Spectral modular arithmetic

In many areas of engineering and applied mathematics, spectral methods provide very powerful tools for solving and analyzing problems. For instance, large to extremely large sizes of numbers can efficiently be multiplied by using discrete Fourier transform and convolution property. Such computations are needed when computing π to millions of digits of precision, factoring and also big prime search projects. When it comes to the utilization of spectral techniques for modular operations in public key cryptosystems two difficulties arise; the first one is the reduction needed after the multiplication step and the second is the cryptographic sizes which are much shorter than the optimal asymptotic crossovers of spectral methods. In this dissertation, a new modular reduction technique is proposed. Moreover, modular multiplication is given based on this reduction. These methods work fully in the frequency domain with some exceptions such as the initial, final and partial transformations steps. Fortunately, the new technique addresses the reduction problem however, because of the extra complexity coming from the overhead of the forward and backward transformation computations, the second goal is not easily achieved when single operations such as modular multiplication or reduction are considered. On the contrary, if operations that need several modular multiplications with respect to the same modulus are considered, this goal is more tractable. An obvious example of such an operation is the modular exponentiation i.e., the computation of c=m[superscript e] mod n where c, m, e, n are large integers. Therefore following the spectral modular multiplication operation a new modular exponentiation method is presented. Since forward and backward transformation calculations do not need to be performed for every multiplication carried during the exponentiation, the asymptotic crossover for modular exponentiation is decreased to cryptographic sizes. The method yields an efficient and highly parallel architecture for hardware implementations of public-key cryptosystems

Kısmi ve Tam Dönümlü Spektral Metotların Karşılaştırması

Bu çalışmada, yakın zamanda sunulmuş spektral modüler aritmetik işlemlerinin aritmetik karmaşıklığı üzerindeki bir analiz adım adım değerlendirme yöntemi ile karşılaştırılmıştır. Bilgisayar aritmetiğinde spektral yöntemlerin standart kullanımı çarpma ve indirgeme adımlarının spektrum ve zaman uzayında birbirinden ayrı olarak gerçekleştirilmesi gerektiğini belirtmektedir. Bu tarz bir prosedür ise açıkça tam dönümlü (ileri ve geri yönde) DFT hesaplamalarına ihtiyaç duymaktadır. Öte yandan, bazı kısmı değerlerin işlem sırasında hesaplanması ile, yeni yöntemler indirgeme işlemi de dahil olmak üzere tüm verilerin tüm zamanlarda spektrumda tutulmasını gerektiren bir yaklaşımı benimsemişlerdir. Tüm bu yaklaşımların işlem süresi performanslarını karşılaştırdığımızda, tam dönümlü algoritmaların son zamanlarda önerilmiş yöntemlerden daha iyi performans gösterdiğini bu çalışmada göstermiş bulunmaktayız

Elliptic and hyperelliptic curves on embedded µP

It is widely recognized that data security will play a central role in future IT systems. Providing public-key cryptographic primitives, which are the core tools for security, is often difficult on embedded processor due to computational, memory, and power constraints. This contribution appears to be the first thorough comparison of two public-key families, namely elliptic curve (ECC) and hyperelliptic curve cryptosystems on a wide range of embedded processor types (ARM, ColdFire, PowerPC). We investigated the influence of the processor type, resources, and architecture regarding throughput. Further, we improved previously known HECC algorithms resulting in a more efficient arithmetic