Information security data storage method and system

Abstract

The invention discloses an information security data storage method and system, and relates to the technical field of electronic information.The method comprises the steps that complete data D collected by an intelligent household appliance is transmitted to a cloud server to be preprocessed, data fragmentation is carried out through XOR XOR encryption, an SHA-512 hash function and a large prime number modulo algorithm, a plurality of sub-data pieces Dz are generated, and the sub-data pieces Dz are stored in the cloud server; the storage position L of each sub-data piece Dz is calculated by combining the local system time T, the equipment secret key K, the true random number R and other information of the intelligent household electrical appliance equipment; and on the basis of the storage position, carrying out dynamic encryption transformation processing on the sub-data pieces to form encrypted data E, and distributing and storing the encrypted data E into a plurality of intelligent household appliances, thereby constructing a multi-source heterogeneous dynamic random distributed data invisible storage system. According to the method, the risk of single-point leakage is effectively reduced, and the physical distribution security and concealment of the data on the equipment level are improved.

Description

Technical Field

[0001] The present invention relates to the field of electronic information technology, and in particular to a method and system for secure information data storage. Background Art

[0002] Information security falls under the sub-field of network information security storage, specifically distributed encrypted storage and dynamic hidden distribution methods applied in smart home systems. In current smart home scenarios, devices such as smart speakers, cameras, door locks, refrigerators, and lighting systems continuously collect highly sensitive data such as user voice, images, behavioral trajectories, and usage preferences. The storage security of this data, whether in the cloud or locally, directly impacts user privacy protection and system resilience against attacks. Therefore, improving data storage's anti-attack capabilities, distributed security, and dynamic concealment without relying on specialized encryption hardware has become a key research area in smart home information security.

[0003] Currently, existing smart home information storage solutions suffer from common flaws such as a single storage structure, centralized data, and vulnerability to attacks. Most systems upload smart device data to a cloud platform for centralized storage. While this facilitates management, a cloud server attack can lead to large-scale sensitive data leaks. Furthermore, while some local storage solutions can avoid cloud-based reliance, the lack of dynamic data sharding or encrypted distribution means attackers only need to breach a single device to access the complete data. Furthermore, existing systems lack self-detection and risk-driven data migration mechanisms after storage, making it impossible to automatically adjust data layout based on device risk status, creating security blind spots. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and system for storing secure information data, which solves the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: comprising the following steps:

[0006] S1. Build a cloud server and integrate it with smart home appliances. The complete data D collected by the smart home appliances is transmitted to the cloud server. In the cloud server, the complete data D is split into several sub-data slices Dz, and the storage information of the smart home appliances is extracted.

[0007] S2. Calculate the storage location L based on the storage information, extract the sub-data slice Dz and the storage location L in combination with the storage information, perform encryption transformation on the stored data, obtain the encrypted data E after the encryption transformation, and perform dynamic invisible storage and encryption transformation on the sub-data slice Dz;

[0008] S3. During data storage, the storage status data of the smart home appliance is regularly detected and extracted. Based on the storage status data, the data migration priority Q is calculated. A migration threshold F1 is set and compared with the migration priority Q to evaluate the migration status. The sub-data slice Dz stored in the source smart home appliance is deleted.

[0009] S4. When the user requests data, several smart home appliances collaborate to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D.

[0010] Preferably, S1 includes S11 and S12;

[0011] S11. Build a cloud server to integrate smart home appliances with the cloud server via a WIFI wireless communication network using the secure transmission protocol TLS 1.3, and number the storage units of the smart home appliances from 0 to M-1.

[0012] Then, complete data D is collected in real time through smart home appliances and transmitted to a cloud server every 24 hours. In the cloud server, XOR encryption, SHA-512 hashing, and large prime number modulo technology are used to construct a data sharding formula to shard the complete data D of the video data, splitting the complete data D into several sub-data slices Dz.

[0013] The sub-data slice Dz is processed and output by the following data sharding formula:

[0014]

[0015] Where Dz i Represents the sub-data slice of the i-th shard of the complete data D, S i represents the random shard seed of the i-th shard, H SHA-512 Represents the SHA-512 hash function, which outputs a fixed 512-bit random number. Indicates XOR encryption operation, mod indicates modulus, and P indicates a large prime number;

[0016] S12, after splitting the complete data D, extracting the stored information in real time through the built-in device of the smart home appliance; the stored information includes the local system time T of the jth smart home appliance of the smart home appliance j , the device key K of the j-th smart home appliance j , the storage occupancy rate U of the i-th smart home appliance j , the true random number R of the j-th smart home appliance j and the total storage space capacity M of smart home appliances;

[0017] And the local system time T of the jth smart home appliance device j Convert to string format.

