The threats of physical side-channel attacks and their countermeasures have been widely researched. Most physical side-channel attacks rely on the unavoidable influence of computation or storage on current consumption or voltage drop on a chip. Such data-dependent influence can be exploited by, for instance, power or electromagnetic analysis. In this work, we introduce a novel non-invasive physical side-channel attack, which exploits the data-dependent changes in the impedance of the chip. Our attack relies on the fact that the temporarily stored contents in registers alter the physical characteristics of the circuit, which results in changes in the die's impedance. To sense such impedance variations, we deploy a well-known RF/microwave method called scattering parameter analysis, in which we inject sine wave signals with high frequencies into the system's power distribution network (PDN) and measure the echo of the signals. We demonstrate that according to the content bits and physical location of a register, the reflected signal is modulated differently at various frequency points enabling the simultaneous and independent probing of individual registers. Such side-channel leakage challenges the t-probing security model assumption used in masking, which is a prominent side-channel countermeasure. To validate our claims, we mount non-profiled and profiled impedance analysis attacks on hardware implementations of unprotected and high-order masked AES. We show that in the case of the profiled attack, only a single trace is required to recover the secret key. Finally, we discuss how a specific class of hiding countermeasures might be effective against impedance leakage.
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A Taxonomy of Side-Channels
After the discovery of data leakage from cryptographic
algorithm implementations, there has been a need to
counter or hide the data that allow adversaries to capture the
cryptographic key. To explore side-channel attack methods or
countermeasures, it is important for researchers to understand
what side-channels are and how they are produced. There have
been numerous surveys in which the side-channel attacks and
countermeasures are surveyed, but little to no research about the
side-channels themselves. This paper addresses this gap in the
existing literature by developing a taxonomy for side-channels,
classified by the manner in which they are produced. Following
the proposed model, some of the common side-channel analysis
attack methods are discussed and we show where the side-channel
would fit in the proposed model.
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- Award ID(s):
- 2142948
- PAR ID:
- 10506676
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- Proceedings of IEEE Southeastcon
- ISSN:
- 1558-058X
- ISBN:
- 979-8-3503-1710-7
- Page Range / eLocation ID:
- 1564 to 1570
- Format(s):
- Medium: X
- Location:
- Atlanta, GA, USA
- Sponsoring Org:
- National Science Foundation
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