Defending Web Servers Against Flash Crowd Attacks. Tandon, R., Palia, A., Ramani, J., Paulsen, B., Bartlett, G., & Mirkovic, J. In Sako, K. & Tippenhauer, N. O., editors, Applied Cryptography and Network Security, pages 338–361, Cham, 2021. Springer International Publishing.
abstract   bibtex   
A flash crowd attack (FCA) floods a service, such as a Web server, with well-formed requests, generated by numerous bots. FCA traffic is difficult to filter, since individual attack and legitimate service requests look identical. We propose robust and reliable models of human interaction with server, which can identify and block a wide variety of bots. We implement the models in a system called FRADE, and evaluate them on three Web servers with different server applications and content. Our results show that FRADE detects both naive and sophisticated bots within seconds, and successfully filters out attack traffic. FRADE significantly raises the bar for a successful attack, by forcing attackers to deploy at least three orders of magnitude larger botnets than today.
@InProceedings{10.1007/978-3-030-78375-4_14,
author="Tandon, Rajat
and Palia, Abhinav
and Ramani, Jaydeep
and Paulsen, Brandon
and Bartlett, Genevieve
and Mirkovic, Jelena",
editor="Sako, Kazue
and Tippenhauer, Nils Ole",
title="Defending Web Servers Against Flash Crowd Attacks",
booktitle="Applied Cryptography and Network Security",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="338--361",
abstract="A flash crowd attack (FCA) floods a service, such as a Web server, with well-formed requests, generated by numerous bots. FCA traffic is difficult to filter, since individual attack and legitimate service requests look identical. We propose robust and reliable models of human interaction with server, which can identify and block a wide variety of bots. We implement the models in a system called FRADE, and evaluate them on three Web servers with different server applications and content. Our results show that FRADE detects both naive and sophisticated bots within seconds, and successfully filters out attack traffic. FRADE significantly raises the bar for a successful attack, by forcing attackers to deploy at least three orders of magnitude larger botnets than today.",
isbn="978-3-030-78375-4"
}

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