Method for constructing logic circuits of small depth and complexity for operation of inversion in finite fields of characteristic 2

Abstract

The present invention is directed to a method for constructing a logic circuit for inversion in finite field GF(2m), where m=nk, and k, n are coprime numbers, using bases in subfields GF(2n) and GF(2k). The present invention may be applied to error correction codes, including BCH codes, Reed-Solomon codes (which are a subset of BCH codes), turbo codes, and the like.

Description

FIELD OF THE INVENTION

[0001] The present invention generally relates to a scheme for arithmetic operations in finite fields, and more particularly, to a computational scheme for arithmetic operations in finite fields of characteristic 2 such as GF(2m), where m is a composite number, which is to be utilized in realizing error correction coding.

BACKGROUND OF THE INVENTION

[0002] An error correction code is an algorithm for expressing a sequence of numbers such that any errors which are introduced may be detected and corrected (within certain limitations) based on the remaining numbers. The study of error correction codes and the associated mathematics is known as coding theory. The commonly used error correction codes in digital communications and data storage may include BCH (Bose-Chaudhuri-Hochquenghem) codes, Reed-Solomon codes (which are a subset of BCH codes), turbo codes, and the like.

[0003] Error correction codes are often defined in terms of Galois or finite field arithmetic. A Galois field is commonly identified by the number of elements which the field contains. The elements of a Galois field may be represented as polynomials in a particular primitive field element, with coefficients in the prime subfield. Since the number of elements contained in a Galois field is always equal to a prime number, q, raised to a positive integer power, m, the notation GF(qm) is commonly used to refer to the finite field containing qm elements. In such a field all operations between elements comprising the field yield results which are each elements of the field.

[0004] Finite fields of characteristic 2 are important because these fields have data structures suitable for computers and may be utilized in error correction coding and cryptography. Conventionally, inverse calculation over a finite field with characteristic 2 may require an enormous amount of calculations compared with multiplication. For example, a well-known method for calculating inverses in a finite field follows directly from the cyclic structure of such a field that the inverse of a field element may be obtained directly from exponentiation. To be more precise:

a−1=a−2+2n

[0005] A person skilled in the art will recognize that this operation may be accomplished with 2n-3 multiplications. Logic circuits for inverse operation based on such a method may thus have large depth and- complexity. The depth of a logic circuit is the maximal number of logic elements in a path from a circuit input to a circuit output. The depth may determine the delay of the circuit. The complexity of a logic circuit is the number of logic elements in the circuit. The logic elements may have two inputs and one output.

[0006] Therefore, it would be desirable to provide a method for constructing logic circuits of small depth and complexity for operation of inversion in finite fields of characteristic 2.

SUMMARY OF THE INVENTION

[0007] Accordingly, the present invention is directed to a method for constructing a logic circuit for inversion in finite field GF(2m), where m=nk, and k, n are coprime numbers, using bases in subfields GF(2n) and GF(2k). The present invention may be applied to error correction codes, including BCH codes, Reed-Solomon codes (which are a subset of BCH codes), turbo codes, and the like.

[0008] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed. The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate an embodiment of the invention and together with the general description, serve to explain the principles of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The numerous advantages of the present invention may be better understood by those skilled in the art by reference to the accompanying figures in which:

[0010] FIG. 1 shows an exemplary configuration of a 2n-bit inverse calculation device in accordance with the present invention; and

[0011] FIG. 2 depicts an exemplary configuration of a 3n-bit inverse calculation device in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0012] Reference will now be made in detail to the presently preferred embodiments of the invention, examples of which are illustrated in the accompanying drawings.

[0013] One aspect of the present invention is directed to a method for constructing a logic circuit for inversion in finite field GF(2m), where m=nk, and k, n are coprime numbers, from its subfield GF(2n). The advantage of this method may lie in the fact that the structure of the subfield may remain accessible to direct manipulation when this type of construction is used. Furthermore, arithmetic operations defined in GF(2m) may be directly calculated in terms of arithmetic operations, including addition, multiplication, square, inversion, division, and the like, performed in the constituent subfield GF(2n).

[0014] According to one aspect of the present invention, logic circuits of small depth and complexity for operation of inversion in finite fields of characteristic 2 may be constructed. The depth of a logic circuit is the maximal number of logic elements in a path from a circuit input to a circuit output. The logic elements may include an exclusive OR unit (for addition), a multiplication unit (for multiplication), a square unit (for square, an inverse calculation unit (for inversion), and the like. The depth may determine the delay of the circuit. The complexity of a logic circuit is the number of logic elements in the circuit. The logic elements may have two inputs and one output. The logic circuit constructed according to the present invention may have less depth and complexity than the logic circuit constructed according to the conventional methods if the bases of the finite fields have a dimension less than 32.

[0015] The present invention may be applied to error correction codes, including BCH codes, Reed-Solomon codes (which are a subset of BCH codes), turbo codes, and the like because all devices for encoding and decoding may contain modules for multiplication and inversion.

[0016] The method of the present invention will be described in detail below.

[0017] Denote a polynomial basis in the field GF(2n)

Bα={1,α,α2,α3, . . . ,αn-1},

[0018] where

p(α)= 0,p(x)=pn-1xn-1+ . . . +p0,pi=0,1

[0019] and p(x) is an irreducible polynomial (minimal polynomial of element α-base generator).

[0020] Denote a normal basis in the field GF(2n)

Bα={α,α2,α4α8,α16, . . . ,α2n-1}

[0021] Normal bases may exist only for some irreducible polynomials p(x).

[0022] Normal bases may have such an advantage that squaring of these bases is equivalent to a shift operation:

(x0α+x1α2+ . . . xn-1α2n)2=xn-1α+x0α2+x1α4+ . . . +xn-2αn-1

Let 1 $$ ξ = ∑ i = 0 n - 1 ⁢ x i ⁢ α 2 i ,   o ⁢ ζ = ∑ j = 0 n - 1 ⁢ y j ⁢ α 2 j ,

[0023] be any elements of the field GF(2n), then their product (multiplication) may be represented by the equality: 2$\pi =\sum _{m=0}^{n-1}{p}_m{\alpha }^{2^m},\mathrm{where}$$p_m=\sum _{i,j=0}^{n-1}{t}_{i-j,m-j}{x}_i{y}_j,\alpha {\alpha }^{2^i}=\sum _{j=0}^{n-1}{t}_{i,j}{\alpha }^{2^j},$

[0024] and tij is a multiplication table of the given basis.

[0025] If one defines a matrix A as aij=ti-j,-j, where i-j and -j are a subtraction modulo n, then the foregoing formulas may be represented as 3$p_m=\sum _{i,j=0}^{n-1}{a}_{i,j}{S}^m\left(x_i\right)S^m\left(y_j\right),$

[0026] where Sm is a shift of the vector on m component, and 4$A\left(x,y\right)=\sum _{i,j=0}^{n-1}{a}_{i,j}{x}_i{y}_j$

[0027] is a bilinear form associated with the matrix A.

[0028] Let m=nk, where k, n are coprime numbers. One may choose in fields GF(2n), GF(2k) any normal bases

Bα={α,α2,α4,α8,α16, . . . ,α2k01},

Bβ={β,β2,β4,β8,β16, . . . ,β2n-1}.

[0029] Then the product of these bases

Bαβ={αβ,αβ2, . . . ,αβ2n-1, . . . ,α2k-1β, . . . ,α2k-1β2n-1}

[0030] is some permutation of some normal bases in the field GF(2m).

