Charging demand matching privacy protection method and system

Abstract

The invention discloses a charging demand matching privacy protection method and system. The method comprises the following steps: acquiring first data of an electric vehicle user and second data of a power grid operator; the electric vehicle user and the power grid operator respectively execute calculation actions to obtain respective hash tables; and after the calculation action is completed, the electric vehicle user and the power grid operator communicate with each other to obtain an optimal charging strategy. According to the method, the balance between user privacy protection and power grid optimization scheduling is realized, and the electric vehicle user is allowed to share necessary charging demand information with a power grid operator on the premise of not leaking personal driving and charging data. According to the scheme, the unbalanced PSI technology is used, the electric vehicle user with a small set serves as a receiver, the power grid operator with a large set serves as a sender, and the optimal charging strategy is intelligently recommended for the user on the premise that privacy information is not leaked. And meanwhile, the solving efficiency of the PSI is greatly improved by combining a fully homomorphic encryption technology.

Description

Technical Field

[0001] The present invention relates to the field of smart grid technology, and in particular to a charging demand matching privacy protection method and system. Background Art

[0002] Nowadays, with the rapid popularization of electric vehicles (EVs) and the widespread integration of renewable energy, traditional power grid systems are facing unprecedented challenges and opportunities. V2G (Vehicle-to-Grid) technology, as an innovative solution, is gradually becoming a key link between smart grids and sustainable transportation systems in the context of global energy transformation and sustainable development. V2G technology not only allows electric vehicles to charge when the grid load is low, but also can feed back the stored electricity to the grid when the grid demand is peak, so as to achieve optimal configuration and dynamic balance of energy. In addition, V2G technology also provides new business models and economic benefits for electric vehicle users, such as obtaining benefits by participating in demand response and energy trading.

[0003] Although V2G has been rapidly integrated into people's daily lives with great advantages, its implementation inevitably involves the collection and processing of a large amount of sensitive data, including users' driving habits, charging behavior, and location information. Security and privacy issues in V2G networks also face huge challenges. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a charging demand matching privacy protection method to solve the problem of balancing privacy protection and power grid optimization scheduling in the process of matching charging demand of electric vehicle users in a V2G network.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a charging demand matching privacy protection method, comprising:

[0008] Acquire first data of electric vehicle users and second data of power grid operators;

[0009] The electric vehicle user and the power grid operator respectively perform calculation actions to obtain their respective hash tables;

[0010] After the calculation is completed, the electric vehicle user and the grid operator communicate with each other to obtain the optimal charging strategy.

[0011] As a preferred solution of the privacy protection method for charging demand matching described in the present invention, wherein: the electric vehicle user and the power grid operator respectively perform calculation actions to obtain their respective hash tables including:

[0012] The electric vehicle user and the grid operator respectively perform hash calculations to load items into their respective hash tables.

[0013] As a preferred solution of the privacy protection method for charging demand matching described in the present invention, the electric vehicle user and the power grid operator communicate with each other including:

[0014] The electric vehicle user sends third data to the power grid operator, and the power grid operator performs calculations based on the third data and returns fourth data to the electric vehicle user;

[0015] The electric vehicle user and the grid operator use batch processing technology and unbalanced PSI technology during the communication process.

[0016] As a preferred solution of the charging demand matching privacy protection method of the present invention, the unbalanced PSI technology includes:

[0017] Encrypting the first data of the electric vehicle user to obtain third data, and transmitting the third data to the power grid operator;

[0018] The grid operator encrypts the calculation result and returns the fourth data to the electric vehicle user, and decrypts the fourth data to obtain the optimal charging strategy.

