Cloud security defence to protect cloud computing against HTTP-DoS and XML-DoS attacks

By Ashley Chonka, Yang Xiang, Wanlei Zhou, Alessio Bonti. 2011

311 citations recorded by the source corpus.

How researchers see this paper

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Distributed learning of deep neural network over multiple agents (2018, neutral): “Widespread application of neural networks in sensitive areas such as ﬁnance and health, has created a need to develop methods for both distributed and secure training [18, 19, 20] and classi-ﬁcation in neural networks.”
Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework (2016, methodology): “While cloud computing provides various benefits to users, there are also underlying security and privacy risks [3-6, 82, 85].”
Low-Rate DDoS Attacks Detection and Traceback by Using New Information Metrics (2011, background): “Furthermore, the proposed IP traceback algorithm can find all attacks as well as attackers from their own local area networks (LANs) and discard attack traffic.”
Security issues in cloud environments: a survey (2014, background): “MitB attacks [33, 67,223] bandwidth under-provisioning, VPSes bots [54,57] direct and indirect DoS, race in power [126,129] UDP uplink flood attack [154] resource exhaustion attacks [125,127] XML flooding attacks [49] DNS reflection and amplification attack [218] In te rn et a n d S er v ic es”