Menghao Zhang (Tsinghua University), Guanyu Li (Tsinghua University), Shicheng Wang (Tsinghua University), Chang Liu (Tsinghua University), Ang Chen (Rice University), Hongxin Hu (Clemson University), Guofei Gu (Texas A&M University), Qi Li (Tsinghua University), Mingwei Xu (Tsinghua University), Jianping Wu (Tsinghua University)

Distributed Denial-of-Service (DDoS) attacks have become a critical threat to the Internet. Due to the increasing number of vulnerable Internet of Things (IoT) devices, attackers can easily compromise a large set of nodes and launch highvolume DDoS attacks from the botnets. State-of-the-art DDoS defenses, however, have not caught up with the fast development of the attacks. Middlebox-based defenses can achieve high performance with specialized hardware; however, these defenses incur a high cost, and deploying new defenses typically requires a device upgrade. On the other hand, software-based defenses are highly flexible, but software-based packet processing leads to high performance overheads. In this paper, we propose Poseidon, a system that addresses these limitations in today’s DDoS defenses. It leverages emerging programmable switches, which can be reconfigured in the field without additional hardware upgrade. Users of Poseidon can specify their defense strategies in a modular fashion in the form of a set of defense primitives; this can be further customized easily for each network and extended to include new defenses. Poseidon then maps the defense primitives to run on programmable switches—and when necessary, on server software—for effective defense. When attacks change, Poseidon can reconfigure the underlying defense primitives to respond to the new attack patterns. Evaluations using our prototype demonstrate that Poseidon can effectively defend against highvolume attacks, easily support customization of defense strategies, and adapt to dynamic attacks with low overheads.

View More Papers

Withdrawing the BGP Re-Routing Curtain: Understanding the Security Impact...

Jared M. Smith (University of Tennessee, Knoxville), Kyle Birkeland (University of Tennessee, Knoxville), Tyler McDaniel (University of Tennessee, Knoxville), Max Schuchard (University of Tennessee, Knoxville)

Read More

MassBrowser: Unblocking the Censored Web for the Masses, by...

Milad Nasr (University of Massachusetts Amherst), Hadi Zolfaghari (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst), Amirhossein Ghafari (University of Massachusetts Amherst)

Read More

Measuring the Deployment of Network Censorship Filters at Global...

Ram Sundara Raman (University of Michigan), Adrian Stoll (University of Michigan), Jakub Dalek (Citizen Lab, University of Toronto), Reethika Ramesh (University of Michigan), Will Scott (Independent), Roya Ensafi (University of Michigan)

Read More

OcuLock: Exploring Human Visual System for Authentication in Virtual...

Shiqing Luo (Georgia State University), Anh Nguyen (Georgia State University), Chen Song (San Diego State University), Feng Lin (Zhejiang University), Wenyao Xu (SUNY Buffalo), Zhisheng Yan (Georgia State University)

Read More