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Cited by 33 publications
(21 citation statements)
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“…Defending against DoS attack is of prime importance for industries, and internet service providers. To overcome this attack many techniques are proposed by various researchers [5,6,8,9,11]. In this paper, we propose a model for the detection of denial of service attack in wireless networks using dominance based rough set.…”
Section: B Comparison With Different Approachmentioning
confidence: 99%
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“…Defending against DoS attack is of prime importance for industries, and internet service providers. To overcome this attack many techniques are proposed by various researchers [5,6,8,9,11]. In this paper, we propose a model for the detection of denial of service attack in wireless networks using dominance based rough set.…”
Section: B Comparison With Different Approachmentioning
confidence: 99%
“…In this section, we compare results of proposed model with five different models such as resilient back propagation (RBP) [11], markov chain model (MCM) [6], radial basis function (RBF) [5], resistant architecture model (RAM) [8], and wavelet transform model (WTM) [9]. Unlike Table XV Figure 4.…”
Section: B Comparison With Different Approachmentioning
confidence: 99%
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“…With this method, rating series can be decomposed into a finite signal and regard the signal as the input of discrete wavelet transform [17], [27]. In our proposed approach, we decompose respectively each user profiles into novelty-based, popularity-based and rating deviation-based rating series as the input signals.…”
Section: A the Frameworkmentioning
confidence: 99%
“…Barford P. et al [84] 4 Local variance shift using wavelets >100 DoS Magnaghi A. et al [89] 4 Locality principle measure TCP-DoS Bartlett G. et al [85] 2 Iterated filtering Low-rate Carl G. et al [86] 3 Change points in the CUSUM DoS Hamdi M. et al [87] 5 Lipschitz singularities DoS Lu W. et al [88] 15 ARX model DoS Dainotti A. et al [91] CUSUM & Adaptive Threshold DoS Li L. et al [92] 5 Energy distribution variation DDoS flood Chen Y. et al [70] 5 Gaussian distribution, DFT RoQ P*: Number of Parameters…”
Section: Table 2 Comparison Of Spectral Anomaly Detection Techniquesmentioning
confidence: 99%