Abstract

SIMON is a block cipher developed to provide flexible security options for lightweight hardware applications such as the Internet-of-things (IoT). Safeguarding such resource-constrained hardware from side-channel attacks poses a significant challenge. Adiabatic circuit operation has recently received attention for such applications due to ultra-low power consumption. In this work, a charge-based methodology is developed to mount a correlation power analysis (CPA) based side-channel attack to an adiabatic SIMON core. The charge-based method significantly reduces the attack complexity by reducing the required number of power samples by two orders of magnitude. The CPA results demonstrate that the required measurements-to-disclosure (MTD) to retrieve the secret key of an adiabatic SIMON core is 4× higher compared to a conventional static CMOS based implementation. The effect of increase in the target signal load capacitance on the MTD is also investigated. It is observed that the MTD can be reduced by half if the load driven by the target signal is increased by 2× for an adiabatic SIMON, and by 5× for a static CMOS based SIMON. This sensitivity to target signal capacitance of the adiabatic SIMON can pose a serious concern by facilitating a more efficient CPA attack.

Highlights

  • As Internet-of-things (IoT) based devices have become an integral part of everyday life, the corresponding risk for security breaches is rapidly increasing [1]

  • This paper focuses on correlation power analysis (CPA), which is one of the most common power analysis based side-channel attacks [16,17]

  • A correlation power analysis (CPA) attack was established on an adiabatic SIMON block cipher

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Summary

Introduction

As Internet-of-things (IoT) based devices have become an integral part of everyday life, the corresponding risk for security breaches is rapidly increasing [1]. Ensuring the security and data privacy for lightweight applications (such as radio frequency identification based systems, wireless sensor nodes and energy harvesting IoT devices) is significantly challenging due to highly limited resources in terms of compute capability, power consumption, and physical area. Adiabatic circuits operate with a trapezoidal or sinusoidal power supply signal to maintain a small voltage difference between the power supply and output nodes during charging [22]. Adiabatic operation reduces the power consumption by minimizing the current to charge the output node. As the power supply signal falls, the charge stored at the output node is recycled back to the power supply. Adiabatic operation can save considerable power even at frequencies in the range of several hundred megahertz [32], which is sufficient for most of the lightweight applications

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