1. Introduction and Preliminaries
The security of the well-known RSA public key, EIGamal, and elliptic curve cryptography is based on difficult mathematical problems which are challenging to solve effectively on classical computers. However, due to the parallelism of quantum computing and the principle of quantum superposition, Shor’s algorithm can solve the integer factorization problem in polynomial time, which means that quantum computers with high computing power will be able to efficiently crack the widely used RSA algorithm [
1]. Grover’s algorithm is another quantum algorithm used to search for information in unordered databases, seriously threatening the security of hash functions and symmetric encryption algorithms in cryptography [
2,
3]. Current encryption technology cannot solve the following problems: (1) there is no combination of multiple disciplines to combat attacks by supercomputers or quantum computers; (2) it is inconceivable that users can remember long bytes of keys, such as 768 and 1024 bytes; (3) it is difficult for users to manage multiple keys; (4) it is not easy to generate single keys for one-time use.
The study of the encryption algorithms mentioned above does not involve the topology of graphs, leading to the introduction of asymmetric topological encryption based on the topological structure of graphs. Wang et al. [
4,
5] first established topological cryptography theories by combining graph structure and number theory. As a research tool for topological encryption, Yao et al. [
6,
7] proposed a method of generating number strings by Topcode-matrix based on graph labeling. Zhang et al. [
8,
9] extended the labeling function and obtained the Topcode-matrix under multiple restricted labelings, and introduced graphic lattices made by graph felicitous-type labelings and colorings in topological coding. In addition, Zhang et al. [
10] introduced the use of arbitrary zero-element Abelian finite modular additive graph groups to generate homomorphic graph group encryption technology. Mu et al. [
11] designed a topological graph encryption method based on Chinese characters by deriving the strokes of Chinese characters into graphs. Tian et al. [
12] generated graphical honeywords on the basis of graph structure and its labeling.
Asymmetric topology encryption is carried out with the help of the topology structure of the graph. Our graph-dependent encryption algorithm is based on topological structure plus mathematical constraints. The specific representation entity is the coloring graph, also known as the coding graph in graph theory. Its process can be briefly described as follows. For a topology graph
G, Bob uses the adjacent matrix
to derive the public key topology signature string
and the private key topology signature string
, both of which are number strings. Bob uses the topology coding matrix
to generate the public key string
and the private key string
. Bob sends the public key topology signature string and public key string to Alice while keeping his own private key topology signature and private key string. Alice uses the public key topology signature string and the public key string to encrypt the plaintext
F, then sends the ciphertext
to Bob. Bob uses the private key topology signature for verification; when
is authenticated by the adjacent matrix
, Bob determines that the ciphertext
is sent by Alice. Because the adjacency matrix is a one-to-one correspondence with graph
G, Alice cannot deny that she sent the ciphertext to Bob; Bob then uses the private key to obtain the plaintext. Topological encryption adopts dual protection to implement topological identity authentication and encryption to ensure file integrity.
Figure 1 illustrates the process of asymmetric topology encryption.
The topological coding matrix
proposed by Yao et al. [
7] refers to the arrangement of all labels of the vertices and edges of a graph with
p vertices and
q edges according to the following:
,
, and
, where
distributes us at least
different number strings in total.
Figure 2 shows a simple example of generating different number strings from a
adjacency matrix to derive number strings in a similar way to a topological coding matrix. The four number strings shown below can be generated according to
Figure 2, though of course there are many other ways to export a number string:
.
In this paper, we propose two random generation topology coding techniques using graph labeling as tool, in addition to two methods of generating number strings from graph structure. The first method is to randomly add edge-removing, which is used to generate a number string with the same scale as the graph. The second method is to randomly add a leaf, which is used to generate a number string from a larger-scale graph. We show the existence and related properties of odd-graceful labeling generated by these operations to add edge-removing and leafs. It is easy to derive the number string from the topological coding matrix of the graph, but difficult to recover the corresponding original graph from a given number string; thus, these two generation topology coding techniques provide a reliable theoretical guarantee for asymmetric topology encryption.
A
-graph is a graph containing
p vertices and
q edges. Graph isomorphism means that if two graphs
and
can be reordered or re-labeled so that their structure matches exactly, then the connection relationship between their vertices is exactly the same. The notation
indicates a set
with odd integer
; the symbol
is used to represent a set of consecutive integers
. The degree of a vertex
u refers to the number of edges adjacent to that vertex
u, denoted as
; in particular, a vertex with degree
is called a leaf. Other symbols not listed here can be found in [
13].
