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Performance Analysis of Real Time Implementations of Voice Encryption Algorithms using Blackfin Processors

A large part of the latest research in speech coding and speech encryption algorithms is motivated by the need of obtaining secure military communications, to allow effective operation in a hostile environment. Since the bandwidth of the communication channel is a sensitive problem in military applications, low bitrate speech compression methods and high throughput encryption algorithms are mostly used. Several speech encryption methods are characterized by very strict requirements in power consumption, size, and voltage supply. These requirements are difficult to fulfill, given the complexity and number of functions to be implemented, together with the real time requirement and large dynamic range of the input signals. To meet these constraints, careful optimization should be done at all levels, ranging from algorithmic level, through system and circuit architecture, to layout and design of the cell library. The key points of this optimization are among others, the choice of the algorithms, the modification of the algorithms to reduce computational complexity, the choice of a fixed-point arithmetic unit, the minimization of the number of bits required at every node of the algorithm, and a careful match between algorithms and architecture. This paper describes the performance analysis on Digital Signal Processor (DSP) platform of some of the recently proposed voice encryption algorithms, as well as the performance of stream ciphers such as Grain v1, Trivium and Mickey 2.0 (which are suited for real time voice encryption). The algorithms were ported onto a fixed point DSP, Blackfin 537, and stage by stage optimization was performed to meet the real time requirements. Memory optimization techniques such as data placement and caching were also used to reduce the processing time. The goal was to determine which of the evaluated encryption algorithms is best suited for real time secure communications.