JultikaUniversity of Oulu repository

Encryption is being used more than ever before. It is used to prevent eavesdropping on our communications over cell phone calls and Internet, securing network connections, making e-commerce and e-banking possible and generally hiding information from unwanted eyes. The performance of encryption functions is therefore important as slow working implementation increases costs. At server side faster implementation can reduce the required capacity and on client side it can lower the power usage. Block ciphers are a class of encryption functions that are typically used to encrypt large bulk data, and thus make them a subject of many studies when endeavoring greater performance. The x86-64 architecture is the most dominant processor architecture in server and desktop computers; it has numerous different instruction set extensions, which make the architecture a target of constant new research on fast software implementations. The examined block ciphers — Blowfish, AES, Camellia, Serpent and Twofish — are widely used in various applications and their different designs make them interesting objects of investigation. Several optimization techniques to speed up implementations have been reported in previous research; such as the use of table look-ups, bit-slicing, byte-slicing and the utilization of “out-of-order” scheduling capabilities. We examine these different techniques and utilize them to construct new implementations of the selected block ciphers. Focus with these new implementations is in modes of operation which allow multiple blocks to be processed in parallel; such as the counter mode. The performance measurements of new implementations were carried out by using the System for Unified Performance Evaluation Related to Cryptographic Operations and Primitives (SUPERCOP) framework on four different processors: AMD K8, AMD K10, Intel Core2 and Intel Sandy-Bridge. The parallel processing permitted by particular modes of operation can improve performance of a block cipher even with traditional table look-up optimization. Bit-slicing, byte-slicing and word-slicing can be used to parallelize block cipher processing in vector registers. These ‘sliced’ techniques can improve the throughput of block cipher implementations significantly compared to table look-up based approaches. Our byte-sliced AES-NI/AVX implementation of Camellia reaches the speed of 5.32 cycles per byte on Intel Sandy-Bridge processor, being 2.65 times faster than our two-way table look-up implementation and 3.96 times faster than the implementation found in the OpenSSL library.