CN111507564A - Urban road alarm message reliability evaluation system and method integrating space-time correlation - Google Patents
Urban road alarm message reliability evaluation system and method integrating space-time correlation Download PDFInfo
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Abstract
The invention discloses an urban road alarm message reliability evaluation system integrating space-time relevance, which comprises the following steps: including the road side unit RSU, the road side unit RSU includes: a message preprocessing unit MPU, a dynamic model building unit DMU and a message evaluation unit MEU. The invention also discloses an evaluation method of the evaluation system, which comprises the following steps: collecting alarm messages broadcast by vehicles in the communication range of the RSU; classifying the alarm messages according to event types; constructing an irregular box body for the same clustering message to obtain a time consistency box line graph; constructing a spatial consistency box line graph according to the time consistency box line graph and the longitude and latitude; performing space-time consistency evaluation according to the space consistency box line graph to obtain a space-time consistency score; the RSU broadcasts the message identification number and the spatiotemporal consistency score to the surrounding vehicles. The evaluation system and the evaluation method carry out reliability evaluation on the obtained alarm message and send the result to the vehicle, thereby ensuring that the vehicle safely and reliably enjoys information service.
Description
Technical Field
The invention belongs to the technical field of information security, and particularly relates to a system and a method for evaluating reliability of an urban road warning message by fusing space-time relevance.
Background
In the information service of the internet of vehicles, the vehicles share the self information and the received information to nearby vehicles and Road Side Units (RSUs) through broadcasting, and the services of improving the driving safety and quality of the vehicles, such as safety, entertainment and the like, are provided for the vehicles and drivers. However, attackers may issue false messages by manipulating sensors or colluding attacks, thereby having a tremendous impact on network and application performance. Therefore, the method is a research hotspot for efficiently detecting the false information for the high-dynamic and low-delay car networking.
The search of the prior art documents shows that the detection of false information in the internet of vehicles mainly has two aspects: consistency and rationality. The consistency detection means that whether the average values or the difference values of all the parties of the message have significant differences under a certain significance level is verified, and unreliable information is detected through the significant differences; detection of reasonableness uses a particular known data model in the real world to detect unreliable information, verifying the authenticity of messages through a set of predefined rules or protocol specifications to describe physically impossible content. The rationality model can be derived from narrowly defined rules (e.g. violating the laws of physics: violating the maximum possible distance; reporting vehicles with a speed of 700 km/h; two vehicles occupying one location at the same time; vehicles that are present in multiple locations at the same time and that transmit information beyond the communication capacity). Sedjelmaci et al published 2014 in IEEEInternet Things paper An effective and light interference detection mechanism for service-oriented vehicle networks compares the position, speed, etc. data from the vehicle nodes with the speed in their beacon messages to detect the false information. Heijden et al, in 2016, published in IEEE Communications Surveys & Tutorials paper Survey on Misbehaviodetection in cooperative interaction transfer systems, proposed a rule-based error information detection scheme that includes a model for detecting a suddenly occurring vehicle (SAV), using signal strength to estimate the distance that first occurs within the communication range of other vehicles carrying the model; and observing the Minimum Moving Distance (MMD), checking whether the moving distance of the vehicle is compatible with the speed thereof. However, these schemes only check the reasonability of the messages from the aspects of position, speed and the like, but some messages have specific time and space correlation, and the correlation between the messages can be mined out so as to judge the authenticity of the messages.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide an urban road warning message reliability evaluation system and an urban road warning message reliability evaluation method integrating space-time correlation, which are used for evaluating the reliability of the obtained warning message and sending the result to a vehicle so as to ensure that the vehicle can safely and reliably enjoy information service.
An urban Road warning message reliability evaluation system fusing space-time relevance, the system comprises a Road-Side Unit (RSU) for receiving messages, evaluating the reliability of the messages and sharing evaluation results, the RSU comprises:
message Preprocessing Unit MPU (Message-Preprocessing Unit): collecting alarm messages, classifying the alarm messages, and taking classified alarm information as preprocessed information;
dynamic Model construction Unit DMU (Dynamic-Model Unit): constructing a space-time consistency model by utilizing the preprocessed information;
message Evaluation unit MEU (Message-Evaluation unit): and performing reliability evaluation on the received message by utilizing a space-time consistency model so as to trigger an event decision process.
