Jonghoon Kwon (ETH), Taeho Lee (ETH), Claude Hähni (ETH), Adrian Perrig (ETH)

Network isolation is a critical modern Internet service. To date, network operators have created a logical network of distributed systems to provide communication isolation between different parties. However, the current network isolation is limited in scalability and flexibility. It limits the number of virtual networks and it only supports isolation at host (or virtual-machine) granularity. In this paper, we introduce Scalable Virtual Local Area Networking (SVLAN) that scales to a large number of distributed systems and offers improved flexibility in providing secure network isolation. With the notion of destination-driven reachability and packet-carrying forwarding state, SVLAN not only offers communication isolation but isolation can be specified at different granularities, e.g., per-application or per-process. Our proof-of-concept SVLAN implementation demonstrates its feasibility and practicality for real-world applications.

View More Papers

Decentralized Control: A Case Study of Russia

Reethika Ramesh (University of Michigan), Ram Sundara Raman (University of Michgan), Matthew Bernhard (University of Michigan), Victor Ongkowijaya (University of Michigan), Leonid Evdokimov (Independent), Anne Edmundson (Independent), Steven Sprecher (University of Michigan), Muhammad Ikram (Macquarie University), Roya Ensafi (University of Michigan)

Read More

Custos: Practical Tamper-Evident Auditing of Operating Systems Using Trusted...

Riccardo Paccagnella (University of Illinois at Urbana–Champaign), Pubali Datta (University of Illinois at Urbana–Champaign), Wajih Ul Hassan (University of Illinois at Urbana–Champaign), Adam Bates (University of Illinois at Urbana–Champaign), Christopher W. Fletcher (University of Illinois at Urbana–Champaign), Andrew Miller (University of Illinois at Urbana–Champaign), Dave Tian (Purdue University)

Read More

When Malware is Packin' Heat; Limits of Machine Learning...

Hojjat Aghakhani (University of California, Santa Barbara), Fabio Gritti (University of California, Santa Barbara), Francesco Mecca (Università degli Studi di Torino), Martina Lindorfer (TU Wien), Stefano Ortolani (Lastline Inc.), Davide Balzarotti (Eurecom), Giovanni Vigna (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara)

Read More

CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples

Honggang Yu (University of Florida), Kaichen Yang (University of Florida), Teng Zhang (University of Central Florida), Yun-Yun Tsai (National Tsing Hua University), Tsung-Yi Ho (National Tsing Hua University), Yier Jin (University of Florida)

Read More