2020
DOI: 10.1016/j.jisa.2020.102457
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T-CAD: A threshold based collaborative DDoS attack detection in multiple autonomous systems

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Cited by 20 publications
(13 citation statements)
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“…In this section, the results of the proposed method for the proposed dataset are mentioned. After multiple performances for different time periods, with different values of the parameter α for different ∅-entropies in the range (2)(3)(4)(5)(6)(7)(8)(9)(10) and considering the values of r to calculate different thresholds for each α, in the range of (-5-5), using the floodlight controller module, different results were obtained; in Tables 2 and 3, the best values obtained in terms of detection accuracy, are listed for different time periods and are obtained separately for each dataset.…”
Section: Results Of the Experimentsmentioning
confidence: 99%
See 2 more Smart Citations
“…In this section, the results of the proposed method for the proposed dataset are mentioned. After multiple performances for different time periods, with different values of the parameter α for different ∅-entropies in the range (2)(3)(4)(5)(6)(7)(8)(9)(10) and considering the values of r to calculate different thresholds for each α, in the range of (-5-5), using the floodlight controller module, different results were obtained; in Tables 2 and 3, the best values obtained in terms of detection accuracy, are listed for different time periods and are obtained separately for each dataset.…”
Section: Results Of the Experimentsmentioning
confidence: 99%
“…In paper [8] , a system called T-CAD is proposed to detect and reduce threshold-based DDoS attacks. This method calculates the entropy of router flows.…”
Section: Related Workmentioning
confidence: 99%
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“…Serangan Distributed Denial of Services (DDoS) terus menjadi salah satu ancaman paling menantang ke Internet. Intensitas dan frekuensi serangan ini meningkat dengan kecepatan yang mengkhawatirkan [5] Begitu seringnya serangan DoS terjadi menyebabkan banyak peneliti yang melakukan penelitian tentang serangan DoS di antaranya yaitu serangan pada sistem fisik [9], survey dan mitigasi serangan DoS pada Named Data Networking [10], eksplorasi bukti digital pada smart router [11], mitigasi serangan DoS yang efisien [12], deteksi DoS pada penerapan jaringan sensor nirkabel [13], deteksi serangan DDoS berbasis multiple autonomous systems [14], dan DDoS bandwidth flooding [15].…”
Section: Pendahuluanunclassified
“…The primary target of DDoS attack is availability of resources for genuine users. The malicious flooding overloads the network, exceeding its bandwidth capabilities and disrupting the services [4]. The target range varies from financial institutions, health care providers and government agencies to low key public networks [2].…”
Section: Introductionmentioning
confidence: 99%