[0018] Preferably, S2 includes S21 and S22;

[0019] S21, extracting the local system time T of the jth smart home appliance from the stored information j , the device key K of the j-th smart home appliance j and the true random number R of the j-th smart home appliance j , dynamically calculate and output the sub-data piece Dz and then store it in the storage location L on the smart home appliance. Based on the output storage location L, the sub-data piece Dz is sent from the cloud server to different smart home appliances for dynamic invisible storage;

[0020] The storage location L is calculated and outputted by the following algorithm formula;

[0021]

[0022] Where, L Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i At the storage location of the jth smart home appliance, H SHA-256 Represents the SHA-256 hash function, which outputs a fixed 256-bit random number.

[0023] Preferably, S22, based on the sub-data slice Dz of the i-th slice of the complete data D i At the storage location L of the jth smart home appliance Dzi，j , combined with the device key K of the j-th smart home appliance j Perform encryption transformation, obtain the encrypted data E after encryption transformation, and store it in the corresponding smart home appliance;

[0024] The encrypted data E is encrypted using the following formula:

[0025]

[0026] Where, E Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i The encrypted data E after encryption transformation in the j-th smart home appliance.

[0027] Preferably, S3 includes S31, S32 and S33;

[0028] S31. During the data storage process, the intrusion detection system (IDS) and operation monitoring log of the smart home appliance are run in real time through the API application program interface to detect the storage status data of the smart home appliance in the past 24 hours;

[0029] The stored status data includes the number of abnormal events detected for the jth smart home appliance device in the past 24 hours (Nalerts) j 、CPU load of the jth smart home appliance is abnormal to normal j , the CPU computing power C of the jth smart home appliance j , the network transmission rate N of the jth smart home appliance j and the storage utilization rate U of the jth smart home appliance j ;

[0030] Based on the storage status data, the migration priority Q is calculated and output to measure the data integrity D of the i-th shard sub-data shard Dz i Migration situation;

[0031] The migration priority Q is calculated and output by the following algorithm formula:

[0032]

[0033] Where Q Di represents the migration priority of the sub-data slice of the i-th slice of the complete data D, log represents the logarithmic function, 24 represents the detection time, △t j Indicates the last migration time interval of the j-th smart home appliance.

[0034] Preferably, S32, based on the user's smart home appliance type, a migration threshold F1 is set, and then the migration threshold F1 is compared with the migration priority Q of the sub-data slice of the i-th slice of the complete data D. Di ,Migration comparative evaluation, judges the implementation of the migration strategy, the specific evaluation contents are as follows;

[0035] When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the migration threshold F1 is exceeded, it indicates that the current smart home appliance storage is abnormal, and the data migration strategy is triggered;

[0036] When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the value is less than or equal to the migration threshold F1, it indicates that the storage of the current smart home appliance is normal and no migration is required.

[0037] Preferably, S33, the data migration strategy uses the secure transmission protocol TLS1.3 to transfer the sub-data slice Dz of the i-th slice of the complete data D of the current smart device to the i , transmitted to the cloud server, and then in the cloud server, the storage location L is recalculated and encrypted, and the sub-data slice Dz of the i-th slice of the complete data D is converted to iStore it in the new storage location L, and use the secure erase method to delete the sub-data slice Dz of the i-th slice of the complete data D of the source smart home appliance device before and after completion. i ;

[0038] Secure erase method, using triple write method to erase the complete data D stored in the source smart home appliance after migration, and the sub-data slice Dz of the i-th slice i ;

[0039] The first time, write all 0s to clear the data flag bit;

[0040] The second time, all 1s are written to overwrite the boundary instruction;

[0041] The third time, random data is written to prevent pattern inference and reconstruction analysis;

[0042] Finally, perform another check to rewrite the integrity, delete the storage table entries, and refresh the cache and persistent logs.

[0043] Preferably, S4 includes S41 and S42;

[0044] S41. When the user requests data, the encrypted data E stored in all smart home appliances and the device key K of the jth smart home appliance must be j , perform key splicing and calculate the decryption key KD;

[0045] The decryption key KD is calculated and output by the following algorithm formula;

[0046]

[0047] Where N represents the total number of smart home appliances. It represents the XOR encryption operation summation symbol, and the XOR encryption operation will be performed sequentially from the first smart home appliance to the Nth smart home appliance.

[0048] Preferably, S42, data decryption is performed based on the decryption key KD and the original key Kor; the splicing formula is:

[0049]

[0050] In the formula, Drecovered represents the decrypted data, Koriginal represents the original key, The logical symbol represents if and only if. The formula indicates that the complete data D can be successfully recovered only when the calculated decryption key KD is completely consistent with the original key Koriginal.

[0051] If the calculated decryption key KD is the same as the original key Koriginal, the data is recovered;

[0052] If the calculated decryption key KD is different from the original key Koriginal, the decryption fails and the data remains secure.

[0053] An information security data storage system includes a data sharding module, a data invisible storage and dynamic encryption module, a data migration module, and a data access and joint decryption module;

[0054] The data sharding module builds a cloud server and integrates it with smart home appliances. It transmits the complete data D collected by smart home appliances to the cloud server, splits the complete data D into several sub-data slices Dz in the cloud server, and extracts the storage information of the smart home appliances.

