## 4 Steps and Analysis of Cloud-Edge Collaborative Intelligent Security Encryption Strategy
### Security Model  
We provide Table 1, and these variables are used in the instructions that follow. From Figure 4, it can be seen that the task of data transmission between edges may need to be secured and of low latency, and in the case of data theft may lead to property damage, so encryption measures are needed for the transmitted data. The strength of encryption will result in transmission delay, so it is especially important to adopt low-delay encryption measures in secure transmission paths and the dynamic adaptation of encryption algorithms with good encryption in insecure transmission paths. First of all, we usually use symmetric encryption algorithms when transmitting data, the common ones being DES, AES, RCS, etc., which have different effective key lengths with each other, such as 128, 192, 256 bits, etc. We define the problem as follows. **Definition 1**. : _There is a symmetric encryption algorithm \(X\), the encryption function is EN, the plaintext is p, the key is k, the encrypted ciphertext is c, and then c = EN (p, k). In the same set, the decryption function is DE, the function to recover plaintext data is p = DE (c, k), and the use of k is the same._  
**Definition 2**. : _The algorithmic security Xs and time of X are related to the number of bits (Ks) of the encryption key, and the encryption rounds (Em). For a particular encryption algorithm X, we can use the multiratee Pearson correlation coefficients to express the correlation \(r_{Xs,Ks,Em}=\frac{\sum_{i=1}^{n}(Xs_{i}-Xs)(Ks_{i}-Ks)(Em_{i}-Em)}{\sqrt{ \sum_{i=1}^{n}(Xs_{i}-Xs)^{2}\sum_{i=1}^{n}(Ks_{i}-Ks)^{2}\sum_{i=1}^{n}(Em_{i }-Em)^{2}}}\), where \(Xs_{i}\), \(Ks_{i}\), and \(Em_{i}\) are the observations in the X-encrypted sample data; \(Xs\), \(Ks\), and \(Em\) are the mean values of \(Xs\), \(Ks\), and \(Em\), respectively; and \(n\) is the number of X-encrypted samples. And \(r_{Xs,Ks,Em}>0\) means that the security of encryption algorithm X is positively correlated with \(Ks\) and \(Em\), and on the contrary, \(r_{Xs,Ks,Em}<0\) means that the encryption time of encryption algorithm X is negatively correlated with \(Ks\) and \(Em\)._  
**Definition 3**. : _As the effective key length Ks of the encryption algorithm X and the encryption round Em become more complex, the sender's cost of sending and hardware cost increase accordingly, and there will be a non-linear relationship between these three: \(Cost=Ks^{2}+Em^{2}+Ks\cdot Em\)._  
**Definition 4**. : _For a certain data transmission process, the type of attack uses the UNSW-NB15 dataset [38], which contains 10 network data types as shown in Table 2, 1 normal sample and 9 \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Definition** \\ \hline c & Coded text \\ \(p\) & Explicit message \\ \(Xs\) & Key security level \\ \(Ks\) & Number of valid key bits \\ \(Em\) & Number of rounds of encryption algorithm execution \\ \(Cost\) & The cost to the user of completing the task \\ \(Mi\) & Importance of the task \\ \(r\) & Pearson correlation coefficient \\ \(N_{i}\) & The the number of attacks of category \(i\) in a period of time \\ \(U\) & Key update cycle \\ \(Sec_{i}\) & The severity of the attack of category \(i\) \\ \(t\) & Attack severity factor [37] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Variables of interest. attack samples, respectively, and the consequences of the attack occurrence are described by the following formula: \(Sec_{i}=N_{i}\cdot e^{i}\). In transmitting tasks, each one has a different level of importance, denoted by Mi. For this symmetric encryption algorithm X, the use of the periodic updating of the key will counteract the attack to a certain extent by using U-cycle updating of the key, where the shorter the updating period, the higher the security X\({}_{s}\) of the encryption algorithm X. Then, the objective \(BF\) (benefit function) can be expressed as  
\[