Using Quadratic Extension

[0031] Let k=2 and n does not divide by 2. One may use in the field GF(22n) a basis

Bαβ={αβ,αβ2, . . . ,αβ2n-1,α2β, . . . ,α2β2n-1},

[0032] which is a product of the optimal normal base of order 2

B α ={α,α2,}, α+α2=1,

[0033] and any normal (or standard polynomial) basis Bβ.

[0034] In field GF(2n) the norm N of any element

x0α+x1α2ε GF(2m)

[0035] is equal to 5$\begin{array}{c}N=\left(x_0\alpha +x_1{\alpha }^2\right)\left(x_0{\alpha }^2+x_1\alpha \right)\\ =x_0{x}_1\left({\alpha }^2+{\alpha }^4\right)+\left(x_0^2+x_1^2\right){\alpha }^3\\ =\left(x_0^2+x_1^2\right)+x_0{x}_1\mathrm{GF}\left(2^n\right).\end{array}$

[0036] The equality for an operation of inversion in the field GF(22n) is

(x0α+x1α2)-1=(x0α2+x1α)/N=(x1/N)α+(x0/N)α2

[0037] FIG. 1 shows an exemplary configuration of a 2n-bit inverse calculation device 100 according to one aspect of the present invention. The 2n-bit inverse calculation device 100 may include two n-bit exclusive OR units (An) 108 and 110, three n-bit multiplication units (Mn) 102, 114 and 116, two n-bit square units (Sn) 104 and 106, and one n-bit inverse calculation unit (In) 112.

[0038] As shown in FIG. 1, the 2n-bit inverse calculation device 100 may calculate the inverse e-1=(x1/N)α+(x0/N)α2ε GF(22n) of an element e=x0α+x1α2ε GF(22n) by using arithmetic operations in a subfield GF(2n). First, a 2n-bit input e may be split into two n-bit parts x0 and x1. Then, x0 may be duplicated to provide inputs to Mn 102, Sn 104, and Mn 116, and x1 may be duplicated to provide inputs to Mn 102, Sn 106, and Mn 114. Mn 102 may receive inputs x0 and x1 and output x0x1, which may be an input to An 108. Sn 104 may receive x0 as an input and output x02, which may become an input to An 108. An 108 may receive x0x1 and x02 as inputs and output x0x1+x02, which may become an input to An 110. Sn 106 may receive x1 as an input and output x12, which may become an input to An 110. An 110 may receive x0x1+x02 and x12 as inputs and output x0x1+x02+x12, which is the norm N and may become an input to In 112. In 112 may receive N as an input and output 1/N, which may be duplicated to provide inputs to Mn 114 and Mn 116. Mn 116 may receive x0 and 1/N as inputs and output x0/N. Mn 114 may receive x1 and 1/N as inputs and output x1/N. x0/N and x1/N may then be joined and outputted as the inverse e-1, which is in 2n bits.

[0039] Recurrent upper bound of the complexity of an inversion is

L (I(2n))≦L(I(n))+2L(M(n))+L(N(2n)),

[0040] where L(N(2n)) is the complexity of the norm, and L(M(n)) is the complexity of multiplication in the field GF(2n).

[0041] Recurrent upper bound of the depth of inversion is

D (I(2n))≦D(I(n))+D(M(n))+D(N(2n)).

[0042] Valid estimation of the complexity and the depth of norm N may be as follows:

L (N(2n))≦L(M(n))+2L(K(n))+n,

D (N(2n))≦D(M(n))+1,

[0043] where L(K(n)) is the complexity of squaring in the base Bβof the field GF(2n). If Bβis a normal basis, then L(K(n))=0, and

L (N(2n))=L(M(n)),

D (N(2n))=D(M(n))

[0044] in many practical cases.

[0045] Multiplication may be represented by the formula

(x0α+x1α2)(y0α+y1α2)=(x1y0+(x1+x0)y1)α+(x1y0+x0(y0+y1))α2

[0046] Recurrent upper bounds of the complexity and the depth of multiplication are

L (M(2n))≦3L(M(n))+4n,

D (M(2n))≦D(M(n))+2.

Using Cubic Extension

[0047] Let k=3, and n does not divide by 3. One may use in the field GF(23n) a basis

Bαβ={αβ,αβ2, . . . ,αβ2n-1, . . . ,α4β, . . . ,α4β2n-1},

[0048] which is a product of the optimal normal basis of order 3

B α ={α,α2,α4},α2+α3=1

[0049] and any normal (or standard polynomial) basis Bβ.

[0050] In field GF(2n) the norm N of any element

(x0α+x1α2+x2α4)ε GF(q3),q=2n,xiε GF(q)

is 6 $$ N = ( x 0 ⁢ α + x 1 ⁢ α 2 + x 2 ⁢ α 4 ) ⁢ ( x 1 ⁢ α + x 2 ⁢ α 2 + x 0 ⁢ α 4 ) ⁢ ( x 2 ⁢ α + x 0 ⁢ α 2 + x 1 ⁢ α 4 ) = x 0 ⁢ x 1 ⁢ x 2 + ( x 1 2 + x 2 2 ) ⁢ x 2 + ( x 0 2 + x 2 2 ) ⁢ x 0 + ( x 1 2 + x 0 2 ) ⁢ x 1 = x 0 ⁢ x 1 ⁢ x 2 + ( x 1 + x 2 ) 3 + ( x 0 + x 2 ) 2 ⁢ ( x 0 + x 1 ) ⁢ ⁢ GF ⁡ ( q ) .

[0051] Inversion of any element

(x0α+x1α2+x2α4)ε GF(q3),xiε GF(q)

[0052] may be represented by the equality

(x0α+x1α2+x2α4)-1=(x1α+x2α2+x0α4)(x2α+x0α2+x1α4)/N

[0053] where

(x1α+x2α2+x0α4)(x2α+x0α2+x1α4)=((x0+x2)2+x1x2)α+((x1+x0)2+x0x2)α2+((x1+x2)2+x1x0)α4

[0054] This equality demonstrates that coordinates Xi of inverse element (x0α+x1α2+x2α4)-1 may be shifted if coordinates xi are shifted.

[0055] Referring now to FIG. 2, an exemplary configuration of a 3n-bit inverse calculation device 200 according to one aspect of the present invention is shown. The 3n-bit inverse calculation device 200 may include eight n-bit exclusive OR units (An) 202, 204, 206, 222, 224, 226, 232 and 234, six n-bit multiplication units (Mn) 208, 210, 212, 220, 228, and 230, and three n-bit square units (Sn) 214, 216 and 218.

[0056] The 3n-bit inverse calculation device 200 may calculate the inverse E-1=[((x0+x2)2+x1x2)/N]α+[((x1+x0)2+x0x2)/N]α2+[((x1+x2)2+x1x0)/N]α4(z0/N)α+(z1/N)α2+(z2/N)α4ε GF(23n) of an element E=(x0α+x1α2+x2α4)ε GF(23n) by using arithmetic operations in a subfield GF(2n). First, a 3n-bit input E may be split into three n-bit parts x0, x1 and x2. An 202 may have x0 and x2 as inputs and output t1=x0+x2. Sn 214 may have t1 as an input and output t7=t12=(x0+x2)2, which may become inputs to An 222 and Mn 230. An 204 may have x0 and x1 as inputs and output t2=x0+x1, which may become inputs to Sn 216 and Mn 230. Sn 216 may have t2 as an input and output t8=t22=(x0+x1)2, which may become an input to An 224. An 206 may have x1 and x2 as inputs and output t3=x1+x2, which may become inputs to Sn 218 and Mn 228. Sn 218 may have t3 as an input and output t9=t32=(x1+x2)2, which may become inputs to An 226 and Mn 228.

