# New Detection Paradigms to Improve Wireless Sensor Network Performance under Jamming Attacks
## 1 Introduction
It works like a hierarchical tree: nodes establish parent and child links that constitute the possible routes. Node hierarchies are used to establish links among parents and children based on the coverage radius that depends on the transmission power. As a result, a node can share both the children and the parents with another node belonging to the same hierarchical level. MPH takes advantage of the proactive route maintenance, allowing more than one route per node, which makes it versatile and adaptable to different topologies. In this work, two new collaborative mechanisms for jamming detection, based on cooperation by receiving feedback from other network nodes, are proposed. The two proposed techniques are improved versions of the method published in [15] with a free training characteristic, i.e., both techniques do not require a previous learning step. These techniques are named (i) Connected Mechanism and (ii) Extended Mechanism. The first one is based on the comparison of performance parameters with respect to directly connected neighbors by interchanging packets with performance metric information, whereas the latter relays The second one is based on the comparison of the parameters known by a collector node, that establishes differences between them and detect a possible affected zone. A notorious advantage of the these two detection techniques proposed in this work concerning the training technique from [15] is that the implementation is faster because there is no previous learning stage. Another advantage is that if the attacker is active during the learning stage,the reference values of this step will be erroneous parameters and the system will not be able to identify the presence of the jammer. Here, we restate the novel contribution that a sensor network can be defended more efficiently by taking advantage of the combined knowledge of the sensor nodes and the collector node. The two proposed jamming detection mechanisms work by identifying and tagging the nodes under attack to circumvent the affected zone. The detection mechanism is based on a novel persistence parameter that gives a value in the neighbor tables for each node. Besides, the mechanism can be applied in centralized (**Extended Mechanism**) or distributed (**Connected Mechanism**) mode. The performance of the proposed approaches is analyzed through computational simulation that analyze the effect of the proximity of the nodes and how a malicious node affects it, thus considering the possibility of false positives resulting from the possible confusion between an affected node and interference in a reactive jamming scenario. Reactive jamming identification is usually based on finding abnormal system behavior and, therefore, it requires the system to be analyzed in the absence of jamming. Also, the effectiveness of the proposed mechanism is contrasted with the mentioned two well-known reactive routing protocols, namely AODV [12] and DSR [16], and one proactive routing protocol, MPH [17]. Results reveal that the proposed technique can reduce the detection of the affected zone to a 15% of the total area identified using AODV and SDR protocols (i.e., reactive protocols), and up to 4% using the MPH protocol (i.e., a proactive protocol). Besides, the performance was assessed in terms of different metrics, namely (i) number of retransmissions and, (ii) retries to listening to the channel, (iii) the end-to-end delay, (iv) resilience, and (v) energy consumption during the attack, showing the effectiveness of the proposed approach. The rest of the paper is organized as follows: Section 2 introduces the related work on the jamming detection problem. Section 3 proposes the analysis of detection mechanism. Section 4 presents the results and describes the performance metrics and energy consumption under routing protocols and a jamming attack. Finally, conclusions are given in Section 5.