Year of Publication

2015

Season of Publication

Fall

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Computer and Information Sciences (MS)

Department

Computing

NACO controlled Corporate Body

University of North Florida. School of Computing

First Advisor

Dr. Swapnoneel Roy

Second Advisor

Dr. Karthikeyan Umapathy

Third Advisor

Dr. Sandeep Reddivari

Department Chair

Dr. Sherif Elfayoumy

College Dean

Dr. Mark A. Tumeo

Abstract

In computer security, cryptographic algorithms and protocols are required to ensure security of data and applications. This research investigates techniques to reduce the energy consumed by cryptographic hash functions. The specific hash functions considered are Message Digest-2 (MD2), Message Digest-5 (MD5), Secure Hash Algorithm-1 (SHA-1) and Secure Hash Algorithm-2 (SHA-2).

The discussion around energy conservation in handheld devices like laptops and mobile devices is gaining momentum. Research has been done at the hardware and operating system levels to reduce the energy consumed by these devices. However, research on conserving energy at the application level is a new approach. This research is motivated by the energy consumed by anti-virus applications which use computationally intensive hash functions to ensure security. To reduce energy consumption by existing hash algorithms, the generic energy complexity model, designed by Roy et al. [Roy13], has been applied and tested. This model works by logically mapping the input across the eight available memory banks in the DDR3 architecture and accessing the data in parallel.

In order to reduce the energy consumed, the data access pattern of the hash functions has been studied and the energy complexity model has been applied to hash functions to redesign the existing algorithms. These experiments have shown a reduction in the total energy consumed by hash functions with different degrees of parallelism of the input message, as the energy model predicted, thereby supporting the applicability of the energy model on the different hash functions chosen for the study.

The study also compared the energy consumption by the hash functions to identify the hash function suitable for use based on required security level. Finally, statistical analysis was performed to verify the difference in energy consumption between MD5 and SHA2.

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