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In this paper, a novel jammer detection framework to detect the intrusion of jammer and the presence of jamming in a cluster-based wireless sensor network is proposed.
In this paper, a novel jammer detection framework (which detects the intrusion of jammer and various types of jamming attacks) is proposed and evaluated.
A novel jammer detection framework is proposed to detect the presence of jammer and jamming in the cluster-based wireless sensor networks.
The novel jammer detection framework is proposed to detect the intrusion of jammer and the presence of jamming in the cluster-based wireless sensor network.
Based on this ground truth, Cao and Kot [23] proposed an ensemble manipulation detection framework (i.e., FusionBoost) to detect a range of manipulations on local image patches.
Jammer detection framework (Section 3): The jammer detection framework (JDF) detects the intrusion of the jammer and various types of jamming attacks.
Second, Farooqi et al. [13] proposed the novel intrusion detection framework, which applied to the distributed environment for detecting intrusion.
Table 1 Types of jamming Types of jammer Average PDR (in %) PDR range (in %) RSSI (in db) Constant 9.76 0–10 −93.141 Deceptive 28.81 25.6 53.5 −93.141 Random 57.9 53.6–73.75 −93.141 Reactive 22.21 11 25.5 −93.141 Jammer detection framework (Section 3): The jammer detection framework (JDF) detects the intrusion of the jammer and various types of jamming attacks.
Fig. 2 Jammer detection framework.
Fig. 2 The proposed nuclear detection framework.
The proposed work defines a contextual anomaly detection framework.
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