CN114051235B - Vehicle track privacy protection method in Internet of vehicles scene - Google Patents
Vehicle track privacy protection method in Internet of vehicles scene Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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Abstract
The invention discloses a vehicle track privacy protection method in a vehicle networking scene, which utilizes a base station and a roadside intelligent computing unit to transmit basic information broadcast by vehicles to a cloud processing center, dynamically constructs a pseudonym confusion area through traffic flow and vehicle position privacy protection requirements, judges the similarity of vehicles according to the information such as the position, speed, acceleration, steering angle and the like of the vehicles, divides the vehicles with similar similarity into the same vehicle group, combines a group signature idea, enables the vehicles travelling in the confusion area to form different groups, provides a pseudonym blank window period, and enables the vehicles to have enough time and opportunity to finish pseudonym transformation.
Description
Technical Field
The invention belongs to a vehicle track privacy protection method, and particularly relates to a vehicle track privacy protection method in an urban road.
Background
With the development of wireless communication technology and the increasing living demands of people, new intelligent traffic with the internet of vehicles technology as a core is getting more and more attention, and the position privacy security problem is particularly important. In a car networking environment, in order to improve traffic efficiency and secure road safety, vehicles need to periodically broadcast basic safety messages containing vehicle identification, location, speed, acceleration, and steering angle at high frequencies.
In order to protect the privacy of vehicles, academia and industry use a pseudonym technology as a basic authentication and anonymity scheme of the internet of vehicles, and a pseudonym changing method is used for protecting the track privacy of the vehicles. A pseudonym is essentially a pair of public and private keys that are used to replace the true identity of the vehicle and to complete the encryption of non-underlying messages. The complete vehicle track can be segmented and the attacker is confused through the pseudonym transformation, so that the difficulty of the attacker in acquiring the track privacy is increased. However, the simple kana transformation still cannot guarantee the track privacy of the vehicle, an attacker can still predict the vehicle position through the space-time information of the vehicle, link the new and old kana, and complete the track privacy theft of the vehicle. At present, schemes for protecting the privacy of a vehicle track are mainly divided into two main categories: a dynamic context confusion-based kana transformation scheme and a confusion-region-based kana confusion scheme.
A dynamic context confusion based kana transformation scheme is to let the vehicle find the right moment in the course of the row or the right neighbor vehicle initiate a kana change at the same time to confuse the attacker. The scheme does not need participation of other non-vehicle facilities, the communication overhead is relatively small, but some kana link algorithms combined with road side information and vehicle position prediction type algorithms used in automatic driving can accurately predict the vehicle position and map new and old kana. The scheme based on the confusion zone sets some static confusion zones in the road, encrypts the vehicle communication entering the confusion zones by using the roadside intelligent computing unit and completes the pseudonym transformation, or issues virtual basic safety messages to simulate the vehicle so as to confuse the attacker. Such a scheme can be effective for an attacker, but can incur additional communication and computational overhead, and the size, shape, traffic pattern, and arrival rate of the vehicles of the static confusion zone can all affect the effectiveness of such a scheme. Therefore, how to design a reasonable and effective kana transformation scheme is still a problem to be solved.
Disclosure of Invention
The invention aims to solve the technical problems that: the utility model provides a vehicle track privacy protection scheme under the networking scene of car, through the dynamic construction pseudonym confusion area of traffic flow and vehicle position privacy safety demand, divide different vehicle subgroups in the confusion area, combine group signature thought to provide pseudonym blank window period, accomplish pseudonym transformation in the group in order to confuse the attacker, can form the confusion area of different sizes and shapes, reduce traffic flow mode, vehicle arrival rate and cause the influence to the protection effect.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a vehicle track privacy protection method in a vehicle networking scene comprises the steps of cooperative cooperation of a vehicle ad hoc network, a roadside intelligent computing unit, a base station and a cloud processing center, wherein the base station and the roadside intelligent computing unit collect and transmit basic information broadcast by a vehicle to the cloud processing center, and the cloud processing center calculates and transmits specific grouping information to the vehicle. The method comprises the following steps:
and step 1, collecting basic safety information broadcast by the vehicle by the roadside intelligent computing unit and the base station and forwarding the basic safety information to the cloud processing center.
And step 2, after receiving the basic safety information of the vehicle, the cloud processing center stores the data and periodically checks the traffic flow conversion condition, and if the traffic flow change reaches a threshold value, the step 3 is shifted.
