Memory hard functions (MHFs) are an important cryptographic primitive that are used to design egalitarian proofs of work and in the construction of moderately expensive key-derivation functions resistant to brute-force attacks. Broadly speaking, MHFs can be divided into two categories: data-dependent memory hard functions (dMHFs) and data-independent memory hard functions (iMHFs). iMHFs are resistant to certain side-channel attacks as the memory access pattern induced by the honest evaluation algorithm is independent of the potentially sensitive input e.g., password. While dMHFs are potentially vulnerable to side-channel attacks (the induced memory access pattern might leak useful information to a brute-force attacker), they can achieve higher cumulative memory complexity (CMC) in comparison than an iMHF. In particular, any iMHF that can be evaluated in N steps on a sequential machine has CMC at most 𝒪((N^2 log log N)/log N). By contrast, the dMHF scrypt achieves maximal CMC Ω(N^2) - though the CMC of scrypt would be reduced to just 𝒪(N) after a side-channel attack. In this paper, we introduce the notion of computationally data-independent memory hard functions (ciMHFs). Intuitively, we require that memory access pattern induced by the (randomized) ciMHF evaluation algorithm appears to be independent from the standpoint of a computationally boundedmore »
This content will become publicly available on September 26, 2023
PREDATOR: A Cache Side-Channel Attack Detector Based on Precise Event Monitoring
Abstract—Recent work has demonstrated the security risk associated
with micro-architecture side-channels. The cache timing side-channel is
a particularly popular target due to its availability and high leakage
bandwidth. Existing proposals for defending cache side-channel attacks
either degrade cache performance and/or limit cache sharing, hence,
should only be invoked when the system is under attack. A lightweight
monitoring mechanism that detects malicious micro-architecture
manipulation in realistic environments is essential for the judicious
deployment of these defense mechanisms.
In this paper, we propose PREDATOR, a cache side-channel attack
detector that identifies cache events caused by an attacker. To detect
side-channel attacks in noisy environments, we take advantage of the
observation that, unlike non-specific noises, an active attacker alters
victim’s micro-architectural states on security critical accesses and thus
causes the victim extra cache events on those accesses. PREDATOR
uses precise performance counters to collect detailed victim’s access
information and analyzes location-based deviations. PREDATOR is
capable of detecting five different attacks with high accuracy and
limited performance overhead in complex noisy execution environments.
PREDATOR remains effective even when the attacker slows the attack
rate by 256 times. Furthermore, PREDATOR is able to accurately report
details about the attack such as the instruction that accesses the attacked
data. In the case of GnuPG RSA [20], PREDATOR can pinpoint the
square/multiply operations in the Modulo-Reduce algorithm; and in the
case more »
- Award ID(s):
- 2106771
- Publication Date:
- NSF-PAR ID:
- 10357261
- Journal Name:
- 2022 IEEE International Symposium on Secure and Private Execution Environment Design
- Sponsoring Org:
- National Science Foundation
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