[0057] Mn 208 may have x0 and x1 as inputs and output t4=x0x1, which may become an input to An 226. Mn 210 may have x1 and x2 as inputs and output t5=x1x2, which may become an input to An 222. Mn 212 may have x0 and x2 as inputs and output t6=x0x2, which may become inputs to An 224 and Mn 220. Mn 220 may have x1 and t6 as inputs and output t13=x1t6=x0x1x2, which may become an input to An 234.

[0058] An 222 may receive t5 and t7 as inputs and output z0=(x0+x2)2+x1x2. An 224 may receive t6 and t8 as inputs and output z1=(x1+x0)2+x0x2. An 226 may receive t4 and t9 as inputs and output z2=(x1+x2)2+x1x0.

[0059] Mn 228 may have t3 and t9 as inputs and output t10=t3t9=(x1+x2)(x1+x2)2=(x1+x2)3, which may become an input to An232. Mn 230 may have t2 and t7 as inputs and output t11=t2t7=(x0+x1)(x0+x2)2, which may become an input to An 232. An 232 may have t10 and t11 as inputs and output t12=t10+t11=(x1+x2)3+(x0+x1)(x0+x2)2, which may become an input to An 234. An 234 may have t12 and t13 as inputs and output N=t12+t13=(x1+x2)3+(x0+x1)(x0+x2)2+x0x1x2.

[0060] After z0, z1, z2, and N are obtained, those of ordinary skill in the art will understand how to obtain the inverse E-1=(z0/N)α+(z1/N)α2+(z2/N)α4ε GF(23n). For example, an n-bit inverse calculation unit (In) may be provided, which may have N as an input and output 1/N. Three additional n-bit multiplication units (Mn) may also be applied: the first Mn may have z0 and 1/N as inputs and output z0/N; the second Mn may have z1 and 1/N as inputs and output z1/N; the third Mn may have z2 and 1/N as inputs and output z2/N. The obtained z0/N, z1/N and z2/N may then be joined and outputted as the inverse E-1, which is in 3n bits.

[0061] From the equality 7$\begin{array}{c}N=x_0{x}_1{x}_2+{\left(x_1+x_2\right)}^3+{\left(x_0+x_2\right)}^2\left(x_0+x_1\right)\\ =x_0\left(x_1{x}_2\right)+\left({\left(x_1+x_2\right)}^2\left(x_1+x_2\right)+{\left(x_0+x_2\right)}^2\left(x_0+x_1\right)\right),\end{array}$

[0062] and assuming D(M(n))≧D(K(n))+2, upper bounds may be obtained:

L (N(3n))≦4L(M(n))+2L(K(n))+4n,

D (N(3n))≦2D(M(n))+1.

[0063] By realizing together with N operators

(x0+x2)2+x1x2

(x1+x0)2+x0x2

(x1+x2)2+x1x0

[0064] and parallel executing three times multiplication on N-1, estimations for the complexity and the depth of inversion in the field GF(23n) are:

L (I(3n))≦L(I(n))+9L(M(n))+3L(K(n))+8n,

D (I(3n))≦D(I(n))+3D(M(n))+1;

and

L (I(3n))≦L(I(n))+6L(M(n))+L(N(3n)+3L(K(n))+6n,

D (I(3n))≦D(I(n))+D(M(n))+D(N(3n)).

[0065] If Bβ is a normal basis, then L(K(n))=0.

Inversion in Field GF(23)

[0066] In a partial case x1 ε GF(2), the equality x12=x1 is valid, and consequently one may have the norm 8$\begin{array}{c}N=x_0{x}_1{x}_2+{\left(x_1+x_2\right)}^3+{\left(x_0+x_2\right)}^2\left(x_0+x_1\right)\\ =x_0{x}_1{x}_2+\left(x_1+x_2\right)+\left(x_0+x_2\right)\left(x_0+x_1\right)\\ =x_0{x}_1{x}_2+x_1+x_2+x_0+x_0{x}_2+x_1{x}_2+x_0{x}_1\\ =x_0⩔x_1⩔x_2\end{array}$

[0067] where V represents a logical disjunction. The norm of nonzero elements in this case is equal to 1, so the inversion

(x0α+x1α+x2α4)-1

[0068] may be represented by the equalities:

(x0+x2)2+x1x2=x0+x2+x1x2=x0+x2x1,

(x1+x0)2+x0x2=x1+x0+x0x2=x1+x0x2,

(x1+x2)2+x1x0=x1+x2+x1x0=x2+x1x0.

[0069] Consequently the complexity and the depth in this case have bounds:

L (I(3))≦6,

D (I(3))≦2.

Multiplication in Cubic Extension

[0070] Multiplication in a given basis Bα may be represented as follows: 9$\left(x_0\alpha +x_1{\alpha }^2+x_2{\alpha }^4\right)\left(y_0\alpha +y_1{\alpha }^2+y_2{\alpha }^4\right)=\left(\left(x_0{y}_1+x_1{y}_0\right)+\left(x_1{y}_2+x_2{y}_1\right)+x_2{y}_2\right)\alpha +\left(\left(x_0{y}_2+x_2{y}_0\right)+\left(x_1{y}_2+x_2{y}_1\right)+x_0{y}_0\right){\alpha }^2+\left(\left(x_0{y}_1+x_1{y}_0\right)+\left(x_0{y}_2+x_2{y}_0\right)+x_1{y}_1\right){\alpha }^4$

[0071] If the following brief notations are used,

[ij]= (xi+xj)(yi+yj), (ij)=(xiyj+xjyi), (i)=xiyi,

[0072] then

[ij]= (ij)+(i)+(j)

[0073] The multiplication equality may thus be rewritten as

((x0y1+x1y0)+(x1y2+x2y1)+x2y2)=(0,1)+(1,2)+(2)==[0,1]+[1,2]+(0),

((x0y2+x2y0)+(x1y2+x2y1)+x0y0)=(0,2)+(1,2)+(0)==[0,2]+[1,2]+(1),

((x0y1+x1y0)+(x0y2+x2y0)+x1y1)=(0,1)+(0,2)+(1)==[0,1]+[0,2]+(2).

[0074] The valid upper bounds for the complexity and the depth of multiplication are:

L (M(3n))≦6L(M(n))+12n,

D (M(3n))≦D(M(n))+3.

Using Biquadratic Extension

[0075] Let k=4, and n does not divide by 4. One may use in the field GF(24n) a basis

Bαβ={αβ,αβ2, . . . ,αβ2n-1, . . . ,α8β, . . . ,α8β2n-1},

[0076] which is a product of the optimal normal basis of order 4

B α {α,α2,α4,α8}, α+α2+α3+α4=1,

[0077] and any normal (or standard polynomial) basis Bβ.