The invention also provides an evaluation method of the urban road warning message reliability evaluation system integrating the space-time correlation, and the evaluation method comprises the following steps:
(1) the method comprises the steps that an MPU (message preprocessing unit) collects alarm messages broadcasted by vehicles in a communication range of the RSU, wherein the alarm messages comprise vehicle identification numbers, message identification numbers, incident places, event types, reporting time and reporting positions;
(2) the message preprocessing unit MPU classifies the alarm messages according to event types, and the alarm messages can be divided into three types: the traffic jam message, the traffic accident message and the road maintenance message are contained;
(3) reporting the same clustering message at T time intervals, dynamically constructing a box line graph by a dynamic model construction unit DMU, representing the number of the clustering messages by using a width NC, and constructing an irregular box body to obtain a time consistency box line graph;
(4) the DMU filters abnormal messages outside the edge line according to the time consistency box line graph and then constructs a space consistency box line graph from the longitude and the latitude;
(5) the information evaluation unit MEU filters abnormal information outside the edge line according to the space consistency box line graph, selects clustering information in the edge line in the space consistency box, the same number NC of clustering information at the reporting time, the same number NC2 of clustering information at the reporting longitude and the same number NC3 of clustering information at the reporting latitude as input, and carries out space-time consistency evaluation to obtain space-time consistency scores;
(6) the RSU broadcasts the message identification number and the spatiotemporal consistency score to the surrounding vehicles.
Preferably, in step (1), the alert message is a first-time-to-send-class message rather than a forwarded message.
In the step (3), the time consistency boxplot comprises 7 data nodes, and the positions of the two ends of the box body respectively correspond to an upper quartile Q3 and a lower quartile Q1 of alarm information reported in a T time interval; the line segment inside the box body represents a median; the two line segments at Q3+1.5IQR, where IQR represents the full range of the quartile, and Q1-1.5 IQR, Q3-Q1, are outlier edge lines. T ranges from 10s to 30s and can be adjusted according to message types and traffic conditions.
In the step (4), the spatial consistency boxplot is longitude and latitude distribution of the clustering messages in the same time-space range and for the same event. Specifically, a box plot is dynamically constructed with D1 as a longitude interval and D2 as a latitude interval, D1 and D2 range from 0.0001 ° to 0.01 °, and the box plot can be adjusted according to message types and traffic conditions.
In step (5), the method for calculating the spatiotemporal consistency score by the spatiotemporal consistency evaluation is as follows:
wherein NE represents the total number of messages in all the time consistency model edge lines, NE2 represents the total number of messages in all the space consistency model edge lines, MAXT represents the maximum time span, and T represents the time interval T for constructing the time consistency box plot; MAXX represents the maximum longitude span, and X represents the longitude interval for constructing a spatially consistent box plot; MAXY represents the maximum latitude span, and Y represents the latitude interval at which the spatial consistency boxplot was constructed.
When the altitude consistency is the same, namely MAXX-MAXY-MAXT-0, returning
When in use
When it is returned to
By dividing by
The final spatiotemporal consistency score is normalized to 0 to 1.
According to the urban road alarm message reliability evaluation system and method integrating the space-time relevance, the space-time consistency of the alarm message is mined by constructing the dynamic box line graph; the credibility of the message content is evaluated by the road side unit, and the result is shared to surrounding vehicles, so that the vehicles can safely and reliably enjoy information service.
Drawings
FIG. 1 is a schematic structural diagram of a time consistency box plot provided by the present invention;
FIG. 2 is a schematic structural diagram of a spatially consistent box plot provided by the present invention;
FIG. 3 is a flow chart of the method for evaluating reliability of an urban road warning message fused with spatiotemporal relevance according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The system for evaluating reliability of an urban Road warning message fusing temporal-spatial correlation provided by the embodiment comprises a Road Side Unit (RSU): the system is used for receiving the message, evaluating the reliability of the message and sharing the evaluation result. The road side unit RSU includes:
message Preprocessing Unit MPU (Message-Preprocessing Unit): collecting alarm messages, classifying the alarm messages, and using the classified alarm messages as preprocessed messages;
dynamic Model construction Unit DMU (Dynamic-Model Unit): constructing a space-time consistency model by utilizing the preprocessed information;
message Evaluation unit MEU (Message-Evaluation unit): and performing reliability evaluation on the received message by utilizing a space-time consistency model so as to trigger an event decision process.
