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

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 39 ) ) ) [post__not_in] => Array ( [0] => 5879 ) )

FUSE: Finding File Upload Bugs via Penetration Testing

Taekjin Lee (KAIST, ETRI), Seongil Wi (KAIST), Suyoung Lee (KAIST), Sooel Son (KAIST)

Read More

Deceptive Previews: A Study of the Link Preview Trustworthiness...

Giada Stivala (CISPA Helmholtz Center for Information Security), Giancarlo Pellegrino (CISPA Helmholtz Center for Information Security)

Read More

ConTExT: A Generic Approach for Mitigating Spectre

Michael Schwarz (Graz University of Technology), Moritz Lipp (Graz University of Technology), Claudio Canella (Graz University of Technology), Robert Schilling (Graz University of Technology and Know-Center GmbH), Florian Kargl (Graz University of Technology), Daniel Gruss (Graz University of Technology)

Read More

Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning

Harsh Chaudhari (Indian Institute of Science, Bangalore), Rahul Rachuri (Aarhus University, Denmark), Ajith Suresh (Indian Institute of Science, Bangalore)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)