[0055] The data invisible storage and dynamic encryption module calculates the storage location L based on the storage information, extracts the sub-data slice Dz and the storage location L and combines the storage information, performs encryption transformation on the stored data, obtains the encrypted data E after encryption transformation, and performs dynamic invisible storage and encryption transformation on the sub-data slice Dz;

[0056] The data migration module periodically detects and extracts storage status data of smart home appliances during data storage. Based on the storage status data, it calculates the data migration priority Q, sets the migration threshold F1 and the migration priority Q for migration comparison and evaluation, determines the migration status, and deletes the source storage sub-data slice Dz.

[0057] The data access and joint decryption module works together with several smart home appliances to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D when the user requests data.

[0058] The present invention provides a method and system for secure information data storage, which has the following beneficial effects:

[0059] (1) This method transmits the complete data D collected by smart home appliances to a cloud server for preprocessing, and uses XOR encryption, SHA-512 hash function and large prime number modulus algorithm to shard the data to generate multiple sub-data slices Dz. Combined with the local system time T, device key K, true random number R and other information of the smart home appliance, the storage location L of each sub-data slice Dz is calculated. Based on the storage location, the sub-data slice is dynamically encrypted and transformed to form encrypted data E, which is distributed and stored in multiple smart home appliances, thereby constructing a multi-source heterogeneous, dynamic random distributed data hidden storage system. This method effectively reduces the risk of single-point leakage and improves the physical distribution security and concealment of data at the device level.

[0060] (2) This method uses the intrusion detection system (IDS) and operation monitoring logs based on smart home appliances to extract the storage status data of each smart home appliance in the past 24 hours in real time. The migration priority Q corresponding to each sub-data slice Dz is further calculated by combining the detection time with the time difference between the last migration, and is dynamically compared with the migration threshold F1 set by the user to accurately determine whether to trigger the migration operation. When migration is required, the sub-data slice Dz is securely transmitted to the cloud through the TLS1.3 security protocol, and the storage location is reallocated and distributed to the new device. At the same time, the data on the original device is completely cleared using the three-way erasure method. The above process realizes the dynamic risk assessment and secure adaptive migration of the data storage path, greatly enhancing the anti-attack and operational resilience of the storage system.

[0061] (3) This method uses a multi-device collaborative decryption mechanism when a user requests access to data. The encrypted data E stored in each smart home appliance is concatenated with its corresponding device key K to form a joint decryption key KD, which is then compared and verified with the original key Koriginal. Only when all device keys participate in the calculation and the concatenation logic is correct can the complete data D be successfully recovered; otherwise, the data will remain undecryptable. This mechanism makes full use of the device distribution characteristics and the key separation principle to prevent attackers from attempting to decrypt data through a single device or a small amount of data, thereby ensuring the integrity and confidentiality of the data recovery process and significantly enhancing the security control capabilities of user data access. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a schematic diagram of the steps of a method for secure information data storage according to the present invention;

[0063] Figure 2 This is a flow chart of an information security data storage system according to the present invention;

[0064] Figure 3 This is a data flow diagram of a method for storing secure information data according to the present invention;

[0065] Figure 4 This is a schematic diagram of a method for storing secure information data according to the present invention. DETAILED DESCRIPTION

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0067] Example 1

[0068] See also Figure 1 、 Figure 3 and Figure 4 The present invention provides a method for storing secure information data. To achieve the above objectives, the present invention is implemented through the following technical solutions: comprising the following steps:

[0069] S1. Build a cloud server and integrate it with smart home appliances. The complete data D collected by the smart home appliances is transmitted to the cloud server. In the cloud server, the complete data D is split into several sub-data slices Dz, and the storage information of the smart home appliances is extracted.

[0070] S2. Calculate the storage location L based on the storage information, extract the sub-data slice Dz and the storage location L in combination with the storage information, perform encryption transformation on the stored data, obtain the encrypted data E after the encryption transformation, and perform dynamic invisible storage and encryption transformation on the sub-data slice Dz;

[0071] S3. During data storage, the storage status data of the smart home appliance is regularly detected and extracted. Based on the storage status data, the data migration priority Q is calculated. A migration threshold F1 is set and compared with the migration priority Q to evaluate the migration status. The sub-data slice Dz stored in the source smart home appliance is deleted.

[0072] S4. When the user requests data, several smart home appliances collaborate to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D.