[0078] Any element

(x0α+x1α2+x2α4+x3α8)ε GF(q4),xiε GF(q),q=2n,

[0079] may be inverted by the following equality:

(x0α+x1α2+x2α4+x3α8)-1=[(x1α+x2α2+x3α4+x0α8)(x2α+x3α2+x0α4+x1α8)(x3α+x0α2+x1α4+x2α8)]/N

[0080] where the norm

N= (x1α+x2α2+x3α4+x0α8)(x2α+x3α2+x0α4+x1α8)(x3α+x0α2+x1α4+x2α8) (x0α+x1α+x2α4+x3α8)

[0081] is equal to 10$\sum _{i=0}^3{x}_i^3\sum _{i=0}^3{x}_i+\sum _{i=0}^3{x}_i^2{x}_{i\oplus 2}{x}_{i\oplus 3}+{\left(\sum _{i\ne j}{x}_i{x}_j\right)}^2+\prod _{i=0}^3{x}_i\mathrm{GF}\left(q\right),$

[0082] and the product

(x1α+x2α2+x3α4+x0α8)(x2α+x3α2+x0α4+x1α8)(x3α+x0α2+x1α4+x2α8)

[0083] is equal to

X0α+X1α2+X2α4+X3α8,

[0084] where

X 0 =x 2 (x22+m(x0,x1,x3))+x1x2(x1+x2)+x0x3(x0+x3)+x1(x0+x3)2+x0x22

X 1 =x 3 (x32+m(x2,x2,x0))+x2x3(x2+x3)+x1x0(x1+x0)+x2(x1+x0)2+x1x32,

X 2 =x 0 (x02+m(x2,x3,x1))+x3x0(x3+x0)+x2x1(x2+x1)+x3(x2+x1)2+x2x02,

X 3 =x 1 (x12+m(x3,x0,x2))+x0x1(x0+x1)+x3x2(x3+x2)+x0(x3+x2)2+x3x12,

[0085] where m (x, y, z) is a brief notation for xy+xz+yz, and ⊕ is addition modulo 4.

[0086] Coordinates Xi of a given product shift if inputs shift.

[0087] For computation of N and all Xi, one may at first compute all products xixj with the complexity of 6L(M(n)), then compute all squares xi2 with the complexity of 4L(K(n)), then compute all sums xi+xj with the complexity of 6n, then compute the formula 11${\left(\sum _{i\ne j}{x}_i{x}_j\right)}^2+\prod _{i=0}^3{x}_i$

[0088] with the complexity L(M(n))+L(K(n))+6n and the depth of less than or equal to 2D(M(n))+2 (under the condition of D(M(n))≧D(K(n))+2), then compute 12$\sum _{i=0}^3{x}_i^2{x}_{i\oplus 2}{x}_{i\oplus 3}=x_0{x}_3\left(x_0{x}_2+x_1^2\right)+x_1{x}_2\left(x_0{x}_2+x_3^2\right)$

[0089] with the complexity of 2L(M(n))+3n and the depth of 2D(M(n))+2, then compute 13$\sum _{i=0}^3{x}_i^3\sum _{i=0}^3{x}_i=\sum _{i=0}^3{x}_i^2{x}_i\sum _{i=0}^3{x}_i$

[0090] with the complexity of 5L(M(n))+n and the depth of 2D(M(n))+D(K(n))+2, and finally compute all Xi with the complexity of 12L(M(n))+20n and the depth of 2D(M(n)) +3.

[0091] The total complexity of the logic circuit with outputs N and Xi may be equal to 26L(M(n))+36n+4L(K(n)), and the depth may be equal to 2D(M(n))+3+max{D(K(n)),1}.

[0092] Using the equality 14$\sum _{i\ne j}{x}_i{x}_j=m\left(x_0,x_1,x_3\right)+m\left(x_3,x_0,x_2\right)+x_0{x}_3+x_1{x}_2$

[0093] may decrease the upper bound for complexity to 26L(M(n))+34n+4L(K(n)) under the condition of D(M(n))≧D(K(n))+3.

[0094] Using the equality 15$\begin{array}{c}{X}_0=x_2^2\left(x_0+x_2\right)+x_1{x}_2\left(x_1+x_2\right)+\left(x_2+x_0+x_3\right)m\left(x_0,x_1,x_3\right)\\ =x_2^2\left(x_0+x_2+x_1\right)+x_1^2{x}_2+\left(x_2+x_0+x_3\right)m\left(x_0,x_1,x_3\right)\end{array}$

[0095] one may rewrite other equalities as follows

X 1 =x 3 2 (x1+x3+x2)+x22x3+(x3+x1+x0)m(x1,x2,x0),

X 2 =x 0 2 (x2+x0+x3)+x32x0+(x0+x2+x1)m(x2,x3,x1),

X 3 =x 1 2 (x3+x1+x0)+x02x1+(x1+x3+x2)m(x3,x0,x2).

[0096] Therefore, for computation of all Xi it is enough to use only sums x0+x3, x1+x2, and because all sums

x0+x2+x1,

x1+x3+x2,

x2+x0+x3,

x3+x1+x0

[0097] may be computed with 4 additions, thus the total complexity may decrease to 26L(M(n))+30n+4L(K(n)) with the same depth of 2D(M(n))+3+max{D(K(n)),1} (under the condition of D(M(n))≧D(K(n))+3).

[0098] Final bounds for complexity and depth may be:

L (I(4n))≦L(I(n))+30L(M(n))+4L(K(n))+30n,

D (I(4n))≦D(I(n))+3D(M(n))+3+max{D(K(n)),1}.

[0099] If Bβ is a normal basis, then

L (K(n))=D(K(n))=0

Inversion in Field GF(24)

[0100] In a partial case xi ε GF(2), the equality xi2xi is valid, and consequently the norm 16$\begin{array}{c}N=\sum _{i=0}^3{x}_i+\sum _{i=0}^3{x}_i{x}_{i\oplus 2}{x}_{i\oplus 3}+\sum _{i\ne j}{x}_i{x}_j+\prod _{i=0}^3{x}_i\\ =\sum _{I⋐\left\{0,1,2,3\right\}}\prod _{i\in I}{x}_i=x_0⩔x_1⩔x_2⩔x_3\end{array}$

[0101] The norm of a nonzero element in this case is equal to 1, so inversion

(x0α+xiα2+x2α4+x3α8)-1

[0102] may be represented by:

X 0 =a2(a0+m(a0, a1, a3))+a1(a0+a3),

X 1 =a3(a1+m(a1, a2, a0))+a2(a1+a0),

X 2 =a0(a2+m(a2, a3, a1))+a3(a2+a1),

X 3 =a1(a3+m(a3, a0, a2))+a0(a3+a2),

[0103] where m(x, y, z) denotes the negation of m(x, y, z)=xy+xz+yz.

[0104] Since 17$\begin{array}{c}{a}_2\left(a_0+⫬m\left(a_0,a_1,a_3\right)\right)+a_1\left(a_0+a_3\right)=\\ a_2\left(a_0+a_0{a}_1+a_0{a}_3+a_1{a}_3+1\right)+a_1\left(a_0+a_3\right)=\\ \left(a_1⫬a_2\right)\left(a_0+a_3\right)+a_2\left(⫬a_0⩔a_3\right),\end{array}$

[0105] the complexity of this equality is equal to 6 and the depth is equal to 3. Final bounds for the complexity and depth are

L (I(4))≦24,

D (I(4))≦3.

