Daniel J. Bernstein (University of Illinois at Chicago and Academia Sinica), Tanja Lange (Eindhoven University of Technology amd Academia Sinica), Jonathan Levin (Academia Sinica and Eindhoven University of Technology), Bo-Yin Yang (Academia Sinica)

This paper introduces PQConnect, a post-quantum end-to-end tunneling protocol that automatically protects all packets between clients that have installed PQConnect and servers that have installed and configured PQConnect.

Like VPNs, PQConnect does not require any changes to higher-level protocols and application software. PQConnect adds cryptographic protection to unencrypted applications, works in concert with existing pre-quantum applications to add post-quantum protection, and adds a second application-independent layer of defense to any applications that have begun to incorporate application-specific post-quantum protection.

Unlike VPNs, PQConnect automatically creates end-to-end tunnels to any number of servers using automatic peer discovery, with no need for the client administrator to configure per-server information. Each server carries out a client-independent configuration step to publish an announcement that the server's name accepts PQConnect connections. Any PQConnect client connecting to that name efficiently finds this announcement, automatically establishes a post-quantum point-to-point IP tunnel to the server, and routes traffic for that name through that tunnel.

The foundation of security in PQConnect is the server's long-term public key used to encrypt and authenticate all PQConnect packets. PQConnect makes a conservative choice of post-quantum KEM for this public key. PQConnect also uses a smaller post-quantum KEM for forward secrecy, and elliptic curves to ensure pre-quantum security even in case of security failures in KEM design or KEM software. Security of the handshake component of PQConnect has been symbolically proven using Tamarin.

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] => 118 ) ) ) [post__not_in] => Array ( [0] => 20086 ) )

L-HAWK: A Controllable Physical Adversarial Patch Against a Long-Distance...

Taifeng Liu (Xidian University), Yang Liu (Xidian University), Zhuo Ma (Xidian University), Tong Yang (Peking University), Xinjing Liu (Xidian University), Teng Li (Xidian University), Jianfeng Ma (Xidian University)

Read More

A Method to Facilitate Membership Inference Attacks in Deep...

Zitao Chen (University of British Columbia), Karthik Pattabiraman (University of British Columbia)

Read More

Detecting Ransomware Despite I/O Overhead: A Practical Multi-Staged Approach

Christian van Sloun (RWTH Aachen University), Vincent Woeste (RWTH Aachen University), Konrad Wolsing (RWTH Aachen University & Fraunhofer FKIE), Jan Pennekamp (RWTH Aachen University), Klaus Wehrle (RWTH Aachen University)

Read More

Oreo: Protecting ASLR Against Microarchitectural Attacks

Shixin Song (Massachusetts Institute of Technology), Joseph Zhang (Massachusetts Institute of Technology), Mengjia Yan (Massachusetts Institute of Technology)

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)