[0073] In this embodiment, the method achieves secure data storage, dynamic migration, and efficient decryption through the collaborative work of a cloud server and smart home appliances. During data storage, the smart home appliance first collects complete data D and uploads it to the cloud server. The server then fragments the complete data D into multiple sub-data slices Dz and calculates the storage location L based on the device's storage information. Subsequently, the sub-data slices Dz are encrypted to form encrypted data E, which is then distributed and stored across multiple smart home appliances based on a dynamic hidden storage mechanism, thereby improving data security and confidentiality. During data storage, the system periodically extracts storage status data from smart home appliances and calculates a data migration priority Q based on this data. A migration threshold F1 is also set and compared with the migration priority Q to determine whether data migration is necessary. This ensures that data can be promptly transferred to other devices when device storage pressure becomes excessive or security risks increase. The sub-data slices Dz on the original device are completely deleted, further enhancing the dynamic security and sustainability of data storage. During the data recovery phase, when a user requests data, multiple smart home appliances collaboratively calculate the decryption key KD and generate a complete key through key splicing. This key is ultimately used to decrypt the data and restore the complete data D. This method not only ensures highly encrypted data storage, but also improves the system's anti-attack capabilities and data privacy protection through dynamic migration and distributed storage strategies, avoiding the risk of single-point storage leaks. It also strengthens access control through a collaborative key management mechanism, ensuring that data can only be decrypted and accessed with authorized collaboration from multiple devices, significantly improving the data storage security and privacy of smart home appliances and the stability of the overall system.

[0074] Example 2

[0075] See also Figure 1 、 Figure 3 and Figure 4 ,Specifically: S1 includes S11 and S12;

[0076] S11. Build a cloud server to integrate smart home appliances with the cloud server via a WIFI wireless communication network using the secure transmission protocol TLS 1.3, and number the storage units of the smart home appliances from 0 to M-1.

[0077] Then, the complete data D (as shown in Table 1) is collected in real time through smart home appliances and transmitted to the cloud server every 24 hours. In the cloud server, XOR encryption, SHA-512 hashing and large prime number modulo technology are used to construct a data sharding formula to shard the complete data D of the video data and split the complete data D into several sub-data slices Dz.

[0078] The sub-data slice Dz is processed and output by the following data sharding formula:

[0079]

[0080] Where Dz i Represents the sub-data slice of the i-th shard of the complete data D, S i The random shard seed of the i-th shard is obtained by taking a random number and automatically obtaining it through the random number generator TRNG inside the smart home appliance. SHA-512 Represents the SHA-512 hash function, which outputs a fixed 512-bit random number. Represents XOR encryption operation, mod represents modulus, and the formula represents the operation of taking the modulus P of the hash calculation result, which is used to limit the value range of the data piece and enhance security. P represents a large prime number, which is used to select a sufficiently large prime number P for modulus to ensure that the data piece is not repeated. For example, if P=2 is selected 521 -1 (prime number), improves security,

[0081] XOR encryption operation ⊕: used to increase data obfuscation, so that even if the attacker obtains the sub-data slice Dz of the i-th slice of the complete data D i , it is also impossible to infer the complete data D;

[0082] Only the random shard seed S of the i-th shard i Only when you know it, you can decrypt the data;

[0083] Table 1: D type table of complete data collected by smart home appliances

[0084] Smart home appliances Complete data D Smart speakers Store user voice data to prevent a single device from leaking user conversation content Smart Camera Protect surveillance video, even if the camera is attacked, hackers cannot obtain the complete video Smart door locks Stores family members' entry and exit records to prevent intruders from stealing family entry and exit information Smart refrigerator Store shopping records and food preference data to prevent data leakage to third parties Smart lighting system Records lighting usage habits in the house to prevent attackers from analyzing home activity patterns

[0085] S12, after splitting the complete data D, extracting the stored information in real time through the built-in device of the smart home appliance; the stored information includes the local system time T of the jth smart home appliance of the smart home appliance j , the device key K of the j-th smart home appliance j , the storage occupancy rate U of the i-th smart home appliance j , the true random number R of the j-th smart home appliance j and the total storage space capacity M of smart home appliances;

[0086] And the local system time T of the jth smart home appliance device j Convert to string format

[0087] Where: local system time T of the jth smart home appliance j Extract through the local system time of smart home appliance devices;

[0088] The device key K of the j-th smart home appliance j Generated through the security chip TPM / TEE of smart home appliances;

[0089] The total storage space capacity M of smart home appliances and the storage occupancy rate U of the i-th smart home appliance j Obtain the current storage usage through the smart home appliance file system API;

[0090] The true random number R of the j-th smart home appliance device j Generated by the true random number generator TRNG inside the smart home.

[0091] In this embodiment, the method establishes a secure connection with smart home appliances via a Wi-Fi wireless communication network through a cloud server and employs the TLS 1.3 secure transmission protocol to ensure confidentiality and integrity of data during transmission. All storage units in smart home appliances are numbered to facilitate efficient data sharding and management. Smart home appliances periodically collect complete data D and shard it using XOR encryption, SHA-512 hashing, and large prime number modulo techniques. Multiple sub-data segments Dz are generated using a data sharding formula to enhance data randomness and security. Even if some of the data segments are leaked, attackers cannot infer the complete data content. Furthermore, after data sharding, the smart home appliance extracts stored information in real time, including the local system time Tj, device key Kj, storage utilization Uj, true random number Rj, and total storage space M. This critical information is obtained through the device's TPM / TEE security chip, true random number generator (TRNG), and file system API, ensuring data authenticity and immutability. By converting the local system time Tj into a string format, the uniformity and traceability of data identification are improved. This method not only improves the data storage security of smart home appliances, but also significantly reduces the risk of data leakage through data sharding, XOR encryption and distributed storage strategies, while preventing hackers from obtaining complete data through a single device. In addition, through dynamic monitoring and intelligent management of device storage status, the utilization efficiency of storage resources is improved, the stability of the system and the ability to protect data privacy are enhanced, providing a more efficient and secure solution for the secure storage and management of smart home data.

