as: duration of jamming attack, control message overhead, and the number of channel re-configurations, as well as one of the metrics they use in their simulations is the Packet Delivery Ratio (PDR). To disable a node or set of nodes in a WSN, the jammer node transmits a radio-frequency signal that interferes with the legitimate signals used by the other sensor nodes. [PERSON] et al., in [20], mention the importance of the transmission state in the links under jamming and how it influences the routing protocol. In [21], [PERSON] et al. analyze the system performance from the network layer through routing. The authors analyze a constant jamming, while in our work we study a reactive jamming that represents the worst-case scenario and the most aggressive attack. In [22], [PERSON] et al. study on-demand routing protocols and the presence of one or more jammers and develop a multi-path selection algorithm. The authors test their algorithm with a modified version of the AODV protocol. In the work of [PERSON] et al. [23], they discuss address the problem of routing link selection based on the jamming parameters that is measured on a low energy consumption algorithm. Nevertheless, they do not isolate nodes under attack and, when jamming conditions change, the selected route could be inside of the affected zone. The difference of such work with respect to ours is that they find the best route to a destination, while we isolate the affected area so that the protocol re-configures the valid routes and the information arrives reliably. In [24], [PERSON] et al. study problems related to energy depletion in hierarchical WSNs models. The authors propose an energy-saving oriented model in which a relay node is used to regulate packet traffic and energy consumption in intermediate nodes. Data gathering, another issue presented in hierarchical networks, is analyzed in [25] under a predefined transmission path scenario. Since a predefined transmission path favors the creation of clusters, a dynamic routing approach is proposed in [26] to balance the traffic in the network and decrease the energy consumption in the nodes. A new performance metric, called energy consumption density, is established to validate the effectiveness of their approach. Against that background, the proposed jamming detection technique is implemented in a hierarchical model of WSNs, which facilitates packet sending and decreases network overhead. Besides, most of the studies use energy-related metrics to analyze the performance of long-lasting and difficult access networks such as WSNs. In contrast, we also introduce five performance metrics to enhance the accuracy in the detection of a possible attacker. The additional metrics proposed in this work are (i) retransmissions, (ii) Carrier Sense Multiple Access (CSMA) retries, (iii) resilience, (iv) delay and (v) valid routes.