## 2 Related Work  
[PERSON] _et al._[7] study mobile _ad hoc_ networks (MANETs); in particular, link quality due to jamming, interference, coverage range or other generic characteristics of the communication medium in an airborne environment. They analyze the connectivity and performance of known protocols using metrics, such as the packet delivery ratio (PDR), end-to-end delay and other overhead metrics. [PERSON] _et al._[8] provide optimal detection tests that show what knowledge of a network an attacker node may acquire. The authors analyze the difficulty of detecting an attacker and the collective impact of defending a network. The authors take into account the probability of jamming and the transmission range. The work of [PERSON] _et al._[9], by contrast, studies a metric for measuring the degree of jamming affecting each node, providing the jammer's localization centrally. Furthermore, the authors complement the method with a decentralized setting, where each node measures the perceived jammer power in order to observe the degree of damage based on coordinates. According to the parts of the network affected by the jamming, a zoning map of the jammed area is created, as well as measures for decreasing node energy consumption are established. Likewise, the work cited in [10] studied a local perspective for detecting jamming. The metric used is throughput. The authors make a comparison between normal levels of throughput and interference levels of throughput (or abnormal). The authors establish two categories of jamming: signal strength-based and protocol behavior-based. Moreover, they try to detect the jamming affected zone (through PDR and throughput) and locate unaffected nodes to isolate them from the attack. This technique favors network performance and the study of the self-configuration feature the of routing protocol. [PERSON] _et al._[PERSON] _et al._ (2015) examine jamming attacks and the corresponding defense strategies. They also analyze different methods for detecting the presence of a jammer node. The authors characterize and then analyze different types of jamming presented in a wireless medium, namely: constant, deceptive, random (which, as shall be discussed below, is a little different from our definition of random jamming) and reactive. To detect the presence of jamming in either the transmitter or receiver, the authors suggest using a number of measures, particularly signal strength, carrier sensing time, the packet send ratio (PSR) and the packet delivery ratio (PDR). Wireless mesh networks are studied by [PERSON] and [PERSON] [PERSON] and [PERSON] (2014). There, the authors analyze the benefits of dynamic channel assignment, alternating routes and channels and effective routing when a network defends against a jamming attack. They also study the effect of restoration and how it affects the latency and throughput of the network. By way of comparison, in [PERSON] and [PERSON] (2015), [PERSON] _et al._ propose a MAC protocol capable of defending a network against a jamming attack at the physical layer. There, a model that takes into account the difference between a jamming attack or a collision is proposed, and the energy efficiency of the protocol on different attacks is shown. By contrast, in [PERSON] and [PERSON] (2016), the authors analyze how powerful an attacker can become with respect to energy consumption, transmission range and coverage. They point out that the objectives of a jammer node include obstructing internode communication (especially with the collector node) and increase the energy consumption of the network node. One of the biggest challenges an attacker must face is to know the MAC protocol that the nodes run, so as to determine how one should attempt to disrupt communication. The aforementioned works consider a number of input variables for the jamming detection mechanisms; _i.e._, packet delivery ratio, signal strength, carrier sense metrics, _etc_.