[0019] As a preferred solution of the charging demand matching privacy protection method of the present invention, the hash calculation includes:

[0020] Performing cuckoo hashing on the first data of the electric vehicle user and performing simple permutation hashing on the second data of the grid operator;

[0021] Let the hash parameter h be the number of hash functions in cuckoo hashing, m be the size of the hash table, B be the size of the bucket in simple permutation hashing, and λ be the statistical security parameter;

[0022] The first data N Y The data is hashed by Cuckoo Hash to ≥1-2 -λ The probability of successfully entering m buckets is N in the second data. X After all the data are hashed, hN X balls enter m buckets with maximum load B.

[0023] As a preferred solution of the privacy protection method for charging demand matching described in the present invention, the communication process between the electric vehicle user and the power grid operator includes:

[0024] Use FHE parameters to make all parties agree on the parameters (n, q, t) of the IND-CPA secure FHE scheme with circuit privacy;

[0025] The circuit depth parameter is selected, the electric vehicle user and the grid operator negotiate the window parameter, and the partition parameter minimizes the total cost.

[0026] As a preferred solution of the charging demand matching privacy protection method of the present invention, wherein: encrypting the first data of the electric vehicle user includes:

[0027] Assume B Y is an array of m buckets;

[0028] First, B Y interpret as a first vector of length m, batching the first vector into a plurality of plaintext polynomials;

[0029] For each plaintext polynomial, the electric vehicle user calculates a power in component form;

[0030] Finally, the electric car user uses FHE to encrypt each power to obtain the third data.

[0031] In a second aspect, the present invention provides a charging demand matching privacy protection system, comprising:

[0032] A data acquisition module, used to acquire first data of electric vehicle users and second data of power grid operators;

[0033] A calculation module, used for the electric vehicle user and the power grid operator to respectively perform calculation actions and obtain respective hash tables;

[0034] The strategy acquisition module is used for the electric vehicle user and the power grid operator to communicate with each other and acquire the optimal charging strategy after the calculation action is completed.

[0035] In a third aspect, the present invention provides a computing device, comprising:

[0036] Memory and processor;

[0037] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the charging demand matching privacy protection method are implemented.

[0038] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the charging demand matching privacy protection method.

[0039] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a privacy protection scheme for charging demand matching based on unbalanced PSI in V2G networks, aiming to achieve a balance between user privacy protection and grid optimization scheduling, allowing electric vehicle users to share necessary charging demand information with grid operators without leaking personal driving and charging data. This scheme uses unbalanced PSI technology, with electric vehicle users with a smaller set as receivers and grid operators with a larger set as senders, to intelligently recommend the optimal charging strategy to users without leaking privacy information. At the same time, the fully homomorphic encryption technology is combined to greatly improve the efficiency of PSI solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0041] Figure 1 A schematic diagram of the overall process of a charging demand matching privacy protection method according to an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of a V2G network architecture of a charging demand matching privacy protection method according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a basic system model of a charging demand matching privacy protection method according to an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of an unbalanced PSI application scenario of a charging demand matching privacy protection method according to an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of the internal structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0047] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0048] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0049] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0050] At the same time, in the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0051] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] Example 1

[0053] Before describing this embodiment, the relevant terms are explained first;

[0054] V2G: V2G (Vehicle-to-Grid) is an energy interaction technology between electric vehicles and the power grid. By enabling electric vehicles to participate in grid regulation during non-driving periods, such as load transfer and spinning reserve, efficient energy utilization is achieved, which helps to stabilize the grid and reduce peak loads.

[0055] Unbalanced PSI: Unbalanced PSI (Private Set Intersection) refers to the situation where the sizes of the data sets of both parties are significantly different during the intersection of private sets. It aims to optimize computing and communication efficiency and is widely used in data alignment scenarios such as user information matching, security testing, and federated learning. It protects privacy while promoting effective data utilization.

[0056] Reference Figure 1-4 , as an embodiment of the present invention, provides a charging demand matching privacy protection method, comprising:

[0057] S100: Acquire first data of the electric vehicle user and second data of the power grid operator;

[0058] In an optional embodiment, the first data of the electric vehicle user may include the electric vehicle user's driving habits, charging behavior, charging requirements, and location information;

[0059] In an optional embodiment, the second data of the power grid operator includes power grid operation status data, charging pile usage data, charging transaction data, power grid and charging pile communication data, etc.

