Connecting the Dots: Privacy Leakage via Write-Access Patterns to the Main Memory

Abstract

Data-dependent access patterns of an application to an untrusted storage system are notorious for leaking sensitive information about the user's data. Previous research has shown how an adversary capable of monitoring both read and write requests issued to the memory can correlate them with the application to learn its sensitive data. However, information leakage through only the write access patterns is less obvious and not well studied in the current literature. In this work, we demonstrate an actual attack on power-side-channel resistant Montgomery's ladder based modular exponentiation algorithm commonly used in public key cryptography. We infer the complete 512-bit secret exponent in ~ 3.5 minutes by virtue of just the write access patterns of the algorithm to the main memory. In order to learn the victim algorithm's write access patterns under realistic settings, we exploit a compromised DMA device to take frequent snapshots of the application's address space, and then run a simple differential analysis on these snapshots to find the write access sequence. The attack has been shown on an Intel Core(TM) i7-4790 3.60GHz processor based system. We further discuss a possible attack on McEliece public-key cryptosystem that also exploits the write-access patterns to learn the secret key.