Analyzing and modeling encryption overhead for sensor network nodes 论文

摘要

Recent research in sensor networks has raised security issues for small embedded devices. Security concerns are motivated by the deployment of a large number of sensory devices in the field. Limitations in processing power, battery life, communication bandwidth and memory constrain the applicability of existing cryptography standards for small embedded devices. A mismatch between wide arithmetic for security (32 bit word operations) and embedded data bus widths (often only 8 or 16 bits) combined with lack of certain operations (e.g., multiply) in the ISA present other challenges.This paper offers two contributions. First, a survey investigating the computational requirements for a number of popular cryptographic algorithms and embedded architectures is presented. The objective of this work is to cover a wide class of commonly used encryption algorithms and to determine the impact of embedded architectures on their performance. This will help designers predict a system's performance for cryptographic tasks. Second, methods to derive the computational overhead of embedded architectures in general for encryption algorithms are developed. This allows one to project computational limitations and determine the threshold of feasible encryption schemes under a set of the constraints for an embedded architecture.Experimental measurements indicate uniform cryptographic cost for each encryption class and each architecture class and negligible impact of caches. RC4 is shown to outperform RC5 for the Motes Atmega platform contrary to the choice of RC5 for the Motes project, a choice driven in large by memory constraints. The analytical model allows to assess the impact of arbitrary embedded architectures as a multi-variant function for each encryption scheme. Overall, our results are not only valuable to assess the feasibility of encryption schemes for existing embedded architectures, they also extend to assess the feasibility of encryption methods for new algorithms and architectures for sensor systems.