[0060] In the embodiment of the present application, the first data of the electric car user is represented as Size is N Y ; The second data of the grid operator is expressed as Size is N X ; Among them, N X ,N Y ,σ is public.

[0061] It should be noted that the method of the present invention is mainly aimed at V2G networks. The typical architecture of V2G networks mainly includes a third party authority (TPA), a dispatching center (DC), a grid server (GS), a local aggregator (LAs), a charging station (CSs) and an electric vehicle (EVs). Figure 2 As shown;

[0062] exist Figure 2In the V2G network, the charging and discharging request service between EVs and the grid can only be carried out after the EVs and the grid are mutually authenticated. Generally speaking, EVs interact with the grid through CSs installed in residential areas, company parking lots, and shopping mall parking lots, because most EVs are parked in these places for about 95% of the time every day. LAs are responsible for monitoring and transmitting information between EVs and DCs, including authentication messages, request commands, battery status, and rewards, etc. In order to avoid the communication burden caused by direct data exchange between DC and each EV, the aggregation scheme of V2G networks usually adopts a hierarchical model. Based on the collected information, DC can formulate an optimized scheduling control strategy to achieve the charging / discharging operation of the required EVs. GS is responsible for the storage and trading of electricity. Although V2G networks bring us the following benefits: (1) Electric vehicle batteries act as buffers to provide auxiliary services such as peak load regulation and reactive power compensation for the grid. (2) Provide additional income for electric vehicle users and promote environmental protection. (3) Improve the stability and reliability of the grid and reduce the operating cost of the power system. However, security and privacy issues in V2G networks also face huge challenges.

[0063] S102: The electric vehicle user and the power grid operator respectively perform calculation actions to obtain their respective hash tables;

[0064] Preferably, the electric vehicle user and the grid operator respectively perform hash calculations to load the items into their respective hash tables;

[0065] Preferably, cuckoo hashing is performed on the first data of the electric vehicle user, and simple permutation hashing is performed on the second data of the power grid operator;

[0066] Preferably, let the hash parameter h be the number of hash functions in cuckoo hashing, m be the size of the hash table, B be the size of the bucket in simple permutation hashing, and λ be the statistical security parameter;

[0067] Preferably, N in the first data Y The data is hashed by Cuckoo Hash to ≥1-2 -λ The probability of successfully entering m buckets is N in the second data. X After all the data are hashed, hN X balls enter m buckets with maximum load B.

[0068] In the embodiment of the present application, the hash calculation is divided into two parts: (1) first hashing the message into shorter characters; (2) hashing into the bucket;

[0069] Specifically, the process of hashing a message into shorter characters is as follows: Let σ′=2log2(N x +N Y)+λ-1; if σ>σ′, the electric vehicle user and the grid operator hash their set to a shorter character representation. First, a random hash function H′:{0,1} is selected. σ →{0,1} σ′ , let X′={H′(x)|x∈X}, Y′={H′(y)|y∈Y}, replace (X,Y,σ) with (X′,Y′,σ′), and output the corresponding items in X and Y as the intersection.

[0070] Specifically, the process of hashing into a bucket is as follows: Random hash function As input, the grid operator uses the set X to perform the following steps to obtain B X :Let B X is an array of m buckets, each of which has a capacity of B and a value of For each x∈X and i∈[h], the grid operator chooses j←[B], that is, B x [Loc i (x)][j]=⊥, and let B x [Loc i (x)][j]:=(x L ,i). If the hash fails because a bucket is full, the grid operator outputs ⊥; otherwise, it outputs B x .

