Yarin Perry (The Hebrew University of Jerusalem), Neta Rozen-Schiff (The Hebrew University of Jerusalem), Michael Schapira (The Hebrew University of Jerusalem)

The Network Time Protocol (NTP) synchronizes time across computer systems over the Internet and plays a crucial role in guaranteeing the correctness and security of many Internet applications. Unfortunately, NTP is vulnerable to so called time shifting attacks. This has motivated proposals and standardization efforts for authenticating NTP communications and for securing NTP textit{clients}. We observe, however, that, even with such solutions in place, NTP remains highly exposed to attacks by malicious textit{timeservers}. We explore the implications for time computation of two attack strategies: (1) compromising textit{existing} NTP timeservers, and (2) injecting textit{new} timeservers into the NTP timeserver pool. We first show that by gaining control over fairly few existing timeservers, an textit{opportunistic} attacker can shift time at state-level or even continent-level scale. We then demonstrate that injecting new timeservers with disproportionate influence into the NTP timeserver pool is alarmingly simple, and can be leveraged for launching both large-scale textit{opportunistic} attacks, and strategic, textit{targeted} attacks. We discuss a promising approach for mitigating such attacks.

View More Papers

Raising Trust in the Food Supply Chain

Alexander Krumpholz, Marthie Grobler, Raj Gaire, Claire Mason, Shanae Burns (CSIRO Data61)

Read More

Доверя́й, но проверя́й: SFI safety for native-compiled Wasm

Evan Johnson (University of California San Diego), David Thien (University of California San Diego), Yousef Alhessi (University of California San Diego), Shravan Narayan (University Of California San Diego), Fraser Brown (Stanford University), Sorin Lerner (University of California San Diego), Tyler McMullen (Fastly Labs), Stefan Savage (University of California San Diego), Deian Stefan (University of California…

Read More

Detecting Kernel Memory Leaks in Specialized Modules with Ownership...

Navid Emamdoost (University of Minnesota), Qiushi Wu (University of Minnesota), Kangjie Lu (University of Minnesota), Stephen McCamant (University of Minnesota)

Read More

POSEIDON: Privacy-Preserving Federated Neural Network Learning

Sinem Sav (EPFL), Apostolos Pyrgelis (EPFL), Juan Ramón Troncoso-Pastoriza (EPFL), David Froelicher (EPFL), Jean-Philippe Bossuat (EPFL), Joao Sa Sousa (EPFL), Jean-Pierre Hubaux (EPFL)

Read More