Defense techniques for low-rate DoS attacks against application servers

2010 ◽  
Vol 54 (15) ◽  
pp. 2711-2727 ◽  
Author(s):  
Gabriel Maciá-Fernández ◽  
Rafael A. Rodríguez-Gómez ◽  
Jesús E. Díaz-Verdejo
Keyword(s):  
Dos Attacks ◽  
Application Servers ◽  
Low Rate

Mathematical Model for Low-Rate DoS Attacks Against Application Servers

2009 ◽  
Vol 4 (3) ◽  
pp. 519-529 ◽  
Author(s):  
G. Macia-Fernandez ◽  
J.E. Diaz-Verdejo ◽  
P. Garcia-Teodoro
Keyword(s):  
Mathematical Model ◽  
Dos Attacks ◽  
Application Servers ◽  
Low Rate

The detection of low-rate DoS attacks using the SADBSCAN algorithm

2021 ◽  
Vol 565 ◽  
pp. 229-247
Author(s):  
Dan Tang ◽  
Siqi Zhang ◽  
Jingwen Chen ◽  
Xiyin Wang
Keyword(s):  
Dos Attacks ◽  
Low Rate

Assessment of a Vulnerability in Iterative Servers Enabling Low-Rate DoS Attacks

2006 ◽  
pp. 512-526 ◽  
Author(s):  
Gabriel Maciá-Fernández ◽  
Jesús E. Díaz-Verdejo ◽  
Pedro García-Teodoro
Keyword(s):  
Dos Attacks ◽  
Low Rate

scholarly journals Low-Rate DoS Attacks Detection Based on MAF-ADM

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 189 ◽  
Author(s):  
Sijia Zhan ◽  
Dan Tang ◽  
Jianping Man ◽  
Rui Dai ◽  
Xiyin Wang
Keyword(s):  
Joint Distribution ◽  
Transmission Control Protocol ◽  
Denial Of Service ◽  
False Negative ◽  
False Negative Rate ◽  
Network Simulator ◽  
Dos Attacks ◽  
Time Frequency ◽  
Anomaly Score ◽  
Low Rate

Low-rate denial of service (LDoS) attacks reduce the quality of network service by sending periodical packet bursts to the bottleneck routers. It is difficult to detect by counter-DoS mechanisms due to its stealthy and low average attack traffic behavior. In this paper, we propose an anomaly detection method based on adaptive fusion of multiple features (MAF-ADM) for LDoS attacks. This study is based on the fact that the time-frequency joint distribution of the legitimate transmission control protocol (TCP) traffic would be changed under LDoS attacks. Several statistical metrics of the time-frequency joint distribution are chosen to generate isolation trees, which can simultaneously reflect the anomalies in time domain and frequency domain. Then we calculate anomaly score by fusing the results of all isolation trees according to their ability to isolate samples containing LDoS attacks. Finally, the anomaly score is smoothed by weighted moving average algorithm to avoid errors caused by noise in the network. Experimental results of Network Simulator 2 (NS2), testbed, and public datasets (WIDE2018 and LBNL) demonstrate that this method does detect LDoS attacks effectively with lower false negative rate.

scholarly journals Low-Rate DoS Attacks, Detection, Defense, and Challenges: A Survey

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 43920-43943 ◽  
Author(s):  
Wu Zhijun ◽  
Li Wenjing ◽  
Liu Liang ◽  
Yue Meng
Keyword(s):  
Dos Attacks ◽  
Low Rate

Evaluation of a low-rate DoS attack against application servers

2008 ◽  
Vol 27 (7-8) ◽  
pp. 335-354 ◽  
Author(s):  
Gabriel Maciá-Fernández ◽  
Jesús E. Díaz-Verdejo ◽  
Pedro García-Teodoro
Keyword(s):  
Dos Attack ◽  
Application Servers ◽  
Low Rate

Modeling and Simulation of Low Rate of Denial of Service Attacks

2014 ◽  
Vol 484-485 ◽  
pp. 1063-1066
Author(s):  
Kui Liang Xia
Keyword(s):  
High Efficiency ◽  
Denial Of Service ◽  
Research Work ◽  
Attack Detection ◽  
Detection Methods ◽  
Dos Attacks ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
User Data ◽  
Low Rate

The low-rate denial of service attack is more applicable to the network in recent years as a means of attack, which is different from the traditional field type DoS attacks at the network end system or network using adaptive mechanisms exist loopholes flow through the low-rate periodic attacks on the implementation of high-efficiency attacked by an intruder and not be found, resulting in loss of user data or a computer deadlock. LDos attack since there has been extensive attention of researchers, the attack signature analysis and detection methods to prevent network security have become an important research topic. Some have been proposed for the current attacks were classified LDoS describe and model, and then in NS-2 platform for experimental verification, and then LDoS attack detection to prevent difficulties are discussed and summarized for the future such attacks detection method research work to provide a reference.

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