Multiplication in Biquadratic Extension

[0106] In a given basis

Bα={α, α2, α4, α8}, α+α2+α3+α4=1

[0107] the operation of multiplication may be represented by: 18$\begin{array}{c}\left(a_0\alpha +a_1{\alpha }^2+a_2{\alpha }^4+a_3{\alpha }^8\right)\left(b_0\alpha +b_1{\alpha }^2+b_2{\alpha }^4+b_3{\alpha }^8\right)=\\ \left(a_1{b}_2+a_2{b}_1+a_0{b}_2+a_2{b}_0+a_1{b}_3+a_3{b}_1+a_3{b}_3\right)\alpha +\\ \left(a_2{b}_3+a_3{b}_2+a_1{b}_3+a_3{b}_1+a_2{b}_0+a_0{b}_2+a_0{b}_0\right){\alpha }^2+\\ \left(a_3{b}_0+a_0{b}_3+a_2{b}_0+a_0{b}_2+a_3{b}_1+a_1{b}_3+a_1{b}_1\right){\alpha }^4+\\ \left(a_0{b}_1+a_1{b}_0+a_3{b}_1+a_1{b}_3+a_0{b}_2+a_2{b}_0+a_2{b}_2\right){\alpha }^8\end{array}$

[0108] Using the brief notation, one may have

(a1b2+a2b+a0b2+a2b0+a1b3+a3b1+a3b3)=(1,2)+(0,2)+(1,3)+(3)=[1,2]+[0,2]+[1,3]+(0),

(a2b3+a3b2+a1b3+a3b1+a2b0+a0b2+a1b1)=(2,3)+(1,3)+(2,0)+(1)=[2,3]+[1,3]+[2,0]+(0),

(a3b0+a0b3+a2b0+a0b2+a3b1+a1b3+a2b2)=(3,0)+(2,0)+(3,1)+(2)=[3,0]+[2,0]+[3,1]+(1),

(a0b1+a1b0+a3b1+a1b3+a0b2+a2b0+a3b3)==(0,1)+(3,1)+(0,2)+(3)=[0,1]+[3,1]+[0,2]+(2).

[0109] The complexity and the depth of multiplication (for odd n) thus have upper bounds

L (M(4n))≦10L(M(n))+21n,

D (M(4n))≦D(M(n))+3.

EXAMPLE

Logical Circuits for Multiplicative Operations in the Field GF(212)

[0110] From foregoing descriptions, it follows that one may construct a multiplication circuit in the field GF(24) with the complexity L(M(4))=31 and the depth D(M(4))=4, and an inversion circuit with the complexity L(M(4))=24 and the depth D(M(4))=3.

[0111] Using the foregoing described method of cubic extension, one may thus construct logic circuits for multiplication and inversion in the field GF(212) with the following complexity and depth:

L (M(12))=6M(4)+48=234,

D (M(12)=3+D(M(4))=7,

L (I(12))≦L(I(4))+9L(M(4))+28=331,

and

D (I(12))≦D(I(4))+3D(M(4))+1=16.

Using 5th Degree Extension

[0112] Let k=5 and n does not divide by 5. One may use in the field GF(25n) a basis

Bαβ={αβ,αβ2, . . . ,αβ2n-1, . . . ,α16β, . . . ,α16β2n-1},

[0113] which is a product of the optimal normal basis of order 5

B α ={α, α2, α4, α8, α16}, α+α2+α4+α5=1,

[0114] and any normal (or standard polynomial) basis Bβ.

[0115] Any element

x= (x0α+x1α2+x2α4+x3α8+x4α16) ε GF(q5), xi ε GF(q), q=2n

[0116] may be inverted by the equality:

(x0α+x1α2+x2α4+x3α8+x4α8)-1=[σ(x)σ2(x)σ3(x)σ4(x)]/N

[0117] where the norm N is equal to the product

N=xσ (x)σ2(x)σ3(x)σ4(x),

[0118] where

σ(x)=(x4α+x0α2+x1α4+x2α8+x3α16)

[0119] is a shift of vector x, and σk(x)=σ(σk-1(x)) is k-multiple shift (shift on k positions).

[0120] Using the equality σ(x)σ(y)=σ(xy), the norm may be an invariant concerning a shift because 19$\begin{array}{c}\sigma \left(N\right)=\sigma \left(x\sigma \left(x\right){\sigma }^2\left(x\right){\sigma }^3\left(x\right){\sigma }^4\left(x\right)\right)\\ =\sigma \left(x\right){\sigma }^2\left(x\right){\sigma }^3\left(x\right){\sigma }^4\left(x\right){\sigma }^5\left(x\right)\\ =\sigma \left(x\right){\sigma }^2\left(x\right){\sigma }^3\left(x\right){\sigma }^4\left(x\right)x\\ =N\end{array}$

[0121] Therefore

N=x 0 α+x 1 α2+x2α4+x3α8+x4α16=x0=x1=x2=x3=x4,

[0122] since

α+α2+α4+α8+α16=1.

[0123] N may be computed: 20$\begin{array}{c}N={\left(\sum _{i=0}^4{x}_i^2+\sum _{i<j}{x}_i{x}_j\right)}^2\sum _{i=0}^4{x}_i+\sum _{i=0}^4{x}_i^2{x}_{i\oplus 2}\left(x_{i\oplus 1}{x}_{i\oplus 4}+x_{i\oplus 3}^2\right)+\\ \sum _{i=0}^4{x}_i^3\left(\left(x_i+x_{i\oplus 1}\right)\left(x_{i\oplus 2}+x_{i\oplus 3}\right)+x_{i\oplus 3}^2+X_{i\oplus 1}^2+x_{i\oplus 4}{x}_{i\oplus 3}\right)+\\ \prod _{i=0}^4{x}_i\in \mathrm{GF}\left(q\right),\end{array}$

[0124] where ⊕ is addition modulo 5.

[0125] One may also note that

σ(x)σ2(x)σ3(x)σ4(x)=X0α+X1α2+X2α4+X3α8+X4α16

[0126] where all coordinates Xi shift if inputs shift.

[0127] In fact,

σ(σ(x)σ2(x)σ3(x)σ4(x))=σ(Nx-1)=Nσ(x)-1=σ(σ(x)σ2(σ(x))σ3(σ(x))σ4(σ(x)).

[0128] Therefore for brevity one may compute only the first coordinate in this product 21$\begin{array}{c}{X}_0=\left(x_2^2+x_4^2\right)\left(x_0^2+x_1^2+x_3^2+x_4^2\right)+x_0^4+x_1^4+x_1{x}_2{x}_3{x}_4+x_4^3\left(x_1+x_2\right)+\\ x_2^3\left(x_1+x_3\right)+x_4\left(x_1^3+x_3^3\right)+x_1^2{x}_2{x}_3+x_3^2{x}_2{x}_4+x_4^2{x}_1{x}_3+\\ x_0^2\left(x_1{x}_2+x_3{x}_4+x_1{x}_3\right)\end{array}$

[0129] To estimate the complexity of inversion, one may assume for simplicity that in the field GF(2n) a normal basis is chosen.

[0130] At first one may compute all cubes xi3 with the complexity of 5L(M(n)) and the depth of D(M(n)), then compute all products xixj with the same depth and the complexity of 10L(M(n)), then compute all sums ai+aj,ai4+ai⊕14,ai2+ai⊕22, with the depth of 1 and the complexity of 20n, and all sums ai3+ai⊕23 with the depth of 1+D(M(n)) and the complexity of 5n.