Definition 1 ([
14])
. Suppose that a connected -graph G admits a mapping . For each edge , the induced edge label is defined as . We write the vertex label set by and the edge label set by . We also have the following constraint conditions:I. ;
II. , ;
III. ;
IV. G is a bipartite graph with bipartition such that (or for short).
The following labelings are defined according to the above conditions:
Labeling-1: An odd-graceful labeling holds I, II, and III true;
Labeling-2. A set-ordered odd-graceful labeling holds I, II, III, and IV true.
Definition 2 ([
15])
. Let G be a -graph with .(i) The -graph obtained by removing an edge of and adding a new edge is denoted as , where and are called transform edges. We call the process of obtaining the graph the randomly adding edge-removing operation, and say that G is a -graph homomorphism to H, denoted as .
(ii) Suppose that the -graph G admits a W-type labeling/coloring f; if the -graph admits a W-type labeling/coloring g as well, such that if and if , then we call the process of obtaining H the labeling/coloring-preserved adding edge-removing operation and G the labeling/coloring-preserved -graph homomorphism to H, denoted as .
Coloring and labeling are both restricted functions that label or classify vertices and edges; the main difference is that coloring allows
for two different vertices
and labeling requires
. In
Figure 3, a
-graph
G admits an odd-graceful labeling
f, and each
-graph
made by doing the randomly adding edge-removing operation to the graph
G admits an odd-graceful labeling
induced by
f for
. In this way, per Definition 2 we have
for
; thus, we obtain the following graph homomorphism chain:
Definition 3. We define a labeling/coloring-preserved -graph set in the following way. Each graph -graphs for has a labeling such that with for and , , with for and for . For , admits the same labeling/coloring, but their topology is different.
Similarly, we have a -graph set by without any labeling/coloring.
Definition 4. The graph G obtained by adding a new leaf is denoted as , ; we call the process of obtaining the graph the random leaf-adding operation (Figure 4). Here, ‘randomly’ means that any vertex in the graph can have a leaf added to it; we say that is a leaf-added graph. Let G be a -graph; then, the leaf-added graph is the result of randomly adding m leaves to graph G, and is a -graph with and . 2. Main Results
Theorem 1. Let be a labeling/coloring-preserved -graph set based on a -graph G admitting an odd-graceful coloring f; then, each graph admits an odd-graceful coloring and .
Proof. For , it can be shown that is obtained by performing the randomly adding edge-removing operation on graph G in several steps. We obtain , and has an odd-graceful labeling . We can prove that also belongs to the set . The fact that indicates that is obtained by randomly adding edge-removing to graph G in several steps; then, we have , and can obtain . Because G has an odd-graceful coloring , the edge color set of obtained by the randomly adding edge-removing operation is exactly the same as the edge color set of G and , and still satisfies the constraint that the edge color be the difference in the color of the two end-vertices. In addition, their vertex set satisfies ; thus, if is still an odd-graceful coloring, then .
Considering that the operation used to randomly add edge-removing is reversible, such as for , it is possible to obtain by the inverse operation. For , we can obtain by randomly adding edge-removing to in several steps. The result has an odd-graceful labeling . In addition, G can be obtained by randomly adding edge-removing to in several steps, that is, . We have , , for ; thus, G admits an odd-graceful labeling f, and we have .
It has already been proved that the sets and are equal. □
Theorem 2. Let a -graph G admitting a set-ordered odd-graceful labeling f, represent the bipartition of vertices of G; then, with , , the coloring-preserved -graph set produced by the randomly adding edge-removing operation is denoted as , and the following proposition is true:
(1) Each element in also has a set-ordered graceful labeling.
(2) There are no two cases in where the labeling of the transform edge is 1 and .
(3) Let the label of the transformation edge be i; then, the number of elements in produced in the order of increasing i satisfies .
(4) A vertex in G is an isolated vertex in if and only if it is a leaf or has no adjacent edges labeled 1 or .
Proof. (1) Because G has a set-ordered odd-graceful labeling and each contained in is obtained by performing the randomly adding edge-removing operation on an edge of the graph G or , , every can be obtained by performing one or more randomly adding edge-removing operations on graph G. These operations ensure that the vertex label of the graph remains unchanged, which proves that and with , where and with . Let the graph obtained by graph have labeling ; then, the label of the vertices satisfies the condition of set-ordered . In addition, we can examine the label of each edge in . First, we analyze the first graph in , with obtained by deleting edge and adding edge on the basis of G and . Both and are satisfied, proving that each element in also has a set-ordered graceful labeling.