[0071] The electric vehicle user uses the set Y to perform the following steps to obtain B Y :Let B Y is an array of m buckets, each with a capacity of 1 and a value of (⊥,⊥). For each y∈Y, the receiver sets w=y, i←[B], defines and calls the Insert(w,i) function: replace (w,i) with B Y [Loc i (w)] If (w,i)≠(⊥,⊥), recursively call Insert(w,j), where j←[h]\{i}. If the recursive call to Insert for any y∈Y exceeds the system limit, the program stops and outputs ⊥; otherwise, output B Y .

[0072] S104: After the calculation action is completed, the electric vehicle user and the grid operator communicate with each other to obtain the optimal charging strategy;

[0073] Preferably, the electric vehicle user sends the third data to the grid operator, and the grid operator calculates according to the third data and returns the fourth data to the electric vehicle user; the electric vehicle user and the grid operator use batch processing technology and unbalanced PSI technology during the communication process.

[0074] Preferably, the first data of the electric vehicle user is encrypted to obtain third data, and the third data is transmitted to the power grid operator; the power grid operator encrypts the calculation result and returns the fourth data to the electric vehicle user, and decrypts the fourth data to obtain the optimal charging strategy.

[0075] Preferably, FHE parameters are used so that all parties agree on the parameters (n, q, t) of the IND-CPA secure FHE scheme with circuit privacy; circuit depth parameters are selected, electric vehicle users and grid operators negotiate window parameters, and the parameters are divided to minimize the total cost.

[0076] In the embodiment of the present application, the grid operator first preprocesses X, which is divided into three steps: division, coefficient calculation and preprocessing;

[0077] In a possible embodiment, the division process may be: the grid operator data set is divided into table B Y Divide vertically (i.e. by column) into α sub-tables B Y,1 ,B Y,2 ,...,B Y,α , each subtable has B′:=B / α columns;

[0078] In a possible embodiment, the coefficient calculation process may be: for each row v of each sub-table, the grid operator uses the polynomial The coefficient of v is substituted by Replace v;

[0079] In a possible embodiment, the batch processing process may be: for each sub-table obtained in the previous step, the grid operator interprets each column thereof as a vector of length m, where the elements are Then the grid operator batches each vector into m / n plaintext polynomials. Thus, the rth subtable is converted into m / n·B′ polynomials 0≤j≤B′.

[0080] In the embodiment of the present application, the window parameter is represented by l∈[1,log2B], and the partition parameter is represented by α∈[1,B];

[0081] It should be noted that the selected t needs to be large enough to make log2t>σ-log2m+log2h+1.

[0082] Preferably, let B Y is an array of m buckets; first, Y It is interpreted as a first vector of length m, and the first vector is batched into multiple plaintext polynomials; for each plaintext polynomial, the electric vehicle user calculates the power in component form; finally, the electric vehicle user encrypts each power using FHE to obtain third data.

[0083] Specifically, first, Y Interpret as a vector of length m, and batch the vector into m / n plaintext polynomials For each batch plaintext polynomial Y, the EV user computes the component form i·2 j Power where 1≤i≤2 l-1 and 0≤j≤log2(B′) / l. Finally, the electric car user uses FHE to encrypt each of these powers and obtains m / n ciphertext sets {c i,j}. Electric vehicle users send these ciphertexts to grid operators.

[0084] In the embodiment of the present application, the electric vehicle user sends the encrypted third data to the grid operator, and the grid operator homomorphically calculates the encryption of all powers. For each ciphertext set {c i,j}, homomorphically compute a vector c=(c0,...,c B′ ), so that c k Is encrypted Finally, the grid operator obtains m / n vectors c1,...,c m / n . Then the calculation and evaluation are performed homomorphically:

[0085]

[0086] for all 1≤i≤m / n,and 1≤r≤α

[0087] It can be seen that the protocol correctly calculates the intersection conditional on the success of the hash path, and the 1-2 -λ The overwhelming probability of occurrence. Its security is proved in the standard semi-honest simulation-based paradigm. That is, the scheme is based on Π PSI Safely implements function F PSI , if it is correct and there are two simulators (PPT algorithm) Sim R , Sim S And has the following properties: Simulator R Taking the EV user data set and the intersection as input, the proposed scheme is required to generate samples that are indistinguishable from what the receiver sees for real interactions. S is defined similarly, but does not take an intersection as input.

