Hyunwoo Lee (Seoul National University), Zach Smith (University of Luxembourg), Junghwan Lim (Seoul National University), Gyeongjae Choi (Seoul National University), Selin Chun (Seoul National University), Taejoong Chung (Rochester Institute of Technology), Ted "Taekyoung" Kwon (Seoul National University)

Middleboxes (MBs) are widely deployed in order to enhance security and performance in networking.
However, as the communications over the TLS become increasingly common, the end-to-end channel model of the TLS undermines the efficacy of MBs.
Existing solutions, such as `split TLS' that intercepts TLS sessions, often introduce significant security risks by installing a custom root certificate or sharing a private key.
Many studies have confirmed the vulnerabilities of combining the TLS with MBs, which include certificate validation failures, unwanted content modification, and using obsolete ciphersuites.
To address the above issues, we introduce an MB-aware TLS protocol, dubbed maTLS, that allows MBs to participate in the TLS in a visible and accountable fashion.
Every participating MB now splits a session into two segments with its own security parameters in collaboration with the two endpoints.
However, the session is still secure as the maTLS protocol is designed to achieve the authentication of MBs, the audit of MBs' operations, and the verification of security parameters of segments.
We carry out testbed-based experiments to show that maTLS achieves the above security goals with marginal overhead.
We also prove the security model of maTLS by using Tamarin, a security verification tool.

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] => 34 ) ) ) [post__not_in] => Array ( [0] => 4591 ) )

A Systematic Framework to Generate Invariants for Anomaly Detection...

Cheng Feng (Imperial College London & Siemens Corporate Technology), Venkata Reddy Palleti (Singapore University of Technology and Design), Aditya Mathur (Singapore University of Technology and Design), Deeph Chana (Imperial College London)

Read More

BadBluetooth: Breaking Android Security Mechanisms via Malicious Bluetooth Peripherals

Fenghao Xu (The Chinese University of Hong Kong), Wenrui Diao (Jinan University), Zhou Li (University of California, Irvine), Jiongyi Chen (The Chinese University of Hong Kong), Kehuan Zhang (The Chinese University of Hong Kong)

Read More

How Bad Can It Git? Characterizing Secret Leakage in...

Michael Meli (North Carolina State University), Matthew R. McNiece (Cisco Systems and North Carolina State University), Bradley Reaves (North Carolina State University)

Read More

One Engine To Serve 'em All: Inferring Taint Rules...

Zheng Leong Chua (National University of Singapore), Yanhao Wang (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences), Teodora Baluta (National University of Singapore), Prateek Saxena (National University of Singapore), Zhenkai Liang (National University of Singapore), Purui Su (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences)

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)