(2) A graph
G admits a set-ordered odd-graceful labeling
f. Thus,
G has a vertex set
with
, where
and
with
. According to the definition of set-ordered odd-graceful labeling, we let
with
,
with
, and
for every edge
. Thus, we obtain the following set-ordered restriction:
Therefore, we can find that under the set-ordered odd-graceful labeling of the graph
G, there is only one case in which the labels of the two end-vertices of the edge with the label 1 are
. We have
and
, where
. For all vertices in
G except the two vertices
and
, the difference between the two labels cannot be 1 and the minimum difference is equal to 2; therefore, there is no
for
. Similarly, looking at an edge labeled
with two end-vertices
and
labeled
and
, the difference between the label pairs of all vertices except for
and
is at most
. Therefore, if no formula
is true for
, then Proposition (2) is true.
(3) It is proved by Proposition (2) that when the randomly adding edge-removing operation is carried out from smallest to largest, there must be no edges labeled 1 and
in
, because
is obtained by the operation of
for
. Because
has a set-ordered odd-graceful labeling,
does not have an even number of labels; in turn,
does not have an even number of labels, which shows that the two end-vertices of the new edge will not appear in
X or
Y. Thus, there can only be one end-vertex in
X and one end-vertex in
Y. Next, we analyze the number of possible new edges when one of the end-vertices is labeled
, the possible new edges between 0 and each vertex in
Y are labeled
, and the possible new edge labels between a vertex labeled 2 and each vertex in
Y are
. Again, we can list
s vertices in
X in the neighborhood of each member of the possible new label set
(refer to the labels listed in
Table 1 for details). All the elements in the set are odd, forming an arithmetical sequence with the first term of
and an arithmetical difference of 2. The total number of possible new edges is
and the edge of
q in
G is part of
; thus, when
i is arranged from largest to smallest, the total number of
contained in
satisfies
.
Figure A1 shows an example of a set
generated by a small-scale graph
G.
(4) According to the shown in
Table 1, in addition to the labels 1 and
, the other leaf edges satisfy
, where
and end-vertex
must not overlap because
is a constant. If
, that is, if
u and
m are the same vertex, then
must be derived.
Table 1.
The labels of the possible new edges.
Table 1.
The labels of the possible new edges.
| | | | ⋯ | | |
---|
| | | | ⋯ | | |
| | | | ⋯ | | |
| | | | ⋯ | | |
⋯ | ⋯ | ⋯ | ⋯ | ⋯ | ⋯ | ⋯ |
| | | | ⋯ | | |
| | | | ⋯ | 3 | 1 |
(1) If the vertex m is a leaf vertex, that is, , and the leaf edges connected to m are not labeled 1 and , then there must be an edge such that edge has the same label as edge . This satisfies the equation ; after the operation , it is the case that m must be the isolated vertex in the structure of the corresponding in .
(2) If m is not the vertex of a leaf, let ; if its k adjacent edges do not contain an edge labeled 1 and , then its adjacent edge in can be obtained by G through k randomly adding edge-removing operations, causing m to become an isolated vertex. □
Theorem 3. A connected bipartite -graph T admitting a set-ordered odd-graceful labeling and then randomly adding leaves to T produces a -graph admitting an odd-graceful labeling.
Proof. The proof of this theorem is provided by an algorithm called the random leaf-adding algorithm (Algorithm 1).
Algorithm 1 Random Leaf-Adding Algorithm |
Input: A connected bipartite -graph T admitting a set-ordered odd-graceful labeling f. |
Output: A connected bipartite -graph admitting an odd-graceful labeling, where is the result of randomly adding leaves to T. |
Step 1. From the definition of a set-ordered odd-graceful labeling, the vertex set with , where and with . Because , we have |
|
meaning that each for is even, each for is odd, and |
|
Step 2. Next, a random lead-adding operation is performed on graph T to obtain graph . By randomly adding new leaves to each vertex by adding new edges for , and randomly adding new leaves to each vertex by adding new edges for , , it is permitted that some or some . The resulting graph is denoted as . |
Step 3. Define a labeling of by labeling edges , setting for , |
|
and for ; in addition, the last edge is colored with . |
Let ; for the newly edges of vertex , we define their labels as follows: |
for , ; |
for , ; |
|
Let ; then, the last edge is colored with . |
Step 4. This step classifies and labels all vertices in ; we label each vertex with for , label added leaves with for and , recolor vertices with for (where ), and color each vertex with for and . In addition, edges that already exist in T are labeled as . Obviously, the following conditions are true: and , , . |
Step 5. Return the odd-graceful labeling of . |
□