[0088] In the embodiment of the present application, the simulator is assumed to be composed of (h,m,B,n,q,t,α,e,H′,{H i} 1≤i≤h ) parameterization, which is fixed, public, and hashed to a smaller representation;

[0089] Then, define the receiver simulator Sim R As follows. R Compute the set Y′=H′(Y) and cuckoo-hash its elements into a table of size m using a modified hash;

[0090] In the embodiment of the present application, the modification method is: if the element y is in X∩Y, insert a 0, otherwise insert a After the hash is completed, Sim R from Randomly insert non-zero elements into the remaining empty slots; next, Sim R Create α-1 more tables of the same size and use the The random non-zero elements are filled; then all the α tables are randomly permuted to match the values ​​inserted in the library; finally, each table is batched into m / n FHE plaintext polynomials and homomorphically encrypted into m / n ciphertexts.

[0091] It should be noted that the obtained m / n·α ciphertext will be used as a simulation of the electric vehicle user’s view. Due to the circuit privacy assumption of the underlying fully homomorphic encryption scheme, this view is indistinguishable from the intersection obtained by the electric vehicle user in the actual execution of the scheme. The simulator Sim S New zero encryptions can be generated to replace encryptions, and according to the IND-CPA security of the fully homomorphic encryption scheme, the result is indistinguishable from the intersection of the grid operators in the real protocol.

[0092] In the embodiment of the present application, the unbalanced PSI architecture diagram in V2G is specifically as shown in the attached Figure 3 As shown, after the system is initialized, the electric vehicle EV and the charging station CS (in order to simplify the steps, only one electric vehicle and one charging station are used as an example) are registered with the TPA through the local aggregator, and the legitimacy of each other's identity is verified through two-way authentication in subsequent charging / discharging transactions;

[0093] In the intelligent transportation system, electric vehicles (EVs) are bound to specific users to achieve account management and personalized customized services. Binding can be achieved through very mature technologies such as near field communication (NFC), radio frequency identification (RFID) or mobile applications, so users can easily bind their personal accounts to EVs to verify and authorize vehicle use rights. This binding not only ensures the safety and exclusivity of vehicle use, but also allows the system to provide customized services based on user preferences and historical behaviors, such as automatically adjusting in-car environment settings, optimizing charging plans, and tracking energy consumption patterns. In addition, the binding process also brings users a convenient payment solution, making the settlement process of charging and parking fees automated and seamless. In short, the binding between electric vehicles and users is an important foundation for realizing intelligent, personalized and efficient transportation services. It greatly enhances the user experience and provides support for the construction of smart cities.

[0094] After the user successfully binds to the electric vehicle, the user enters the charging requirements through the demand matching application set by the local aggregator LA or the vehicle's built-in system. The requirements include the expected charging time, location, preferred charging power, expected charging amount, charging speed, and any special service requests. However, users do not want to disclose sensitive information such as their driving routes, charging history, and location, so the demand information is sent after encryption. The intelligent charging service platform will securely transmit the encrypted information to the user server managed by DC for storage. When the user is in actual use, the platform will intelligently recommend CS and related charging services to the user based on the user's location, the power of the vehicle, etc. Since the user's geographical location and EV status are sent encrypted, and the user data in the server is also encrypted, this solution uses the privacy set intersection PSI technology to return matching services to the user without leaking any information outside the intersection.

[0095] Private Set Intersection (PSI) is a cryptographic technique that allows two communicating parties to compute the intersection of sets without revealing any information other than the intersection.

