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Proceedings Paper

Towards leakage resiliency: memristor-based AES design for differential power attack mitigation
Author(s): Ganesh Khedkar; Colin Donahue; Dhireesha Kudithipudi
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Paper Abstract

Side-channel attacks (SCAs), specifically differential power attacks (DPA), target hardware vulnerabilities of cryptosystems. Next generation computing systems, integrated with emerging technologies such as RRAM, offer unique opportunities to mitigate DPAs with their inherent device characteristics. We propose two different approaches to mitigate DPA attacks using memristive hardware. The first approach, obfuscates the power profile using dual RRAM modules. The power profile stays almost uniform for any given data access. This is achieved by realizing a memory and its complementary module in RRAM hardware. Balancing logic, which ensures the parallel access, is implemented in CMOS. The power consumed with the dual-RRAM balancing is an order lower than the corresponding pure CMOS implementation. The second exploratory approach, uses a novel neuromemristive architecture to compute an AES transformation and mitigate DPAs. Both the proposed approaches were tested on a 128-bit AES algorithm. A customized simulation framework, integrating CAD tools, is developed to mount the DPA attacks. In both the designs, the attack mounted on the baseline architectures (CMOS only) was successful and full key was recovered. However, DPA attacks mounted on the dual RRAM modules and neuromemristive hardware modules of an AES cryptoprocessor yielded no successful keys, demonstrating their resiliency to DPA attacks.

Paper Details

Date Published: 22 May 2014
PDF: 11 pages
Proc. SPIE 9119, Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII, 911907 (22 May 2014); doi: 10.1117/12.2053373
Show Author Affiliations
Ganesh Khedkar, Rochester Institute of Technology (United States)
Colin Donahue, Rochester Institute of Technology (United States)
Dhireesha Kudithipudi, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9119:
Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII
Misty Blowers; Jonathan Williams, Editor(s)

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