[0131] Then one may compute the formula 22${\left(\sum _{i=0}^4{x}_i^2+\sum _{i<j}{x}_i{x}_j\right)}^2\sum _{i=0}^4{x}_i$

[0132] with the complexity of 4L(M(n))+6n and the depth of 3+2D(M(n)), using the equality 23$\begin{array}{c}\sum _{i=0}^4{x}_i^2+\sum _{i<j}{x}_i{x}_j=\left(x_3^2+x_0^2+x_0{x}_1\right)+\left(x_1^2+x_4^2+x_3{x}_4\right)+\\ \left(x_0+x_1+x_2\right)\left(x_2+x_3+x_4\right)\end{array}$

[0133] Next one may compute the formula 24$\sum _{i=0}^4{x}_i^3\left(\left(x_i+x_{i\oplus 1}\right)\left(x_{i\oplus 2}+x_{i\oplus 3}\right)+x_{i\oplus 3}^2+x_{i\oplus 1}^2+x_{i\oplus 4}{x}_{i\oplus 3}\right)$

[0134] with the complexity of 10L(M(n))+14n and the depth of 5+2D(M(n)), and the formula 25$\sum _{i=0}^4{x}_i^2{x}_{i\oplus 2}\left(x_{i\oplus 1}{x}_{i\oplus 4}+x_{i\oplus 3}^2\right)$

[0135] with the complexity of 10L(M(n))+9n and the depth of 4+2D(M(n)).

[0136] Then one may compute the sum of the last formula with the complexity of 10L(M(n))+14n+10L(M(n))+9n and the depth of 6+2D(M(n)).

[0137] But the depth may be decreased on 1 without increasing the complexity if one represents this sum as the sum of 10 additive terms, from which only 5 terms have the depth of 2+2D(M(n)) and others have the depth of 1+2D(M(n)), and construct a binary tree from operations of addition so that 5 of its vertex have the depth of 3, and the other 5 vertex have the depth of 4.

[0138] Therefore the sum of the foregoing three given formulas has the complexity of 24L(M(n))+29n and the depth of 6+2D(M(n)). One may add a term 26$\prod _{i=0}^4{x}_i$

[0139] with the complexity of 2L(M(n))+n and the depth of 2D(M(n))+1+max{D(M(n)),6}. Therefore the norm N computed may have the complexity of

41L(M(n))+57n

[0140] and the depth of

2D(n))+1+max{D(M(n)),6}.

[0141] The formula

(Xi⊕22+Xi⊕42)(Xi2+Xi⊕12+Xi⊕32+Xi⊕42)+Xi4+Xi⊕14

[0142] computed may have the complexity of 5L(M(n))+10n and the depth of 3+D(M(n)).

[0143] The formula 27$x_{i\oplus 4}^3\left(x_{i\oplus 1}+x_{i\oplus 2}\right)+x_{i\oplus 2}^3\left(x_{i\oplus 1}+x_{i\oplus 3}\right)+x_{i\oplus 4}\left(x_{i\oplus 1}^3+x_{i\oplus 3}^3\right)+x_{i\oplus 1}^2{x}_{i\oplus 2}{x}_{i\oplus 3}+x_{i\oplus 1}{x}_{i\oplus 2}{x}_{i\oplus 3}{x}_{i\oplus 4}+x_{i\oplus 3}^2{x}_{i\oplus 2}{x}_{i\oplus 4}+x_{i\oplus 4}^2{x}_{i\oplus 1}{x}_{i\oplus 3}+x_i^2\left(x_{i\oplus 1}{x}_{i\oplus 2}+x_{i\oplus 3}{x}_{i\oplus 4}+x_{i\oplus 1}{x}_{i\oplus 3}\right)$

[0144] computed may have the complexity of 40L(M(n))+45n and the depth of 4+2D(M(n)).

[0145] Therefore the system Xi, i=0, . . . , 4 may have the complexity

45L(M(n))+60n

[0146] and the depth

5+2D(M(n)).

[0147] The complexity of operator N, Xi is equal to

45(L(M(n))+60n+41L(M(n))+57n=86L(M(n))+117n,

[0148] and the depth is equal to 2D(M(n))+1+max {D(M(n)), 6}.

[0149] Final estimates for the complexity and depth of inversion are

L (I(5n))≦L(I(n))+91L(M(n))+117n,

D (I(5n))≦D(I(n))+3D(M(n))+1+max {D(M(n)), 6}.

Inversion in Field GF(25)

[0150] In a partial case xi ε GF(2), the equality xi2 =x1 is valid, and consequently the norm of a nonzero element is equal to 1.

[0151] As all coordinates of an element

(x0α+x1α2+x2α4+x3α8+x4α8)-1

[0152] shift, if inputs shift, then it may be sufficient to compute only the first coordinate as follows: 28$\begin{array}{c}{X}_0=\left(x_2^2+x_4^2\right)\left(x_0^2+x_1^2+x_3^2+x_4^2\right)+x_0^4+x_1^4+x_1{x}_2{x}_3{x}_4+\\ x_4^3\left(x_1+x_2\right)+x_2^3\left(x_1+x_3\right)+x_4\left(x_1^3+x_3^3\right)+x_1^2{x}_2{x}_3+\\ x_3^2{x}_2{x}_4+x_4^2{x}_1{x}_3+x_0^2\left(x_1{x}_2+x_3{x}_4+x_1{x}_3\right)\\ =x_4{x}_1+x_4+x_0+x_1+x_1{x}_2{x}_3{x}_4+x_2{x}_0+x_4{x}_0+\\ x_1{x}_2{x}_3+x_3{x}_2{x}_4+x_4{x}_1{x}_3+x_0\left(x_1{x}_2+x_3{x}_4+x_1{x}_3\right)\\ =\stackrel{\_}{x_2{x}_2}\left(x_1⩔x_4\right)+x_0{x}_1\left(x_2+x_3\right)+x_3{x}_4\left(x_0+x_1\right)+x_0\stackrel{\_}{x_2+x_4},\end{array}$

[0153] where {overscore (x)} is a brief notation for negation x.

[0154] The depth of this formula is 4, and the complexity is 14. Final estimations for the complexity and depth of inversion are

D (I(5))≦4,

L (I(5))≦55.

Multiplication in 5th Degree Extension

[0155] Using brief notations, multiplications may be represented by the formula

(a0α+a1α2+a2α4+a3α8+a4α16)(b0α+b1α2+b2α4+b3α8+b4α16)=(c0α+c1α2+c2α4+c3α8+c4α16),

c 0 =(0,1)+(1,3)+(2,3)+(2,4)+(4),

c 1 =(1,2)+(2,4)+(3,4)+(3,0)+(0),

c 2 =(2,3)+(3,0)+(4,0)+(4,1)+(1),

c 3 =(3,4)+(4,1)+(0,1)+(0,2)+(2),

c 4 =(4,0)+(0,2)+(1,2)+(1,3)+(3),

[0156] where

(ij)=(xiyj+xjyi), (i)=xiyj

[0157] The complexity and the depth of multiplication (n does not divide by 5) may have upper bounds:

L (M(5n))≦15L(M(n))+40n,

D (M(5n))≦D(M(n))+4.

EXAMPLE

Logical Circuits for Multiplicative Operations in the Field GF(220)

[0158] Using extension of 5th degree, one may construct a logic circuit for inversion with the complexity of

L (I(20))≦L(I(4))+91L(M(4))+468=3100+468+24=3313

[0159] and the depth of

D (I(20))≦D(I(4))+3D(M(4))+1+max{D(M(4)),6}=22

[0160] since L(M(4))=31,D(M(4))=4,L(I(4))=24,D(I(4))=3, as shown in the foregoing description.