And step 3, clustering vehicles by a rapid clustering method based on the density peak value based on the positions of the vehicles to obtain a current traffic flow distribution area. After the vehicle flow distribution is calculated, the confusion zone is dynamically constructed according to the safety requirements of the vehicle.
And 4, calculating a specific confusion zone boundary for each preparation confusion zone. After the calculation is completed, a wake-up step 5 performs a vehicle group division, and a loop step 2 checks whether a reconstruction of the confusion zone is necessary.
And 5, checking whether the confusion zone constructed in the step 4 exists, if so, turning to the step 6, and if not, waiting for the step 4.
And 6, checking whether the previously calculated vehicle group information exists in the dynamic confusion zone, if so, checking whether the vehicle group leaves the confusion zone, and if so, deleting the vehicle group from the vehicle group information. Turning to step 7.
And 7, independently taking the vehicles which are not grouped in the confusion zone as a group and adding the group into the vehicle group information, and then carrying out hierarchical combination according to the similarity among the vehicle groups to obtain the final vehicle group information.
And 8, selecting group owners of the vehicle groups, generating information necessary for group signatures for each group, and distributing the information to the target vehicles. After the distribution is completed, the process goes to step 9, and after the detection interval time, step 5 is executed regularly to recalculate the vehicle group information.
And 9, after the vehicle receives the information, performing grouping operation and pseudonym change operation. If the information of the group leader and the group member are not matched, the cloud center is reported, and the process goes to step 10.
And 10, counting report information, performing error check, taking the vehicle with the reported times exceeding the warning threshold as a suspicious vehicle, tracking the suspicious vehicle, removing the vehicle topology, re-jumping to the step 5, and calculating the vehicle group.
According to the method, the confusion area is dynamically constructed according to the traffic flow and traffic flow privacy security requirements, and the group signature thinking is combined to form a vehicle group with similar states to perform pseudonym change, so that the interference of the size, shape, traffic flow mode and vehicle arrival rate of the confusion area on the privacy protection effect of the vehicle position can be avoided, the pseudonym change is completed by providing a long-time pseudonym blank window period, thereby the attacker is confused, and the probability of continuously linking new and old pseudonyms by the attacker is reduced.
Drawings
FIG. 1 is a diagram of an architecture of an Internet of vehicles system according to the present invention;
FIG. 2 is a flow chart of the technical scheme of the invention;
Detailed Description
And 1, collecting basic safety information broadcast by the vehicle by the roadside intelligent computing unit and the base station, and forwarding the basic safety information to a cloud processing center, wherein the basic safety information comprises identity information (VIN code or pseudonym) of the vehicle, position coordinates (x, y), speed v, acceleration a and steering angle epsilon.
And 2, after receiving the basic safety information of the vehicle, the cloud processing center stores the data and periodically checks the traffic flow conversion condition, and if the traffic flow variation delta TV reaches a threshold value, the process goes to the step 3.The cloud processing center can adjust the time period T for checking the traffic flow change condition according to the road congestion degree of severe congestion, light congestion and smooth of the road traffic congestion degree evaluation method GA/T115-2020 p The options are set to 15min, 30min and 60min. Defining traffic volume (traffic volume) of a previous check period as TV 1 The traffic flow for the next inspection cycle is TV 2 Then the vehicle flow amount change Δtv= |tv 2 /TV 1 -1, setting the threshold for Δtv to 0.3, 0.5, 1, depending on the road congestion level "severe congestion", "mild congestion", "clear".
And step 3, clustering vehicles by a rapid clustering method based on the density peak value based on the positions of the vehicles to obtain a current traffic flow distribution area. The formula for dividing the traffic flow is as follows:
wherein, (x) 1 ,y 1 )、(x 2 ,y 2 ) The position coordinates of the vehicle 1 and the vehicle 2 are shown, and d is the distance between the two vehicles. After calculating the flow distribution, the pseudonym duration of the vehicle is counted, and the vehicle safety requirement of each area is calculated. And then, the safety requirements are used as indexes to sort the traffic distribution areas in a descending order, and the first 50% of traffic areas are selected as the preliminary confusion areas. For vehicles in each traffic distribution area, the calculation formula of the vehicle safety requirement score of each area is as follows:
Δt＝NOW-t.
where NOW is the time of calculation, t is the pseudonym duration, Δt is the time interval, t1 and t2 are the evaluation thresholds (set to 3 and 6, respectively), and the calculation formula of the total safety requirements score for each traffic distribution area is
Where m is the number of current traffic distribution areas (default set to 9).