[0096] It should be noted that the present invention uses fully homomorphic encryption FHE to construct a fast PSI protocol, which has a small communication overhead, works well when one of the two sets is much smaller than the other, and is secure against semi-honest adversaries. Batch processing is a well-known and powerful technology in fully homomorphic encryption to achieve SIMD (single instruction, multiple data) operations on ciphertext.

[0097] In the embodiment of the present application, for an appropriate choice of plaintext modulus t, there is a t arrive The ring isomorphism of ;

[0098] In one possible embodiment, a constant polynomial a∈R t Corresponds to the vector Furthermore, this isomorphism translates polynomial addition and multiplication into every n-field To simplify the explanation, the polynomial and vector notations of the plain text are used interchangeably, and the conversion from one representation to the other is omitted;

[0099] Apply batching to reduce the computation and communication cost of the basic protocol as follows: The receiver groups its items into vectors of length n, encrypts them, and sends N Y / nThe ciphertext is sent to the sender. i After that, the sender samples A vector of uniformly random nonzero elements Homomorphic Computation and returns it to the receiver. Batching techniques allow the sender to operate on n items from the receiver simultaneously, resulting in an n-fold improvement in both computation and communication. Since n is typically in the thousands, this leads to a significant improvement over the basic protocol.

[0100] In one possible embodiment, the term N X +N Y The total number of is much smaller than the number of all possible strings of length σ2 σ Since the performance of the protocol will decrease as the length of the string increases, the parties use an agreed hash function to compress their strings to a fixed length σ max It is then advantageous to perform the PSI protocol on these hash strings.

[0101] When all N X +N Y The random string is hashed to a size of When the domain is , the probability of collision is approximately For a statistical safety parameter λ, Pr[collision occurrence]≤2 -λ . Therefore, the compressed string should have at least length:

[0102] σ max =2log2(N X +N Y )+λ-1

[0103] Substituting in permutation-based cuckoo hashing further reduces the length of the string to:

[0104] σ max -log2 m+log2 h+1

[0105] Therefore, by choosing the encryption parameter t,

[0106] log2t>σ max -log2 m+log2 h+1

[0107] Analog-to-digital conversion is a well-known operation in lattice-based fully homomorphic encryption schemes. It is a public operation that transforms a ciphertext with encryption parameter q into a ciphertext that encrypts the same plaintext, but with parameter q′<q being smaller. As long as q′ is not too small, the correctness of the encryption scheme is preserved. Since the size of an FHE ciphertext is linear in logq, the analog-to-digital conversion reduces the size of the ciphertext by a factor of logq / logq′. This trick allows the sender to "compress" the returned ciphertext before sending it to the receiver. In practice, the returned ciphertext can be reduced to about 15-20% of the original.

[0108] It should be noted that the present invention designs a charging demand matching privacy protection scheme based on unbalanced PSI in V2G network, and the application scenarios are as follows: Figure 4 As shown, electric vehicle users with small sets interact their personal driving and charging data with grid operators with larger sets to obtain intersection information, i.e., the optimal charging strategy, which is then returned to the electric vehicle users; electric vehicle users and grid operators first pre-process their own data sets through hash calculations, and then encrypt and transmit them through homomorphic encryption to obtain the final intersection.

[0109] The above is a schematic scheme of a charging demand matching privacy protection method of this embodiment. It should be noted that the technical scheme of the charging demand matching privacy protection system and the technical scheme of the charging demand matching privacy protection method described above belong to the same concept. For details not described in detail in the technical scheme of the charging demand matching privacy protection system in this embodiment, please refer to the description of the technical scheme of the charging demand matching privacy protection method described above.

