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

Finding Safety in Numbers with Secure Allegation Escrows

Venkat Arun (Massachusetts Institute of Technology), Aniket Kate (Purdue University), Deepak Garg (Max Planck Institute for Software Systems), Peter Druschel (Max Planck Institute for Software Systems), Bobby Bhattacharjee (University of Maryland)

Read More

DESENSITIZATION: Privacy-Aware and Attack-Preserving Crash Report

Ren Ding (Georgia Institute of Technology), Hong Hu (Georgia Institute of Technology), Wen Xu (Georgia Institute of Technology), Taesoo Kim (Georgia Institute of Technology)

Read More

Data-Driven Debugging for Functional Side Channels

Saeid Tizpaz-Niari (University of Colorado Boulder), Pavol Černý (TU Wien), Ashutosh Trivedi (University of Colorado Boulder)

Read More