[0161] Using biquadratic extension one may construct a logic circuit for inversion with the complexity of

L (I(20))≦L(I(5))+30L(M(5))+170=1875

[0162] and the depth of

D (I(20))≦D(I(5))+3D(M(5))+4=23.

[0163] Both logic circuits use different bases in the field GF(220), but these bases are equivalent: one is permutation of another, and some are a normal base in this field. For any from these bases, the complexity and the depth of multiplication may have upper bounds

L (M(20))≦15L(M(4))+160=625,

D (M(20))≦D(M(4))+4=8.

[0164] It is to be noted that the above described embodiments according to the present invention may be conveniently implemented using conventional general purpose digital computers programmed according to the teachings of the present specification, as will be apparent to those skilled in the computer art. Appropriate software coding may readily be prepared by skilled programmers based on the teachings of the present disclosure, as will be apparent to those skilled in the software art.

[0165] It is to be understood that the present invention may be conveniently implemented in forms of software package. Such a software package may be a computer program product which employs a storage medium including stored computer code which is used to program a computer to perform the disclosed function and process of the present invention. The storage medium may include, but is not limited to, any type of conventional floppy disks, optical disks, CD-ROMS, magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, or any other suitable media for storing electronic instructions.

[0166] It is also understood that the specific order or hierarchy of steps in the methods disclosed are examples of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the method can be rearranged while remaining within the scope of the present invention. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy presented.

[0167] It is believed that the present invention and many of its attendant advantages will be understood by the foregoing description. It is also believed that it will be apparent that various changes may be made in the form, construction and arrangement of the components thereof without departing from the scope and spirit of the invention or without sacrificing all of its material advantages. The form herein before described being merely an explanatory embodiment thereof, it is the intention of the following claims to encompass and include such changes.

Claims

1. A method for constructing a logic circuit for operation of inversion in finite field GF(22n), wherein n is a positive integer, comprising the steps of: (a) expressing an element e ε GF(22n) ase=x0α+x1α2(x0, x1 εGF(2n))where α+α2=1 so that an inverse e-1 of said element e in said finite field GF(22n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(x1/N)α+(x0/N)α2where N=(x02+x12)+x0x1 εGF(2n) by using an optimal normal basis of order 2 {α, α2}; and (b) calculating said inverse e-1 of said element e in said finite field GF(22n) by executing said combination of arithmetic operations in said subfield GF(2n).

2. A method for constructing a logic circuit for operation of inversion in finite field GF(23n), wherein n is a positive integer, comprising the steps of: (a) expressing an element e ε GF(23n) ase=x0α+x1α2+x2α4(x0, x1, x2 ε GF(2n))where α2+α3=1 so that an inverse e-1 of said element e in said finite field GF(23n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[((x0+x2)2+x1x2)/N]α+[((x1+x0)2+x0x2)/N]α2+[((x1+x2)2+x1x0)/N]α4where N=x0x1x2+(x1+x2)3+(x0+x2)2(x0+x1) ε GF(2n) by using an optimal normal basis of order 3 {α, α2, α4}; and (b) calculating said inverse e-1 of said element e in said finite field GF(23n by executing said combination of arithmetic operations in said subfield GF(2n).

3. The method of claim 2, wherein said n=1.

4. A method for constructing a logic circuit for operation of inversion in finite field GF(24n), wherein n is a positive integer, comprising the steps of: (a) expressing an element e ε GF(24n) ase=x0α+x1α2+x2α4+x3α8(x0, x1, x2, x3 ε GF(2n))where α+α2+α3+α4=1 so that an inverse e-1 of said element e in said finite field GF(24n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(X0/N)α+(X1/N)α2+(X2/N)α4+(X3/N)α8where 29N=∑i=03⁢xi3⁢∑i=03⁢xi+∑i=03⁢xi2⁢ ⁢xi⊕2⁢xi⊕3+(∑i≠j⁢xi⁢xj)2+∏i=03⁢xi⁢⁢GF⁡(2n)X0=x22(x0+x2+x1)+x12x2+(x2+x0+x3)m(x0,x1,x3)X1=x32(x1+x3+x2)+x22x3+(x3+x1+x0)m(x1,x2,x0)X2=x02(x2+x0+x3)+x32x0+(x0+x2+x1)m(x2,x3,x1)X3=x12(x3+x1+x0)+x02x1+(x1+x3+x2)m(x3,x0,x2)⊕ is addition modulo 4, by using an optimal normal basis of order 4 {α, α2, α4, α8}; and (b) calculating said inverse e-1 of said element e in said finite field GF(24n) by executing said combination of arithmetic operations in said subfield GF(2n).

5. The method of claim 4, wherein said n=1.

6. A method for constructing a logic circuit for operation of inversion in finite field GF(25n), wherein n is a positive integer, comprising the steps of: (a) expressing an element e ε GF(25n) ase=x0α+x1α2+x2α4+x3α8+x4α16 (x0,x1,x2,x3,x4 ε GF(2n))where α+α2+α4+α5=1 so that an inverse e-1 of said element e in said finite field GF(25n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[σ(x)σ2(x)σ3(x)σ4(x)]/Nwhereσ(x)=(x4α+x0α2+x1α4+x2α8+x3α16) 30N=⁢(∑i=04⁢xi2+∑i<j⁢xi⁢xj)2⁢∑i=04⁢xi+∑i=04⁢xi2⁢xi⊕2⁡(xi⊕1⁢xi⊕4+xi⊕32)+⁢∑i=04⁢xi3⁡((xi+xi⊕1)⁢(xi⊕2+xi⊕3)+xi⊕32+xi⊕12+xi⊕4⁢xi⊕3)+⁢∏i=04⁢xi∈GF⁡(2n)β is addition modulo 5, by using an optimal normal basis of order 5 {α, α2, α4, α8, α16}; and (b) calculating said inverse e-1 of said element e in said finite field GF(25n) by executing said combination of arithmetic operations in said subfield GF(2n).

7. The method of claim 6, wherein said n=1.

8. A device for calculating an inversion in finite field GF(22n), wherein n is a positive integer, comprising: (a) means for expressing an element e ε GF(22n) ase=x0α+x1α2(x0, x1 ε GF(2n))where α+α2=1 so that an inverse e-1 of said element e in said finite field GF(22n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(x1/N)α+(x0/N)α2where N=(x02+x12)+x0x1 ε GF(2n) by using an optimal normal basis of order 2 {α, α2}; and (b) means for calculating said inverse e-1 of said element e in said finite field GF(22n) by executing said combination of arithmetic operations in said subfield GF(2n).

9. A device for calculating an inversion in finite field GF(23n), wherein n is a positive integer, comprising: (a) means for expressing an element e ε GF(23n) ase=x0α+x1α2+x2α4(x0,x1,x2 ε GF(2n))where α2+α3=1 so that an inverse e-1 of said element e in said finite field GF(23n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[((x0+x2)2+x1x2)/N]α+[((x1+x0)2+x0x2)/N]α2+[((x1+x2)2+x1x0)/N]α4where N=x0x1x2+(x1+x2)3 +(x0+x2)2(x0+x1) ε GF(2n) by using an optimal normal basis of order 3 {α, α2, α4}; and (b) means for calculating said inverse e-1 of said element e in said finite field GF(23n) by executing said combination of arithmetic operations in said subfield GF(2n).