The flow chart of the evaluation method of the urban road warning message reliability evaluation system fusing the spatio-temporal relevance is shown in fig. 3. Specifically, the method comprises the following steps:
s1, collecting alarm information
The Message Preprocessing Unit (MPU) collects alarm messages broadcast by vehicles in the communication range of the RSU, the content of the alarm messages comprises vehicle identification numbers (CI), message identification numbers (MI), incident places (I L), Event Types (ET), reporting time (ST), reporting positions (S L), namely EM { CI, MI, I L, S L }, and the alarm messages are defined as messages of a first sending class instead of forwarded messages, the collected messages are as follows:
{001, 001, (120.016, 30.278), traffic jam, 2020-1-1510: 01: 01, (120.018, 30.284) };
{002, 002, (120.217, 30.25), traffic accident, 2020-1-1510: 01: 08, (120.216, 30.24) };
{003, 003, (120.017, 30.288), traffic jam, 2020-1-1510: 01: 02, (120.016, 30.287) };
{004, 004, (120.017, 30.288), traffic jam, 2020-1-1510: 01: 03, (120.018, 30.289);
{001, 005, (120.015, 30.25), road maintenance, 2020-1-1510: 02: 00, (120.016, 30.24) };
{001, 006, (120.015, 30.25), road maintenance, 2020-1-1510: 02: 05, (120.018, 30.24) };
{005, 007, (120.017, 30.288), traffic congestion, 2020-1-1510: 01: 04, (120.018, 30.289) };
{006, 008, (120.017, 30.288), traffic jam, 2020-1-1510: 01: 05, (120.018, 30.289) };
{007, 009, (120.017, 30.288), traffic congestion, 2020-1-1510: 01: 06, (120.018, 30.289) };
{008, 010, (120.017, 30.288), traffic jam, 2020-1-1510: 01: 07, (120.018, 30.289) };
{009, 011, (120.017, 30.288), traffic jam, 2020-1-1510: 01: 08, (120.018, 30.289)}.
S2, classifying the messages according to event types
The Message Preprocessing Unit (MPU) classifies messages according to event type, and may obtain clusters: clusterC1{001, 003, 004, 007, 008, 009, 010, 011}, clusterC2{002}, clusterC3{005, 006 }. Messages within a time interval and from the same vehicle are only entered into the first message it sends, so the 006 message in clusterC3 is considered invalid. Among them, clusterC1 (containing "traffic jam" messages), clusterC2 (containing "traffic accident" messages), and clusterC3 (containing "road repair" messages).
S3, constructing a time consistency box chart according to the reporting time
As shown in fig. 1, taking the message of clusterC1 as an example, the dynamic model building unit (DMU) dynamically builds a box diagram at a time interval of 10s, the positions of the two ends of the box respectively correspond to the upper and lower quartiles of the reporting time (Q3: 10: 01: 02 and Q1: 10: 01: 06), and the line segment inside the box represents the median 10: 01: 04. the two line segments at Q3+1.5IQR and Q1-1.5 IQR are outlier edge lines, where IQR represents the quartile range, i.e., IQR is 00:00: 07. In order to reflect the difference of the number of messages at each reporting moment, the width NC is used for representing the number value of the messages and constructing an irregular box body, which is different from the traditional rectangular box body.
S4, filtering abnormal values according to the time consistency box line graph
According to most of the honest assumptions in the internet of vehicles, the more messages are reported at the same time, the closer this time is to the true situation of the event. Therefore, the messages in the margin line in the time consistency box chart and the Number (NC) of the messages with the same reporting time are used as the input of the space consistency box chart.
S5, constructing a space consistency box chart for the messages with reasonable time
As shown in fig. 2, the dynamic model building unit (DMU) dynamically builds a box plot with D1 as a longitude interval and D2 as a latitude interval, where D1 and D2 range from 0.0001 ° to 0.01 ° (adjusted according to message types and traffic conditions), and represent that the distribution of the longitude and latitude of the incident point is reported for the same event in the same time-space range.
S6, filtering abnormal values according to the spatial consistency box line graph
And filtering the space abnormal messages outside the edge line according to the space consistency box line graph. And the messages in the normal value range and the Number (NC) of the messages with the same reporting time, the number (NC2) of the messages with the same reporting longitude and the number (NC3) of the messages with the same reporting latitude are taken as the input of a Message Evaluation Unit (MEU).
S7, evaluating the space-time consistency of the message
The spatiotemporal consistency score of a message by a Message Evaluation Unit (MEU) is calculated as follows:
wherein NE represents that the total number of messages in all the time consistency box line graph edge lines is 8, and NE2 represents that the total number of messages in all the space consistency model edge lines is 8. The confidence score using the exponential function will grow faster as the number of messages at the same time and location is greater, indicating a higher probability that the message is true.
