# New Detection Paradigms to Improve Wireless Sensor Network Performance under Jamming Attacks
## 1 Introduction  
Wireless Sensor Networks (WSNs) are made up of hundreds, or even thousands, of sensor nodes with limited communication and calculation capabilities that can cooperate to perform complex tasks such as monitoring or control [1; 2; 3]. Due to their distributed nature and open access to the wireless medium, WSNs may encounter intermittent communication issues and are extremely vulnerable to different kinds of attacks and security threats [4]. For instance, these networks may be subject to jamming attacks, which deactivate or saturate the resources of the system. This type of attack aims to reduce the network capabilities for transporting information. For achieving such goal, the jammer node generates an interference. If the jammer succeeds then the MAC layer of the wireless devices under the attack may produce packet retransmissions, increasing the network traffic. In particular, in the event of jamming, the network performance decreases noticeably [5]. A key element of counteracting a jammer node is its detection and localization, being the centralization of the attacker a fundamental step [6]. The optimization of security infrastructures in terms of resources (energy, computing time, overhead and others), provides a useful perspective when facing an attack, minimizing its influence on network performance. A jamming attack is intended to generate interference and it may be difficult to be detected because other types of communication interference can also occur. The jamming detection problem, therefore, consists of segregating the behavior from the wireless environment from the network topology. An abrupt network performance decrease, alongside with constant topology reconfiguration, often indicates a possible attack. Currently, jamming detection techniques [7] are mainly based on basic signal-to-noise ratio deterioration measurements [8], Received Signal Strength Indicator (RSSI), or other metrics such as packet loss or packet delivery ratio [9]. In WSNs, jamming detection techniques must be adapted to the particular nature of these networks and their routing protocols [10]. Among them, reactive routing protocols [11] are broadly adopted in WSNs due to their small packet overhead on the network and the fact that new nodes entries are created only when deemed necessary, which reduces the required number of messages between neighbor nodes. Consequently, the source node requires to find a route before sending a message leading to processing time even before it starts. Ad hoc On-demand Distance Vector (AODV) [12] and Dynamic Source Routing (DSR) [13] are two well-known reactive protocols. AODV uses the routing tables of the nodes to find the route towards to a given destination. The new routes are found by a reactivity mechanism, in which the needed route is asked to the neighboring nodes. In this way, the number of hops towards the requested path is found. Before the process of discovery of any route starts, this table is conformed by neighbor nodes and new destinations are only introduced when a node needs to communicate with another node and the table does not contain a route. Thus, a process to discover the possible routes to the destination is launched. In this process, each node uses a counter or sequence number (i.e., an integer value) that is incremented each time before generating a control message. On the other hand, the DSR protocol follows an origin routing scheme which determines the route of each packet just before sending it. Besides, in this algorithm, the sent packets between nodes must include a header that determines the identifiers of the nodes visited along the path. Fortunately, DSR does not require persistent control messages, which reduce the overhead on the network. Moreover, we introduce a hybrid protocol (between proactive and reactive nature), named MPH (Multi-Parent Hierarchical). The MPH protocol, proposed in [14], creates a hierarchical network logical topology where the hierarchy of the nodes is given by their location level.