04-03-2013, 10:59 AM
A Secure Cooperative Approach For Nonline-of-Sight Location Verification In VANET
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INTRODUCTION
Vehicular ad hoc networks (VANETs) are being developed to provide on-demand wireless communication infrastructure among vehicles and authorities. Such an infrastructure is expected to deliver multiple road safety and driving assistance applications. Vehicles will be equipped with sensors and communication devices that will allow them to cooperate with each other and with authority units to disseminate and exchange various road applications’ messages. For example, warning messages and traffic management instructions can be broadcast to increase drivers’ awareness of potential travel hazards, allowing them to respond earlier to avoid traffic congestion and collisions or to clear the way for inbound emergency response units. Other applications pertain to passenger comfort and convenience, such as locating points of interest, exchanging multimedia assets with other users in the network, or receiving location-based commercial advertisements.
Many of these promising applications require knowledge of real-time events and neighboring vehicles’ location specifications. A vehicle can determine its location using existing technologies such as Global Positioning Systems (GPS), map matching, dead reckoning, cellular localization, image and video processing, and relative positioning. Researchers have discussed integrating several techniques with statistical filters in a method called data fusion (see Fig. 1). Each technique has its advantages as well as security concerns, which must be taken into consideration during application development.
Enabling each vehicle to determine its location is necessary in VANET, but it is not enough. Vehicles also need to have information about events in their surroundings and proximal vehicles. This type of information can be exchanged between network members using beaconing, direct messaging, or group updates.
MOTIVATION AND PROBLEM STATEMENT
In VANETs, objects such as buildings, trees, and other features that exist on roadsides can interfere with or block radio signals. In general, the higher the radio signal frequency is, the more vulnerable it is to interference. One particular study showed the vulnerability of high-frequency radio signals to interference. For example, at a frequency of 5.85 GHz, a signal loss of 14 dB is caused by home penetration, and a loss of 11–16 dB is due to tree shadowing, whereas a signal loss of 7.7 dB is caused by penetrating a building at a frequency of 912 MHz. In the U.S., the 5.9-GHz frequency is assigned for VANET communication.
In Fig. 2, we illustrate what can happen if an obstacle blocks communication signals. Vehicle A detects an event E, which is an emergency vehicle approaching. In response, A sends a warning message to its neighbors behind it to encourage their operators to slow down and allow the emergency vehicle to pass, which is a sequence of events that could prevent vehicle operators from needing to brake suddenly or swerve. However, vehicle B might not receive the warning due to the position of the bus C. The bus does not forward the message, assuming that B is within A’s communication range. If A has the knowledge that B is still within communication range but obstacle C is blocking direct communication with it, the application should decide to allow C to forward the message to ensure message delivery.
SECURING LOCALIZATION
Due to VANET limitations and the importance of position information, securing localization is a challenging area of research on VANETs. A secure localization can be achieved with the following approaches.
1) Secure communication: Secure communication channels by enabling receivers to authenticate the sender while maintaining their privacy and checking message integrity. Some researchers have suggested securing VANET communications to authenticate the sender and check the message integrity using digital signatures.
2) Misbehavior detection and isolation: Detect malicious nodes by evaluating the context of messages and the behavior of the sending nodes.
3) Robust localization algorithm: Develop computation algorithms that accept and deal with errors and false position information.
4) Location verification: Enable nodes to verify received location information and validate its integrity.
RELATED WORK
Researchers have studied securing position information for wireless and ad hoc networks. Since each network has its own characteristics and requirements, several security frameworks and solutions have been proposed for different networks. Moreover, location verification protocols have been proposed with some solutions to provide a security layer for localization systems.
Boukerche et al. discussed secure localization algorithms that were proposed for wireless sensor networks (WSNs). The robust position estimation (ROPE), location anomaly detection (LAD), and Echo protocols apply location verification processes to check the computed position of network nodes. ROPE allows beacon nodes to use the radio signal physical parameters to verify the distance of a sender, LAD detects network anomalies by comparing the received data to the deployment information of sensors and the expected behavior of their observations, and Echo performs an in-region check to verify a node position with the help of a selected neighbor node using radio signal parameters and ultrasound signals to compute distance.
Table I summarizes some studies that have been conducted in this area. In most proposed solutions, verification protocols rely on signal strength measurement between nodes that have direct line of sight established between them. A state of NLOS may result in either dropping a record from a neighbor’s list or preventing a node from establishing a proper communication channel to verify a questioned node.
CONCLUSIONS
Obstacles can have a negative effect on drivers’ real-time traffic hazard awareness, which will affect some critical safety transactions such as merging with traffic, responding to sudden traffic pattern changes, and blind spot awareness. A state of NLOS between two vehicles may result in ignoring each other’s existence while they are just a few meters apart.We believe that neighborhood awareness is essential to supporting reliability and integrity in VANET applications. Current VANET location verification solutions assume that direct communication among vehicles is available. In this paper, we presented a collaborative protocol to verify an announced position when direct communication between the questioned node and the verifier is not possible. In addition to verifying a node location in a multihop cooperative approach, several security measures were included to improve themessage integrity. The simulation results showed that the proposed protocol increased the vehicles’ rate of neighborhood awareness under the effect of simulated obstacles. The exchanged messages helped to update the neighboring vehicles’ records and increased awareness for other nodes that cooperatively forwarded requests and replies. A solution such as what we propose will help to maintain localization service integrity and reliability, providing reliable position information for upper level applications.
