Measurements and analysis of end-to-end Internet dynamics
Measurements and analysis of end-to-end Internet dynamics
Bro: a system for detecting network intruders in real-time
Computer Networks: The International Journal of Computer and Telecommunications Networking
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Denial of service protection the nozzle
ACSAC '00 Proceedings of the 16th Annual Computer Security Applications Conference
Preventing Internet denial-of-service with capabilities
ACM SIGCOMM Computer Communication Review
Honeycomb: creating intrusion detection signatures using honeypots
ACM SIGCOMM Computer Communication Review
Denial-of-Service Attack-Detection Techniques
IEEE Internet Computing
Editorial: Distributed denial-of-service and intrusion detection
Journal of Network and Computer Applications
Network intrusion detection in covariance feature space
Pattern Recognition
Detecting Denial-of-Service attacks using the wavelet transform
Computer Communications
DDoS attack detection method using cluster analysis
Expert Systems with Applications: An International Journal
A comprehensive taxonomy of DDOS attacks and defense mechanism applying in a smart classification
WSEAS Transactions on Computers
Protocol-based classification for intrusion detection
WSEAS Transactions on Computer Research
Probabilistic techniques for intrusion detection based on computer audit data
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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With the proliferation of Internet applications and network-centric services, network and system security issues are more important than before. In the past few years, cyber attacks, including distributed denial-of-service (DDoS) attacks, have a significant increase on the Internet, resulting in degraded confidence and trusts in the use of Internet. However, the present DDoS attack detection techniques face a problem that they cannot distinguish flooding attacks from abrupt changes of legitimate activity. In this paper, we give a model for detecting DDoS attacks based on network traffic feature to solve the problem above. In order to apply the model conveniently, we design its implementation algorithm. By using actual data to evaluate the algorithm, the evaluation result shows that it can identify DDoS attacks.