[0110] Example 2

[0111] This embodiment provides a charging demand matching privacy protection system, including:

[0112] A data acquisition module, used to acquire first data of electric vehicle users and second data of power grid operators;

[0113] A calculation module, used for electric vehicle users and power grid operators to perform calculation actions respectively and obtain their respective hash tables;

[0114] The strategy acquisition module is used to communicate between electric vehicle users and grid operators to obtain the optimal charging strategy after the calculation action is completed.

[0115] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0116] Example 3

[0117] This embodiment provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a charging demand matching privacy protection method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse.

[0118] This embodiment also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the following is achieved: obtaining first data of the electric vehicle user and second data of the power grid operator; the electric vehicle user and the power grid operator respectively perform calculation actions to obtain their respective hash tables; after the calculation actions are completed, the electric vehicle user and the power grid operator communicate with each other to obtain the optimal charging strategy.

[0119] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A charging demand matching privacy protection method, characterized in that: include: Acquire first data of electric vehicle users and second data of power grid operators; The electric vehicle user and the power grid operator respectively perform calculation actions to obtain their respective hash tables; After the calculation is completed, the electric vehicle user and the grid operator communicate with each other to obtain the optimal charging strategy.

2. The charging demand matching privacy protection method according to claim 1, characterized in that: The electric vehicle user and the grid operator respectively perform calculation actions to obtain their respective hash tables including: The electric vehicle user and the grid operator respectively perform hash calculations to load items into their respective hash tables.

3. The charging demand matching privacy protection method according to claim 1 or 2, characterized in that: The electric vehicle user and the grid operator communicate with each other including: The electric vehicle user sends third data to the power grid operator, and the power grid operator performs calculations based on the third data and returns fourth data to the electric vehicle user; The electric vehicle user and the grid operator use batch processing technology and unbalanced PSI technology during the communication process.

4. The charging demand matching privacy protection method according to claim 3, characterized in that: Unbalanced PSI techniques include: Encrypting the first data of the electric vehicle user to obtain third data, and transmitting the third data to the power grid operator; The grid operator encrypts the calculation result and returns the fourth data to the electric vehicle user, and decrypts the fourth data to obtain the optimal charging strategy.

5. The charging demand matching privacy protection method according to claim 2, characterized in that: Hash calculation includes, Performing cuckoo hashing on the first data of the electric vehicle user and performing simple permutation hashing on the second data of the grid operator; Let the hash parameter h be the number of hash functions in cuckoo hashing, m be the size of the hash table, B be the size of the bucket in simple permutation hashing, and λ be the statistical security parameter; The first data N Y The data is hashed by Cuckoo Hash to ≥1-2 -λ The probability of successfully entering m buckets is N in the second data. X After all the data are hashed, hN X balls enter m buckets with maximum load B.

6. The charging demand matching privacy protection method according to claim 5, characterized in that: The communication process between the electric vehicle user and the grid operator includes: Use FHE parameters to make all parties agree on the parameters (n, q, t) of the IND-CPA secure FHE scheme with circuit privacy; The circuit depth parameter is selected, the electric vehicle user and the grid operator negotiate the window parameter, and the partition parameter minimizes the total cost.

7. The charging demand matching privacy protection method according to claim 6, characterized in that: Encrypting the first data of the electric vehicle user includes: Assume B Y is an array of m buckets; First, B Y interpret as a first vector of length m, batching the first vector into a plurality of plaintext polynomials; For each plaintext polynomial, the electric vehicle user calculates a power in component form; Finally, the electric car user uses FHE to encrypt each power to obtain the third data.

8. A charging demand matching privacy protection system, characterized in that: include, A data acquisition module, used to acquire first data of electric vehicle users and second data of power grid operators; A calculation module, used for the electric vehicle user and the power grid operator to respectively perform calculation actions and obtain respective hash tables; The strategy acquisition module is used for the electric vehicle user and the power grid operator to communicate with each other and acquire the optimal charging strategy after the calculation action is completed.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the charging demand matching privacy protection method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the charging demand matching privacy protection method described in any one of claims 1 to 7.

Images