Journal ArticleDOI
Detection and defense of application-layer DDoS attacks in backbone web traffic
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TLDR
This work distinguishes itself from previous methods by considering AL-DDoS attack detection in heavy backbone traffic and integrates the above detection principles into a modularized defense architecture, which consists of a head-end sensor, a detection module and a traffic filter.About:
This article is published in Future Generation Computer Systems.The article was published on 2014-09-01. It has received 107 citations till now. The article focuses on the topics: Robust random early detection & Web traffic.read more
Citations
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Proceedings Article
On Network-Aware Clustering of Web Clients
TL;DR: Clusters---a grouping of clients that are close together topologically and likely to be under common administrative control are introduced, using a ``network-aware" method, based on information available from BGP routing table snapshots.
Journal ArticleDOI
An Entropy-Based Network Anomaly Detection Method
TL;DR: The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network.
Journal ArticleDOI
Security and Privacy of Smart Cities: A Survey, Research Issues and Challenges
TL;DR: A comprehensive survey of security and privacy issues of smart cities is delineated, and a basis for categorizing the present and future developments within this area is presented, to highlight the security requirements for designing a secure smart city.
Journal ArticleDOI
SkyShield: A Sketch-Based Defense System Against Application Layer DDoS Attacks
TL;DR: An effective defense system, named SkyShield, is proposed, which leverages the sketch data structure to quickly detect and mitigate application layer DDoS attacks and utilizes the abnormal sketch to facilitate the identification of malicious hosts of an ongoing attack.
Journal ArticleDOI
DDoS Attacks at the Application Layer: Challenges and Research Perspectives for Safeguarding Web Applications
Amit Praseed,P. Santhi Thilagam +1 more
TL;DR: This paper attempts to explore the entire spectrum of application layer DDoS attacks using critical features that aid in understanding how these attacks can be executed to help researchers understand why a particular group of features are useful in detecting a particular class of attacks.
References
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Journal ArticleDOI
Self-similarity in World Wide Web traffic: evidence and possible causes
Mark Crovella,Azer Bestavros +1 more
TL;DR: It is shown that the self-similarity in WWW traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local-area network.
Journal ArticleDOI
Self-similarity in World Wide Web traffic: evidence and possible causes
Mark Crovella,Azer Bestavros +1 more
TL;DR: It is shown that the self-similarity in WWW traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network.
Journal ArticleDOI
Network Applications of Bloom Filters: A Survey
TL;DR: The aim of this paper is to survey the ways in which Bloom filters have been used and modified in a variety of network problems, with the aim of providing a unified mathematical and practical framework for understanding them and stimulating their use in future applications.
Book ChapterDOI
CAPTCHA: using hard AI problems for security
TL;DR: This work introduces captcha, an automated test that humans can pass, but current computer programs can't pass; any program that has high success over a captcha can be used to solve an unsolved Artificial Intelligence (AI) problem; and provides several novel constructions of captchas, which imply a win-win situation.
Proceedings ArticleDOI
A signal analysis of network traffic anomalies
TL;DR: This paper reports results of signal analysis of four classes of network traffic anomalies: outages, flash crowds, attacks and measurement failures, and shows that wavelet filters are quite effective at exposing the details of both ambient and anomalous traffic.