MAXT represents the maximum time span 8s in the time consistency model, T represents the time threshold that can be within the same cluster; MAXX represents the maximum longitude span of 0.001 in the spatial consistency model, X represents a longitude threshold that can be within the same cluster; MAXY represents the maximum latitude span of 0.01, and Y represents the latitude threshold that can be within the same cluster. That is, when the reporting space-time span of the messages in the cluster is large, the overall trust score of the cluster is relatively reduced.
When the space-time consistency in the clusters is highly the same, i.e. MAXX (MAXY) MAXT (0), return
When in use
When it is returned to
By removing
The final spatiotemporal consistency score is normalized to 0 to 1.
S8, feeding back an evaluation result according to the score
Finally, the RSU broadcasts the message identification number and the spatiotemporal consistency Score MessageID, Score to surrounding vehicles.
Claims (7)
1. The system for evaluating the reliability of the urban road warning message fused with the space-time relevance is characterized by comprising a Road Side Unit (RSU), wherein the RSU comprises:
message preprocessing unit MPU: collecting alarm messages, classifying the alarm messages, and taking classified alarm information as preprocessed information;
a dynamic model construction unit DMU: constructing a space-time consistency model by utilizing the preprocessed information;
message evaluation unit MEU: and performing reliability evaluation on the received message by utilizing a space-time consistency model so as to trigger an event decision process.
2. The evaluation method of the urban road warning message reliability evaluation system fusing the spatiotemporal relevance according to claim 1, characterized in that the evaluation method comprises the following steps:
(1) the method comprises the steps that an MPU (message preprocessing unit) collects alarm messages broadcasted by vehicles in a communication range of the RSU, wherein the alarm messages comprise vehicle identification numbers, message identification numbers, incident places, event types, reporting time and reporting positions;
(2) the message preprocessing unit MPU classifies the alarm messages according to event types, and the alarm messages can be divided into three types: the traffic jam message, the traffic accident message and the road maintenance message are contained;
(3) reporting the same clustering message at T time intervals, dynamically constructing a box line graph by a dynamic model construction unit DMU, representing the number of the clustering messages by using a width NC, and constructing an irregular box body to obtain a time consistency box line graph;
(4) the DMU filters abnormal messages outside the edge line according to the time consistency box line graph and then constructs a space consistency box line graph from the longitude and the latitude;
(5) the information evaluation unit MEU filters abnormal information outside the edge line according to the space consistency box line graph, selects clustering information in the edge line in the space consistency box, the same number NC of clustering information at the reporting time, the same number NC2 of clustering information at the reporting longitude and the same number NC3 of clustering information at the reporting latitude as input, and carries out space-time consistency evaluation to obtain space-time consistency scores;
(6) the RSU broadcasts the message identification number and the spatiotemporal consistency score to the surrounding vehicles.
3. The method for evaluating the reliability of an urban road warning message fusing spatial and temporal correlation according to claim 2, wherein in the step (1), the warning message is a first-time sending type message rather than a forwarded message.
4. The method for evaluating the reliability of the urban road alarm message fusing the spatio-temporal correlation according to claim 2, wherein in the step (3), the time consistency box line graph comprises 7 data nodes, and the positions of two ends of the box body respectively correspond to upper and lower quartiles Q3 and Q1 of the alarm information reported in the T time interval; the line segment inside the box body represents a median; the two line segments at Q3+1.5IQR, where IQR represents the full range of the quartile, and Q1-1.5 IQR, Q3-Q1, are outlier edge lines.
5. The method for evaluating the reliability of an urban road warning message fusing the spatio-temporal correlation according to claim 4, wherein in the step (4), the spatial consistency box chart is the longitude and latitude distribution of the clustered messages in the same spatio-temporal range and for the same event.
6. The method for evaluating reliability of an urban road warning message fusing spatial and temporal relevance according to claim 5, wherein in step (5), the method for calculating the spatial and temporal consistency score by the spatial and temporal consistency evaluation is as follows:
wherein NE represents the total number of messages in all the time consistency model edge lines, NE2 represents the total number of messages in all the space consistency model edge lines, MAXT represents the maximum time span, and T represents the time interval T for constructing the time consistency box plot; MAXX represents the maximum longitude span, and X represents the longitude interval for constructing a spatially consistent box plot; MAXY represents the maximum latitude span, and Y represents the latitude interval at which the spatial consistency boxplot was constructed.
7. The method of claim 6, wherein when the temporal-spatial coherence is the same, i.e. MAXX-MAXY-MAXT-0, the method returns
When in use
When it is returned to
By dividing by
The final spatiotemporal consistency score is normalized to 0 to 1.
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