[0092] Example 3

[0093] See also Figure 1 、 Figure 3 and Figure 4 , specifically: S2 includes S21 and S22;

[0094] S21, extracting the local system time T of the jth smart home appliance from the stored information j , the device key K of the j-th smart home appliancej and the true random number R of the j-th smart home appliance j , dynamically calculate and output the sub-data piece Dz and then store it in the storage location L on the smart home appliance. Based on the output storage location L, the sub-data piece Dz is sent from the cloud server to different smart home appliances for dynamic invisible storage;

[0095] The storage location L is calculated and outputted by the following algorithm formula;

[0096]

[0097] Where, L Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i At the storage location of the jth smart home appliance, H SHA-256 represents the SHA-256 hash function, which outputs a fixed 256-bit random number to ensure the security of the data storage location L. Mod M in the formula means that the storage location L is always within the available space of the smart home device;

[0098] The significance of the formula is that the local system time T of the j-th smart home appliance device j and the true random number R of the j-th smart home appliance j It will keep changing. Even if the current storage location is found, it is impossible to predict where the data will be stored in the future. At the same time, the storage location depends on the device key K of the j-th smart home appliance device. j , attackers cannot restore the storage address on unauthorized devices;

[0099] Specific example,

[0100] Assume that the total storage capacity M of the smart home appliance is 1000 storage blocks.

[0101] The local system time T of the jth smart home appliance j It is converted to string format and generates "1710888831";

[0102] The device key K of the j-th smart home appliance j Generates "87912348712984712394712394";

[0103] The true random number R of the j-th smart home appliance device j Produced as "32048712398471298347192837"

[0104] The final complete data D is the sub-data slice Dz of the i-th slice i The storage location L of the jth smart home appliance device Dzi，jThe output result is 49, which means the sub-data slice Dz of the i-th slice of the complete data D i Stored in the 49th storage block of the smart home appliance device.

[0105] S22, sub-data slice Dz based on the i-th slice of the complete data D i At the storage location L of the jth smart home appliance Dzi，j , combined with the device key K of the j-th smart home appliance j Perform encryption transformation, obtain the encrypted data E after encryption transformation, and store it in the corresponding smart home appliance;

[0106] The encrypted data E is encrypted using the following formula:

[0107]

[0108] Where, E Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i The encrypted data E after encryption transformation in the j-th smart home appliance.

[0109] In this embodiment, the method extracts the local system time T of the jth smart home appliance in the stored information. j , the device key K of the j-th smart home appliance j and the true random number R of the j-th smart home appliance j , and calculate the sub-data slice Dz of the i-th slice of the complete data D based on these dynamic variables i At the storage location L of the jth smart home appliance Dzi，j The storage location is calculated by the SHA-256 hash function, making the data storage address random and unpredictable. Even if an attacker knows the current storage location, he cannot predict the future data storage location. At the same time, since the calculation of the storage location depends on the device key K of the j-th smart home appliance j , ensuring that unauthorized devices cannot reproduce the storage address, thereby further enhancing data security. Subsequently, the cloud server will store the sub-data slice Dz of the i-th shard of the complete data D according to the calculated storage location L. iDynamically distribute to different smart home appliances to achieve invisible storage and prevent a single device from becoming an attack target. Based on the storage location L, combined with the device key K, the stored data is encrypted and transformed to generate encrypted data E, which is stored in the corresponding smart home appliance. Through this encryption mechanism, even if an attacker obtains the stored data, it cannot be decrypted on an unauthorized device, further improving data protection capabilities. The implementation of this method effectively realizes distributed dynamic storage and invisible encryption among smart home appliances, improves data security, privacy and anti-attack capabilities, while optimizing storage resource allocation, improving system stability and reliability, and providing an efficient and secure solution for smart home data storage.

[0110] Example 4

[0111] See also Figure 1 、 Figure 3 and Figure 4 , specifically: S3 includes S31, S32 and S33;

[0112] S31. During the data storage process, the intrusion detection system (IDS) and operation monitoring log of the smart home appliance are run in real time through the API application program interface to detect the storage status data of the smart home appliance in the past 24 hours;

[0113] The stored status data includes the number of abnormal events detected for the jth smart home appliance device in the past 24 hours (Nalerts) j , The CPU load of the jth smart home appliance is abnormal to normal j , the CPU computing power C of the jth smart home appliance j , the network transmission rate N of the jth smart home appliance j and the storage utilization rate U of the jth smart home appliance j ;

[0114] Based on the storage status data, the migration priority Q is calculated and output to measure the data integrity D of the i-th shard sub-data shard Dz i Migration situation;

[0115] The migration priority Q is calculated and output by the following algorithm formula:

[0116]

[0117] Where Q Di represents the migration priority of the sub-data slice of the i-th shard of the complete data D, log represents the logarithmic function, which is used to smooth the data to prevent the score distortion caused by excessive outliers, 24 represents the detection time, △t j represents the last migration time interval of the j-th smart home appliance,

[0118] Represents the anomaly detection score.