[attachment=52499]
INTRODUCTION
Vehicular ad hoc networks (VANETs) are being developed to provide on-demand wireless communication infrastructure among vehicles and authorities. Such an infrastructure is expected to deliver multiple road safety and driving assistance applications. Vehicles will be equipped with sensors and communication devices that will allow them to cooperate with each other and with authority units to disseminate and exchange various road applications’ messages. For example, warning messages and traffic management instructions can be broadcast to increase drivers’ awareness of potential travel hazards, allowing them to respond earlier to avoid traffic congestion and collisions or to clear the way for inbound emergency response units. Other applications pertain to passenger comfort and convenience, such as locating points of interest, exchanging multimedia assets with other users in the network, or receiving location-based commercial advertisements.
Many of these promising applications require knowledge of real-time events and neighboring vehicles’ location specifications. A vehicle can determine its location using existing technologies such as Global Positioning Systems (GPS), map matching, dead reckoning, cellular localization, image and video processing, and relative positioning. Researchers have discussed integrating several techniques with statistical filters in a method called data fusion (see Fig. 1). Each technique has its advantages as well as security concerns, which must be taken into consideration during application development.
Enabling each vehicle to determine its location is necessary in VANET, but it is not enough. Vehicles also need to have information about events in their surroundings and proximal vehicles. This type of information can be exchanged between network members using beaconing, direct messaging, or group updates.
MOTIVATION AND PROBLEM STATEMENT
In VANETs, objects such as buildings, trees, and other features that exist on roadsides can interfere with or block radio signals. In general, the higher the radio signal frequency is, the more vulnerable it is to interference. One particular study showed the vulnerability of high-frequency radio signals to interference. For example, at a frequency of 5.85 GHz, a signal loss of 14 dB is caused by home penetration, and a loss of 11–16 dB is due to tree shadowing, whereas a signal loss of 7.7 dB is caused by penetrating a building at a frequency of 912 MHz. In the U.S., the 5.9-GHz frequency is assigned for VANET communication.
In Fig. 2, we illustrate what can happen if an obstacle blocks communication signals. Vehicle A detects an event E, which is an emergency vehicle approaching. In response, A sends a warning message to its neighbors behind it to encourage their operators to slow down and allow the emergency vehicle to pass, which is a sequence of events that could prevent vehicle operators from needing to brake suddenly or swerve. However, vehicle B might not receive the warning due to the position of the bus C. The bus does not forward the message, assuming that B is within A’s communication range. If A has the knowledge that B is still within communication range but obstacle C is blocking direct communication with it, the application should decide to allow C to forward the message to ensure message delivery.
SECURING LOCALIZATION
Due to VANET limitations and the importance of position information, securing localization is a challenging area of research on VANETs. A secure localization can be achieved with the following approaches.
1) Secure communication: Secure communication channels by enabling receivers to authenticate the sender while maintaining their privacy and checking message integrity. Some researchers have suggested securing VANET communications to authenticate the sender and check the message integrity using digital signatures.
2) Misbehavior detection and isolation: Detect malicious nodes by evaluating the context of messages and the behavior of the sending nodes.
3) Robust localization algorithm: Develop computation algorithms that accept and deal with errors and false position information.
4) Location verification: Enable nodes to verify received location information and validate its integrity.
RELATED WORK
Researchers have studied securing position information for wireless and ad hoc networks. Since each network has its own characteristics and requirements, several security frameworks and solutions have been proposed for different networks. Moreover, location verification protocols have been proposed with some solutions to provide a security layer for localization systems.
Boukerche et al. discussed secure localization algorithms that were proposed for wireless sensor networks (WSNs). The robust position estimation (ROPE), location anomaly detection (LAD), and Echo protocols apply location verification processes to check the computed position of network nodes. ROPE allows beacon nodes to use the radio signal physical parameters to verify the distance of a sender, LAD detects network anomalies by comparing the received data to the deployment information of sensors and the expected behavior of their observations, and Echo performs an in-region check to verify a node position with the help of a selected neighbor node using radio signal parameters and ultrasound signals to compute distance.
Table I summarizes some studies that have been conducted in this area. In most proposed solutions, verification protocols rely on signal strength measurement between nodes that have direct line of sight established between them. A state of NLOS may result in either dropping a record from a neighbor’s list or preventing a node from establishing a proper communication channel to verify a questioned node.
CONCLUSIONS
Obstacles can have a negative effect on drivers’ real-time traffic hazard awareness, which will affect some critical safety transactions such as merging with traffic, responding to sudden traffic pattern changes, and blind spot awareness. A state of NLOS between two vehicles may result in ignoring each other’s existence while they are just a few meters apart.We believe that neighborhood awareness is essential to supporting reliability and integrity in VANET applications. Current VANET location verification solutions assume that direct communication among vehicles is available. In this paper, we presented a collaborative protocol to verify an announced position when direct communication between the questioned node and the verifier is not possible. In addition to verifying a node location in a multihop cooperative approach, several security measures were included to improve themessage integrity. The simulation results showed that the proposed protocol increased the vehicles’ rate of neighborhood awareness under the effect of simulated obstacles. The exchanged messages helped to update the neighboring vehicles’ records and increased awareness for other nodes that cooperatively forwarded requests and replies. A solution such as what we propose will help to maintain localization service integrity and reliability, providing reliable position information for upper level applications.