Step 4, for each pre-confusion zone, calculating four vehicle positions (x value of longitude corresponding to position coordinate and y value of latitude corresponding to position coordinate) with minimum longitude, maximum longitude, minimum latitude and maximum latitude in the zone, and expanding the communication distance s of one vehicle outwards by four position points respectively c (set to 200 m) to construct a dynamic confusion zone. After the dynamic confusion zone construction is complete, wake-up step 5 performs vehicle panel partitioning, and loop step 2 checks if the confusion zone needs to be reconstructed.
And 5, checking whether the confusion zone constructed in the step 4 exists, if so, turning to the step 6, and if not, waiting for the step 4.
And 6, checking whether the vehicle group information exists in the dynamic confusion area, if so, checking whether the vehicle group information calculated before exists in the dynamic confusion area, if so, checking whether the vehicle group leaves the confusion area, and if so, deleting the vehicle group from the vehicle group information. Turning to step 7.
And 7, independently taking the vehicles which are not grouped in the confusion zone as a group and adding the group into the vehicle group information, calculating the similarity between each vehicle group based on the information such as the vehicle position, the speed, the acceleration and the steering angle, and carrying out hierarchical combination. The formula for similarity of the vehicle group is as follows:
wherein, (x) 1 ，y 1 )、(x 2 ，y 2 ) Is the position coordinates of the vehicle 1 and the vehicle 2, v 1 、v 2 Is the speed of the vehicle 1, 2, a 1 、a 2 Acceleration of the vehicle 1 and the vehicle 2, ε 1 、ε 2 Is the rotation of the vehicle 1 and the vehicle 2Angle direction. If the number of vehicles N of a vehicle consist reaches a threshold (set to 10), the calculation is removed and added to the result set. If the distance between all the vehicle subgroups in the confusion zone is greater than the communication distance s of the vehicles c And terminating the merging, adding the rest of the vehicle groups to the result set and saving the result. Turning to step 8.
And 8, the cloud processing center generates group identification, group public key, group private key, member private key and member group signature information for each group of vehicles by using a center selection algorithm, distributes the group identification, group public key, corresponding member private key and member signature information to the group members, and sends the group identification, group public key, group private key and group member public key to the group members. Defining a detection interval time t according to the time of the group leader vehicle running 10km at the current speed v chk =10/v. After the dispensing is completed, the process goes to step 9 and at the detection interval t chk Thereafter, step 5 is performed to recalculate the vehicle consist information.
And 9, after the vehicle receives the information, performing intra-group operation and pseudonymous name conversion operation. The overtime t is defined according to the time of the vehicle running at the current speed v for 1km out =1/v. Group length per group according to time t p Periodically transmitting detection information with group identification and group signature to detect surrounding group members; if at t out If no response from the panelist or an erroneous response is received within the time, the panelist is removed from the vehicle team and the cloud report is provided with the group identification, the panelist public key, the panelist group signature and the group separation information of the member group signature, and then the process goes to step 10. After the group member receives the probe, it will check the group signature and group identification, and if the check passes, it replies to the group member with a message with the group identification and its own group signature and broadcasts a base security message without a pseudonym. If the checking is not passed, carrying error information of the group identifier, the member private key, the member group signature and the received group leader group signature to the cloud report, and entering a silent state, and at t out And stopping communication within the time. Turning to step 10. After forming the vehicle group, the group leader will base it as usual with its own pseudonymBroadcasting of the security message, other vehicles within the group all broadcast basic security messages with the pseudonym information removed. When the vehicles outside the group communicate with the vehicles inside the group, the vehicles inside the group can master the pseudonym public key of the vehicles outside the group and can normally receive information, when the vehicles inside the group send information to the group members or the vehicles outside the group, the private key of the vehicles inside the group is used for signing a data packet, the data packet is firstly sent to the group length, if the data packet is inside the group, the group length forwards the corresponding decryption public key and the data packet to the target group member, and if the data packet is outside the group, the group length carries out signature forwarding by using the pseudonym of the vehicles inside the group after decryption. If the panelist is off-group, an off-group report carrying the group identification, the member private key and the member group signature is sent to the cloud processing center, and the detection information of the panelist is ignored, and the process goes to step 10.
Step 10, respectively storing report information of the group leader and report information of the group leader, judging that the report information of the group leader and the group leader is in paired appearance, if the paired appearance is in paired appearance and the group identification, the group leader group signature and the member group signature are verified to be successful, indicating that the group is normal, modifying cloud vehicle group information according to the group separation report, marking the vehicle group information as error information if verification is failed, and checking the number N of the error information of a confusion area Error If the threshold is reached (set to 50), the process goes to step 5 to recalculate the vehicle consist information for that area.