[0119] S32: Set the migration threshold F1 based on the type of smart home appliance, and then compare the migration threshold F1 with the migration priority Q of the sub-data slice of the i-th slice of the complete data D. Di ,Migration comparative evaluation, judges the implementation of the migration strategy, the specific evaluation contents are as follows;

[0120] When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the migration threshold F1 is exceeded, it indicates that the current smart home appliance storage is abnormal, and the data migration strategy is triggered;

[0121] When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the value is less than or equal to the migration threshold F1, it indicates that the storage of the current smart home appliance is normal and no migration is required.

[0122] S33, data migration strategy uses the secure transmission protocol TLS1.3 to transfer the complete data D of the current smart device to the sub-data slice Dz of the i-th slice i , transmitted to the cloud server, and then in the cloud server, the storage location L is recalculated and encrypted, and the sub-data slice Dz of the i-th slice of the complete data D is converted to i Store it in the new storage location L, and use the secure erase method to delete the sub-data slice Dz of the i-th slice of the complete data D of the source smart home appliance device before and after completion. i ;

[0123] Secure erase method, using triple write method to erase the complete data D stored in the source smart home appliance after migration, and the sub-data slice Dz of the i-th slice i ;

[0124] The first time, write all 0s to clear the data flag bit;

[0125] The second time, all 1s are written to overwrite the boundary instruction;

[0126] The third time, random data is written to prevent pattern inference and reconstruction analysis;

[0127] Finally, perform another check to rewrite the integrity, delete the storage table entries, and refresh the cache and persistent logs.

[0128] In this embodiment, the method extracts the storage status data in the past 24 hours and calculates the migration priority Q of the sub-data slice based on these parameters. The anomaly detection score is smoothed by the logarithmic function log to prevent the influence of outliers on the score, making the calculation of the migration priority Q more stable. At the same time, the user can set the migration threshold F1 according to the type of smart home appliance and compare it with the calculated migration priority Q. Di Perform comparative evaluation, when migration priority Q Di When F1 is exceeded, the data migration strategy is triggered, otherwise the data remains unchanged. At the same time, data migration uses the TLS1.3 secure transmission protocol to ensure transmission security, and recalculates the storage location L and performs encryption transformation on the cloud server to ensure the privacy and security of the stored data. At the same time, after the migration is completed, the data on the source device is securely erased using a three-write method, including writing all 0s, all 1s, and random data to prevent data recovery. Finally, the original storage traces are completely eliminated through integrity verification, deletion of storage table items, refreshing of caches, and persistent logs. Through the implementation of this method, not only the storage security of smart home appliances is improved, and data is prevented from being illegally stolen or tampered with, but also the reliability of data storage is improved, ensuring that data can be migrated and protected in a timely manner under abnormal circumstances, thereby optimizing the overall security performance and data management capabilities of the smart home system.

[0129] Example 5

[0130] See also Figure 1 、 Figure 3 and Figure 4 , specifically: S4 includes S41 and S42;

[0131] S41. When the user requests data, the encrypted data E stored in all smart home appliances and the device key K of the jth smart home appliance must be j , perform key splicing and calculate the decryption key KD;

[0132] The decryption key KD is calculated and output by the following algorithm formula;

[0133]

[0134] Where N represents the total number of smart home appliances. It represents the XOR encryption operation summation symbol, and the XOR encryption operation will be performed sequentially from the first smart home appliance to the Nth smart home appliance.

[0135] S42. Decrypt the data based on the decryption key KD and the original key Kor; the splicing formula is:

[0136]

[0137] In the formula, Drecovered represents the decrypted data, Koriginal represents the original key, The logical symbol represents if and only if. The formula indicates that the complete data D can be successfully recovered only when the calculated decryption key KD is completely consistent with the original key Koriginal.

[0138] If the calculated decryption key KD is the same as the original key Koriginal, the data is recovered;

[0139] If the calculated decryption key KD is different from the original key Koriginal, the decryption fails and the data remains secure.

[0140] In this embodiment, the method realizes the secure decryption and recovery of data by collaboratively calculating the decryption key KD through smart home appliances. At the same time, when the user requests data, the encrypted data E stored in all smart home appliances is extracted, and the device key KD of each smart home appliance is used to decrypt the data. j Key concatenation is performed, and the decryption key KD is gradually calculated through XOR operations. This method ensures the dynamic and distributed nature of the decryption key, making it difficult for hackers to obtain the complete decryption key even if some devices are attacked. The decryption key KD is then compared with the original key Kor. If the two are identical, decryption successfully recovers the complete data D; if they are inconsistent, decryption fails and the data remains encrypted, ensuring information security. Through distributed key concatenation and a strict key matching mechanism, this method enables secure data access in smart home environments, prevents single-point attacks, improves data privacy protection, and enhances the system's anti-attack and data recovery reliability, thereby significantly improving the security and stability of smart home devices during data storage and access.

