Proceedings ArticleDOI
A Recurrence Quantification Analytical Approach to Detect DDoS Attacks
N. Jeyanthi,J. Vinithra,Sneha,R. Thandeeswaran,N. Ch. S. N. Iyengar +4 more
- pp 58-62
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TLDR
A mathematical model called Recurrence Quantification Analysis (RQA) is proposed for detecting the DDoS attacks by computing entropy and determinism of selected packet attributes and to detect the anomalies and check the performance.Abstract:
Distributed Denial of Service (DDoS) is a type of attack in the application layer initiated from the various hosts to a single web server. The aim of this attack is to consume all the resources of the targeted system by exploiting the vulnerability. We proposed a mathematical model called Recurrence Quantification Analysis (RQA) for detecting the DDoS attacks by computing entropy and determinism of selected packet attributes. To detect the anomalies and check the performance we considered the live traffic traces from the network and various RQA parameters like entropy, laminarity and determinism were used to determine the uncertainty or randomness in the dataset.read more
Citations
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Journal ArticleDOI
Network Attacks and Their Detection Mechanisms: A Review
TL;DR: Different type of possible network attacks and detection mechanisms proposed by various researchers that are capable of detecting such attacks are reviewed.
Journal ArticleDOI
Rqa based approach to detect and prevent ddos attacks in voip networks
TL;DR: A Recurrence Quantification based approach to detect and prevent VoIP from a DDoS attack, which detects the attack at an earlier stage and also helps to prevent from further attacks.
Journal ArticleDOI
A survey on DoS/DDoS attacks mathematical modelling for traditional, SDN and virtual networks
Juan Fernando Balarezo,Song Wang,Karina Gomez Chavez,Akram Al-Hourani,Sithamparanathan Kandeepan +4 more
TL;DR: In this article, the authors present a classification approach for existing DoS/DDoS models in different kinds of networks; traditional networks, Software Defined Networks (SDN) and virtual networks.
Combining Recurrence Quantification Analysis and Adaptive Clustering to Detect DDoS Attacks.
TL;DR: This work proposes a new method, called DDoS by RQA, which uses the Recurrence Quantification Analysis (RQA) based on the extraction of network traffic dynamic features and the combination with an Adaptive Clustering Algorithm (A-Kmeans) to detect DDoS attacks.
Journal ArticleDOI
Credit Based Methodology to Detect and Discriminate DDOS Attack From Flash Crowd in A Cloud Computing Environment
TL;DR: A new reputation-based framework for mitigating the DDoS in cloud by classifying the users into three categories as well- reputed, reputed and ill-reputed based on credits is proposed, expected to take the edge off DDoS off in a cloud environment and ensures full security to cloud resources.
References
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Proceedings ArticleDOI
A Novel Model for Detecting Application Layer DDoS Attacks
Yi Xie,Shun-Zheng Yu +1 more
TL;DR: This paper considers sophisticated attacks that utilize legitimate application layer HTTP requests from legitimately connected network machines to overwhelm Web server and proposes a counter-mechanism based on Web user browsing behavior to protect the servers from these attacks.
Proceedings ArticleDOI
Distinguishing DDoS Attacks from Flash Crowds Using Probability Metrics
TL;DR: A set of novel methods using probability metrics to distinguish DDoS attacks from Flash crowds effectively are proposed, and simulations show that the proposed methods work well and can greatly reduce both false positive and false negative rates in detection.
Journal Article
Denial of Service Attack Techniques: Analysis, Implementation and Comparison
TL;DR: The potential damage from DOS attacks is demonstrated by simulating a distribution zombie program that will carry the Ping of Death attack and the ramifications of the damage are analyzed.
Proceedings ArticleDOI
Flash Crowd Detection Using Decoy Hyperlinks
TL;DR: A novel method for detecting denial of service attacks on web services are presented and evaluated by using decoy hyperlinks embedded in web pages, which are hyperlinks without semantic information or are invisible to the human user, acting like traps for DoS attacks.
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