Claims (1)
1. A vehicle track privacy protection method in a vehicle networking scene comprises the steps of cooperative coordination of a vehicle ad hoc network, a roadside intelligent computing unit, a base station and a cloud processing center, wherein the base station and the roadside intelligent computing unit collect basic safety information broadcast by vehicles and transmit the basic safety information to the cloud processing center, the cloud processing center dynamically constructs vehicle confusion areas, calculates vehicle groups in each confusion area by utilizing the positions, the speeds, the directions and the accelerations of the vehicles, and forms a pseudonym blank window period by utilizing a group signature idea to provide enough time and opportunity for the vehicles to finish pseudonym transformation; the method comprises the following steps:
step 1, a roadside intelligent computing unit and a base station collect basic safety information broadcasted by a vehicle and forward the basic safety information to a cloud processing center;
step 2, after receiving the basic safety information of the vehicle, the cloud processing center stores the data and periodically checks the traffic flow conversion condition, and if the traffic flow change reaches a threshold value, the step 3 is turned to;
step 3, clustering vehicles by a rapid clustering method based on a density peak value based on the positions of the vehicles to obtain a current traffic flow distribution area; after calculating the traffic flow distribution area, dynamically constructing an confusion area according to the safety requirements of the vehicle;
step 4, calculating a specific confusion zone boundary for each preparation confusion zone; after the calculation is completed, the wake-up step 5 is used for dividing the vehicle groups, and the loop step 2 is used for checking whether the confusion zone needs to be reconstructed or not;
step 5, checking whether the confusion zone constructed in the step 4 exists, if so, turning to the step 6, and if not, waiting for the step 4;
step 6, checking whether the previously calculated vehicle subgroup information exists in the dynamic confusion zone, if so, checking whether the vehicle subgroup leaves the confusion zone, and if so, deleting the vehicle subgroup from the vehicle subgroup information; turning to step 7;
step 7, taking the vehicles which are not grouped in the confusion zone as a group independently and adding the vehicles into the vehicle group information, and then carrying out hierarchical combination according to the similarity among the vehicle groups to obtain final vehicle group information;
step 8, selecting group owners of the vehicle groups, generating necessary information of group signatures for each group, and distributing the necessary information to the target vehicles; defining detection interval time t according to the time of 10km of group leader vehicle running at current speed v chk =10/v; after the dispensing is completed, the process goes to step 9 and at the detection interval t chk Step 5 is executed regularly to recalculate the vehicle group information;
step 9, after the vehicle receives the information, performing grouping operation and pseudonym change operation, specifically, defining timeout time t according to the time of the vehicle running for 1km at the current speed v out Group length per group in terms of time t =1/v p Periodic transmission of the bandGroup identification and group signature detection information to detect surrounding panelists; if at t out Removing the vehicle group if the response of the group member is not received or the wrong response information is received in the time, reporting the group separation information carrying the group identification, the group public key, the group signature and the member group signature to the cloud processing center, and then turning to step 10; after receiving the detection information, the panelist will check the group signature and the group identifier, if the detection is passed, the panelist replies a message with the group identifier and the own group signature, and broadcasts a basic security message without a pseudonym, if the detection is not passed, the cloud processing center is reported with error information carrying the group identifier, the member private key, the member group signature and the received group signature, and enters a silent state, and at t out Stopping communication in time, and turning to step 10; after forming the vehicle group, the group owner broadcasts basic safety information by using own pseudonym as usual, other vehicles in the group broadcast basic safety information without pseudonym information, when the vehicles outside the group communicate with the vehicles inside the group, the vehicles inside the group can master the pseudonym public key of the vehicles outside the group and can normally receive information, when the vehicles inside the group send information to the group members or the vehicles outside the group, the private key of the vehicles inside the group signs a data packet by the self, the group owner forwards the corresponding decryption public key and the data packet to the destination group member, if the vehicles outside the group are the vehicles outside the group, the group owner carries out signature forwarding by using own pseudonym after decrypting, if the group member leaves the group, the group owner sends a group leaving report carrying a group identifier, a member private key and a member group signature, and ignores the detection information of the group owner, and the step 10 is carried out; if the information of the group leader and the group member is not matched, reporting the cloud processing center, and turning to step 10;
and 10, counting report information, performing error check, taking the vehicle with the reported times exceeding the warning threshold as a suspicious vehicle, tracking the suspicious vehicle, removing the vehicle topology, re-jumping to the step 5, and calculating the vehicle group.
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