[0141] Example 6

[0142] See also Figure 1 and Figure 2 , an information security data storage system, including a data sharding module, a data invisible storage and dynamic encryption module, a data migration module and a data access and joint decryption module;

[0143] The data sharding module builds a cloud server and integrates it with smart home appliances. It transmits the complete data D collected by smart home appliances to the cloud server, splits the complete data D into several sub-data slices Dz in the cloud server, and extracts the storage information of the smart home appliances.

[0144] The data invisible storage and dynamic encryption module calculates the storage location L based on the storage information, extracts the sub-data slice Dz and the storage location L and combines the storage information, performs encryption transformation on the stored data, obtains the encrypted data E after encryption transformation, and performs dynamic invisible storage and encryption transformation on the sub-data slice Dz;

[0145] The data migration module periodically detects and extracts storage status data of smart home appliances during data storage. Based on the storage status data, it calculates the data migration priority Q, sets the migration threshold F1 and the migration priority Q for migration comparison and evaluation, determines the migration status, and deletes the source storage sub-data slice Dz.

[0146] The data access and joint decryption module works together with several smart home appliances to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D when the user requests data.

[0147] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that various changes, modifications, substitutions, and alterations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for secure information data storage, characterized in that: The following steps are involved: S1. Build a cloud server and integrate it with smart home appliances. The complete data D collected by the smart home appliances is transmitted to the cloud server. In the cloud server, the complete data D is split into several sub-data slices Dz, and the storage information of the smart home appliances is extracted. S2. Calculate the storage location L based on the storage information, extract the sub-data slice Dz and the storage location L in combination with the storage information, perform encryption transformation on the stored data, obtain the encrypted data E after the encryption transformation, and perform dynamic invisible storage and encryption transformation on the sub-data slice Dz; S3. During data storage, the storage status data of the smart home appliance is regularly detected and extracted. Based on the storage status data, the data migration priority Q is calculated. A migration threshold F1 is set and compared with the migration priority Q to evaluate the migration status. The sub-data slice Dz stored in the source smart home appliance is deleted. S4. When the user requests data, several smart home appliances collaborate to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D.

2. A method for secure information data storage according to claim 1, characterized in that: S1 includes S11 and S12; S11. Build a cloud server to integrate smart home appliances with the cloud server via a WIFI wireless communication network using the secure transmission protocol TLS 1.3, and number the storage units of the smart home appliances from 0 to M-1. Then, complete data D is collected in real time through smart home appliances and transmitted to a cloud server every 24 hours. In the cloud server, XOR encryption, SHA-512 hashing, and large prime number modulo technology are used to construct a data sharding formula to shard the complete data D of the video data, splitting the complete data D into several sub-data slices Dz. The sub-data slice Dz is processed and output by the following data sharding formula: Where Dz i Represents the sub-data slice of the i-th shard of the complete data D, S i represents the random shard seed of the i-th shard, H SHA-512 Represents the SHA-512 hash function, which outputs a fixed 512-bit random number. Indicates XOR encryption operation, mod indicates modulus, and P indicates a large prime number; S12, after splitting the complete data D, extracting the stored information in real time through the built-in device of the smart home appliance; the stored information includes the local system time T of the jth smart home appliance of the smart home appliance j , the device key K of the j-th smart home appliance j , the storage occupancy rate U of the i-th smart home appliance j , the true random number R of the j-th smart home appliance j and the total storage space capacity M of smart home appliances; And the local system time T of the jth smart home appliance device j Convert to string format.

3. A method for secure information data storage according to claim 2, characterized in that: S2 includes S21 and S22; S21, extracting the local system time T of the jth smart home appliance from the stored information j , the device key K of the j-th smart home appliance j and the true random number R of the j-th smart home appliance j , dynamically calculate and output the sub-data piece Dz and then store it in the storage location L on the smart home appliance. Based on the output storage location L, the sub-data piece Dz is sent from the cloud server to different smart home appliances for dynamic invisible storage; The storage location L is calculated and outputted by the following algorithm formula; Where, L Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i At the storage location of the jth smart home appliance, H SHA-256 Represents the SHA-256 hash function, which outputs a fixed 256-bit random number.

4. A method for secure information data storage according to claim 3, characterized in that: S22, sub-data slice Dz based on the i-th slice of the complete data D i At the storage location L of the jth smart home appliance Dzi，j , combined with the device key K of the j-th smart home appliance j Perform encryption transformation, obtain the encrypted data E after encryption transformation, and store it in the corresponding smart home appliance; The encrypted data E is encrypted using the following formula: Where, E Dzi，j Represents the sub-data slice Dz of the i-th slice of the complete data D i The encrypted data E after encryption transformation in the j-th smart home appliance.