10. The device of claim 9, wherein said n=1.

11. A device for calculating an inversion in finite field GF(24n), wherein n is a positive integer, comprising: (a) means for expressing an element e ε GF(24n) ase=x0α+x1α2+x2α4+x3α8(x0,x1,x2,x3ε GF(2n))where α+α2+α3α4=1 so that an inverse e-1 of said element e in said finite field GF(24n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(X0/N)α+(X1/N)α2+(X2/N)α4+(X3/N)α8where 31N=∑i=03⁢χi3⁢∑i=03⁢χi+∑i=03⁢χi2⁢ ⁢xi⊕2⁢ ⁢xi⊕3+(∑i≠j⁢xi⁢xj)2+∏i=03⁢xi⁢⁢ ⁢GF⁡(2n)X0=x22(x0+x2+x1)+x12x2+(x2+x0+x3)m(x0,x1,x3)X1=x32(x1+x3+x2)+x22x3+(x3+x1+x0)m(x1,x2,x0)X2=x02(x2+x0+x3)+x32x0+(x0+x2+x1)m(x2,x3,x1)X3=x12(x3+x1+x0)+x02x1+(x1+x3+x2)m(x3,x0,x2)⊕ is addition modulo 4, by using an optimal normal basis of order 4 {α, α2, α4, α8}; and (b) means for calculating said inverse e-1 of said element e in said finite field GF(24n) by executing said combination of arithmetic operations in said subfield GF(2n).

12. The device of claim 11, wherein said n=1.

13. A device for calculating an inversion in finite field GF(25n), wherein n is a positive integer, comprising: (a) means for expressing an element e ε GF(25n) ase=x0α+x1α2+x2α4+x3α8+x4α16(x0,x1,x2,x3,x4 ε GF(2n))where α+α2+α4+α5=1 so that an inverse e-1 of said element e in said finite field GF(25n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[σ(x)σ2(x)σ3(x)σ4(x)]/Nwhereα(x)=(x4α+x0α2+x1α4+x2α8+x3α16) 32N=⁢(∑i=04⁢χi2+∑i<j⁢xi⁢xj)2⁢∑i=04⁢xi+∑i=04⁢χi2⁢ ⁢xi⊕2⁡(xi⊕1⁢xi⊕4+χi⊕32)+⁢∑i=04⁢χi3⁡((xi+xi⊕1)⁢(xi⊕2+xi⊕3)+χi⊕32+χi⊕12+xi⊕4⁢xi⊕3)+⁢∏i=04⁢xi⁢⁢ ⁢GF⁡(2n)⊕ is addition modulo 5, by using an optimal normal basis of order 5 {α, α2, α4, α8, α16}; and (b) means for calculating said inverse e-1 of said element e in said finite field GF(25n) by executing said combination of arithmetic operations in said subfield GF(2n).

14. The device of claim 13, wherein n=1.

15. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a system for calculating an inverse in finite field GF(22n), the computer readable program code means includes: (a) first computer readable program code means for causing said computer to express an element e ε GF(22n) ase=x0α+x1α2(x0,x1 ε GF(2n))where α+α2=1 so that an inverse e-1 of said element e in said finite field GF(22n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(x1/N)α+(x0/N)α2where N=(x02+x12)+x0x1 ε GF(2n) by using an optimal normal basis of order 2 {α, α2}; and (b) second computer readable program code means for causing said computer to calculate said inverse e-1 of said element e in said finite field GF(22n) by executing said combination of arithmetic operations in said subfield GF(2n).

16. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a system for calculating an inverse in finite field GF(23n), the computer readable program code means includes: (a) first computer readable program code means for causing said computer to express an element e ε GF(23n) ase=x0α+x1α2+x2α4(x0,x1,x2 ε GF(2n))where α2+α3=1 so that an inverse e-1 of said element e in said finite field GF(23n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[((x0+x2)2+x1x2)/N]α+[((x1+x0)2+x0x2)/N]α2+[((x1+x2)2+x1x0)/N]α4where N=x0x1x2+(x1+x2)3+(x0+x2)2(x0+x1) ε GF(2n) by using an optimal normal basis of order 3 {α, α2, α4}; and (b) second computer readable program code means for causing said computer to calculate said inverse e-1 of said element e in said finite field GF(23n) by executing said combination of arithmetic operations in said subfield GF(2n).

17. The article of manufacture of claim 16, wherein said n=1.

18. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a system for calculating an inverse in finite field GF(24n), the computer readable program code means includes: (a) first computer readable program code means for causing said computer to express an element e ε GF(24n) ase=x0α+x1α2+x2α4+x3α8(x0,x1,x2,x3 ε GF(2n))where α+α2+α3+α4=1 so that an inverse e-1 of said element e in said finite field GF(24n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=(X0/N)α+(X1/N)α2+(X2/N)α4+(X3/N)α8where 33N=∑i=03⁢χi3⁢∑i=03⁢χi+∑i=03⁢χi2⁢ ⁢xi⊕2⁢ ⁢xi⊕3+(∑i≠j⁢xi⁢xj)2+∏i=03⁢xi⁢⁢ ⁢GF⁡(2n)X0=x22(x0+x2+x1)+x12x2+(x2+x0+x3)m(x0,x1,x3)X1=x32(x1+x3+x2)+x22x3+(x3+x1+x0)m(x1,x2,x0)X2=x02(x2+x0+x3)+x32x0+(x0+x2+x1)m(x2,x3,x1)X3=x12(x3+x1+x0)+x02x1+(x1+x3+x2)m(x3,x0,x2)⊕ is addition modulo 4, by using an optimal normal basis of order 4 {α, α2, α4, α8}; and (b) second computer readable program code means for causing said computer to calculate said inverse e-1 of said element e in said finite field GF(24n) by executing said combination of arithmetic operations in said subfield GF(2n).

19. The article of manufacture of claim 18, wherein said n=1.

20. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a system for calculating an inverse in finite field GF(25n), the computer readable program code means includes: (a) first computer readable program code means for causing said computer to express an element e ε GF(25n) ase=x0α+x1α2+x2α4+x3α8+x4α16 (x0,x1,x2,x3,x4 ε GF(2n))where α+α2+α4+α5=1 so that an inverse e-1 of said element e in said finite field GF(25n) is expressed as a combination of arithmetic operations performed in subfield GF(2n) given bye-1=[(σ(x)σ2(x)σ3(x)σ4(x)]/Nwhereσ(x)=(x4α+x0α2+x1α4+x2α8+x3α16) 34N=⁢(∑i=04⁢χi2+∑i<j⁢xi⁢xj)2⁢∑i=04⁢xi+∑i=04⁢χi2⁢ ⁢xi⊕2⁡(xi⊕1⁢xi⊕4+χi⊕32)+⁢∑i=04⁢χi3⁡((xi+xi⊕1)⁢(xi⊕2+xi⊕3)+χi⊕32+χi⊕12+xi⊕4⁢xi⊕3)+⁢∏i=04⁢xi⁢⁢ ⁢GF⁡(2n)⊕ is addition modulo 5, by using an optimal normal basis of order 5 {α, α2, α4, α8, α16}; and (b) second computer readable program code means for causing said computer to calculate said inverse e-1 of said element e in said finite field GF(25n) by executing said combination of arithmetic operations in said subfield GF(2n).

21. The article of manufacture of claim 20, wherein said n=1.