Data storage method, apparatus, and device, and readable storage medium
A data storage method, apparatus, and device, and a readable storage medium. The method includes: after a random access memory is powered on, obtaining target data to be stored in a fixed storage address of the random access memory; determining a target transmission mode from a bit value change transmission mode and a bit value fixed transmission mode, wherein the target transmission mode is different from a historical transmission mode determined after the random access memory is powered on last time; and transmitting the target data from and to the random access memory according to the target transmission mode. The method can prevent data from being stolen after power-down of the target data, and guarantees the data security.
1. A data storage method, comprising:
after a random access memory is powered on, acquiring target data to be stored in a fixed storage address in the random access memory;
determining a target transmission mode from a bit value change transmission mode and a bit value fixed transmission mode; the target transmission mode being different from a historical transmission mode determined after the random access memory is powered on last time; and
transmitting the target data from and to the random access memory according to the target transmission mode;
wherein the step of determining the target transmission mode from the bit value change transmission mode and the bit value fixed transmission mode comprises:
acquiring a power-on frequency of the random access memory;
when the power-on frequency is an even number, determining the bit value change transmission mode as the target transmission mode; and
when the power-on frequency is an odd number, determining the bit value fixed transmission mode as the target transmission mode.
2. The data storage method according to claim 1 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing bit flipping on a bit value of the target data to obtain a flipped bit stream corresponding to the target data;
transmitting the flipped bit stream to the random access memory;
reading the flipped bit stream from the random access memory; and
performing bit flipping on the flipped bit stream to obtain the target data.
3. The data storage method according to claim 1 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing shift processing on the bit stream of the target data to obtain a shifted bit stream corresponding to the target data;
transmitting the shifted bit stream to the random access memory;
reading the shifted bit stream from the random access memory; and
performing shift recovery on the shifted bit stream to obtain the target data.
4. The data storage method according to claim 1 , wherein when the target transmission mode is the bit value fixed transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
transmitting the bit stream of the target data to the random access memory; and
reading the bit stream from the random access memory to obtain the target data.
5. The data storage method according to claim 1 , wherein the step of acquiring the power-on frequency of the random access memory comprises:
acquiring the power-on frequency from an upper computer.
6. The data storage method according to claim 1 , wherein the step of acquiring target data to be stored in a fixed storage address in the random access memory comprises:
acquiring model parameters of a deep learning model from the upper computer; and
taking the model parameters as the target data.
7. A data storage device, comprising:
a memory configured to store a computer program; and
a processor configured to, when executing the computer program, implement operations as follows:
after a random access memory is powered on, acquiring target data to be stored in a fixed storage address in the random access memory;
determining a target transmission mode from a bit value change transmission mode and a bit value fixed transmission mode; the target transmission mode being different from a historical transmission mode determined after the random access memory is powered on last time; and
transmitting the target data from and to the random access memory according to the target transmission mode;
wherein the step of determining the target transmission mode from the bit value change transmission mode and the bit value fixed transmission mode comprises:
acquiring a power-on frequency of the random access memory;
when the power-on frequency is an even number, determining the bit value change transmission mode as the target transmission mode; and
when the power-on frequency is an odd number, determining the bit value fixed transmission mode as the target transmission mode.
8. A non-transitory computer-readable storage medium, storing a computer program that is executed executable by a processor, and upon execution by the processor, is configured to cause the processor to implement operations as follows:
after a random access memory is powered on, acquiring target data to be stored in a fixed storage address in the random access memory;
determining a target transmission mode from a bit value change transmission mode and a bit value fixed transmission mode; the target transmission mode being different from a historical transmission mode determined after the random access memory is powered on last time; and
transmitting the target data from and to the random access memory according to the target transmission mode;
wherein the step of determining the target transmission mode from the bit value change transmission mode and the bit value fixed transmission mode comprises:
acquiring a power-on frequency of the random access memory;
when the power-on frequency is an even number, determining the bit value change transmission mode as the target transmission mode; and
when the power-on frequency is an odd number, determining the bit value fixed transmission mode as the target transmission mode.
9. The device according to claim 7 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing bit flipping on a bit value of the target data to obtain a flipped bit stream corresponding to the target data;
transmitting the flipped bit stream to the random access memory;
reading the flipped bit stream from the random access memory; and
performing bit flipping on the flipped bit stream to obtain the target data.
10. The device according to claim 7 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing shift processing on the bit stream of the target data to obtain a shifted bit stream corresponding to the target data;
transmitting the shifted bit stream to the random access memory;
reading the shifted bit stream from the random access memory; and
performing shift recovery on the shifted bit stream to obtain the target data.
11. The device according to claim 7 , wherein when the target transmission mode is the bit value fixed transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
transmitting the bit stream of the target data to the random access memory; and
reading the bit stream from the random access memory to obtain the target data.
12. The device according to claim 7 , wherein the step of acquiring the power-on frequency of the random access memory comprises:
acquiring the power-on frequency from an upper computer.
13. The device according to claim 7 , wherein the step of acquiring target data to be stored in a fixed storage address in the random access memory comprises:
acquiring model parameters of a deep learning model from the upper computer; and
taking the model parameters as the target data.
14. The medium according to claim 8 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing bit flipping on a bit value of the target data to obtain a flipped bit stream corresponding to the target data;
transmitting the flipped bit stream to the random access memory;
reading the flipped bit stream from the random access memory; and
performing bit flipping on the flipped bit stream to obtain the target data.
15. The medium according to claim 8 , wherein when the target transmission mode is the bit value change transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
performing shift processing on the bit stream of the target data to obtain a shifted bit stream corresponding to the target data;
transmitting the shifted bit stream to the random access memory;
reading the shifted bit stream from the random access memory; and
performing shift recovery on the shifted bit stream to obtain the target data.
16. The medium according to claim 8 , wherein when the target transmission mode is the bit value fixed transmission mode, the step of transmitting the target data from and to the random access memory according to the target transmission mode comprises:
transmitting the bit stream of the target data to the random access memory; and
reading the bit stream from the random access memory to obtain the target data.
17. The medium according to claim 8 , wherein the step of acquiring target data to be stored in a fixed storage address in the random access memory comprises:
acquiring model parameters of a deep learning model from the upper computer; and
taking the model parameters as the target data.