5. A method for secure information data storage according to claim 1, characterized in that: S3 includes S31, S32 and S33; S31. During the data storage process, the intrusion detection system (IDS) and operation monitoring log of the smart home appliance are run in real time through the API application program interface to detect the storage status data of the smart home appliance in the past 24 hours; The stored status data includes the number of abnormal events detected for the jth smart home appliance device in the past 24 hours (Nalerts) j , The CPU load of the jth smart home appliance is abnormal to normal j , the CPU computing power C of the jth smart home appliance j , the network transmission rate N of the jth smart home appliance j and the storage utilization rate U of the jth smart home appliance j ; Based on the storage status data, the migration priority Q is calculated and output to measure the data integrity D of the i-th shard sub-data shard Dz i Migration situation; The migration priority Q is calculated and output by the following algorithm formula: Where Q Di represents the migration priority of the sub-data slice of the i-th slice of the complete data D, log represents the logarithmic function, 24 represents the detection time, △t j Indicates the last migration time interval of the j-th smart home appliance.

6. A method for secure information data storage according to claim 5, characterized in that: S32: Set the migration threshold F1 based on the type of smart home appliance, and then compare the migration threshold F1 with the migration priority Q of the sub-data slice of the i-th slice of the complete data D. Di ,Migration comparative evaluation, judges the implementation of the migration strategy, the specific evaluation contents are as follows; When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the migration threshold F1 is exceeded, it indicates that the current smart home appliance storage is abnormal, and the data migration strategy is triggered; When the migration priority Q of the sub-data slice of the i-th shard of the complete data D Di When the value is less than or equal to the migration threshold F1, it indicates that the storage of the current smart home appliance is normal and no migration is required.

7. A method for secure information data storage according to claim 6, characterized in that: S33, data migration strategy uses the secure transmission protocol TLS1.3 to transfer the complete data D of the current smart device to the sub-data slice Dz of the i-th slice i , transmitted to the cloud server, and then in the cloud server, the storage location L is recalculated and encrypted, and the sub-data slice Dz of the i-th slice of the complete data D is converted to i Store it in the new storage location L, and use the secure erase method to delete the sub-data slice Dz of the i-th slice of the complete data D of the source smart home appliance device before and after completion. i ; Secure erase method, using triple write method to erase the complete data D stored in the source smart home appliance after migration. The sub-data slice Dz of the i-th slice i ; The first time, write all 0s to clear the data flag bit; The second time, all 1s are written to overwrite the boundary instruction; The third time, random data is written to prevent pattern inference and reconstruction analysis; Finally, perform another check to rewrite the integrity, delete the storage table entries, and refresh the cache and persistent logs.

8. A method for secure information data storage according to claim 1, characterized in that: S4 includes S41 and S42; S41. When the user requests data, the encrypted data E stored in all smart home appliances and the device key K of the jth smart home appliance must be j , perform key splicing and calculate the decryption key KD; The decryption key KD is calculated and output by the following algorithm formula; Where N represents the total number of smart home appliances. It represents the XOR encryption operation summation symbol, and the XOR encryption operation will be performed sequentially from the first smart home appliance to the Nth smart home appliance.

9. A method for secure information data storage according to claim 8, characterized in that: S42, decrypting the data based on the decryption key KD and the original key Kor; The splicing formula is: In the formula, Drecovered represents the decrypted data, Koriginal represents the original key, The logical symbol represents if and only if. The formula indicates that the complete data D can be successfully recovered only when the calculated decryption key KD is completely consistent with the original key Koriginal. If the calculated decryption key KD is the same as the original key Koriginal, the data is recovered; If the calculated decryption key KD is different from the original key Koriginal, the decryption fails and the data remains secure.

10. An information security data storage system, applied to an information security data storage method according to any one of claims 1 to 9, characterized in that: It includes data sharding module, data invisible storage and dynamic encryption module, data migration module and data access and joint decryption module; The data sharding module builds a cloud server and integrates it with smart home appliances. It transmits the complete data D collected by smart home appliances to the cloud server, splits the complete data D into several sub-data slices Dz in the cloud server, and extracts the storage information of the smart home appliances. The data invisible storage and dynamic encryption module calculates the storage location L based on the storage information, extracts the sub-data slice Dz and the storage location L and combines the storage information, performs encryption transformation on the stored data, obtains the encrypted data E after encryption transformation, and performs dynamic invisible storage and encryption transformation on the sub-data slice Dz; The data migration module periodically detects and extracts storage status data of smart home appliances during data storage. Based on the storage status data, it calculates the data migration priority Q, sets the migration threshold F1 and the migration priority Q for migration comparison and evaluation, determines the migration status, and deletes the source storage sub-data slice Dz. The data access and joint decryption module works together with several smart home appliances to perform key splicing, calculate the decryption key KD, and decrypt the data based on the decryption key KD to restore the complete data D when the user requests data.

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