Detection Of Impersonation Attack Based Computer Science Essay

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Vehicular Ad-Hoc Network or Vanet is a technology which offers the exchange of safety information between the communicating nodes. The Nodes or the vehicles in Vanets acts as a wireless router, thus allowing other participating nodes to form a range of network. Vanet involves Vehicle to Vehicle, Vehicle to Road Side, Vehicle to Infrastructure Communication. Vanets provides various applications and services between the vehicles for alerting the driver during the emergency situations.

Focusing on security services for various application and management messages, Vanet provides anonymity, authenticity and confidentiality between the vehicular networks. Sensors in the Vehicles can able to detect the changes in the speed or pattern in the vehicles and report it to the neighbouring vehicles, but other threats caused by bogus traffic information while traffic ahead, cheating with identity, speed or position, and tracking of vehicles could be made tricky by the adversary.

Tamilselvan L. and Sankaranarayanan D. V. [4] had studied about the Prevention of impersonation attack in wireless mobile ad hoc Networks. They have proposed new protocol which is used to prevent the impersonation attack. Their proposed model follows the mechanisms such as hash chains and digital signatures to secure mutable fields and authenticate the non-mutable fields of the messages respectively.

In our project, we focus on the detection of impersonation attacks in a fixed key infrastructure. The proposed method uses cryptography mechanism to detect the impersonator. The rest of the paper is followed as follows. Vanet Architecture is presented in section 2. Various attacks are explained in section 2.2

V2V Communication

DSRC is a short range communication (one way or two way) standard developed for mainly vehicle to vehicle communication and vehicle to infrastructure communication. These communications further provides variety of applications and services. The federal communication in United States has allocated 75 MHz bandwidth at 5.9 GHz Band radio frequency. This channel is based upon 802.11a standard and it has 7 distinct channels each of which is 10 MHz wide. The channels are designed to provide safety and non -safety applications. One channel is designed for serving safety communications, while other two channels are designed for special purposes. They can also have additional channel which can be combined for additional bandwidth.

Vehicles in the system send periodic status updates, through beacon signals during emergency situations, through the DSRC channels. There are many projects built around the world for academics, research in vehicle to vehicle communications. Some of the well known standard's such as Vehicle Safety Consortium (VSC) in the USA, Car-to-Car Communications Consortium (C2C-CC), Network on wheels (NoW), Cooperative Vehicles and Infrastructure Systems (CVIS) in the European Union and the Advanced Safety Vehicle Program (ASV) in Japan. The incorporated standard by DSRC into IEEE 802.11, WAVE is a universally accepted standard and IEEE 802.11p standard set to work with the security standard. IEEE standard 1609 defines the standard of security mechanisms for wireless communications in the Vehicular environment. The architectural components include OBU, RSU and WAVE.

WAVE standard defines two devices such as Road side unit (RSU) and Onboard Unit (OBU). The Road side unit host an application and provides services to the OBU. The WAVE uses orthogonal Frequency division multiplexing to split the channel capability of providing 10 MHz channels.

Vanet Overview

Intelligent Transportation System

Intelligent transportation system (ITS) is a kind of intelligent system which provides services to vehicles by collecting various traffic data and making sure of free flow of traffic. The vehicles broadcast information to the transportation agency, which further updates the information globally.

Inter-vehicle Communication

Inter-vehicle communication support multi-hop multicast/broadcast communication. It believes the messages should travel one behind the other vehicle.

Vehicle to roadside communication

It follows single hop broadcasting method. It observes the speed of the vehicle and check whether they violets the desired limit. Finally the RSU broadcast message to other equipped vehicles.

Routing based Communication

Multicast based routing is used in routing-based communication. The messages are sent using multi hop reaches until the messages reach the destined vehicle [12].

Vanet Network Architecture

Cellular/WLAN

In this architecture, the cellular gateway access point at the traffic is used to collect the information. Vanet is combined with cellular and WLAN to form a network.

Adhoc

The Adhoc network over comes the cost constraints of the cellular/WLAN network, to obtain certain goals like blind crossing.

Hybrid

It's a combination of both Infrastructure and ad-hoc network which provides better coverage among different wireless systems.

Vanet Architecture

The Vanet model is categorized into three different levels. The primary level is CA- Certified Authority. One of the main challenges in Vanets is establishing a trust between the other vehicles. This task is done by CA. They are responsible in the registration of RSU's and Vehicles. They have the complete authority to revoke the certificates, when needed. This level is considered as the stronger level and it is believed to be the trusted party and placed it in the highest level of security and it cannot be compromised. The secondary level is the RSU, which is fixed along the road sides and assumed to be trusted by the user while considering it as a middle level of security. The third level is the vehicles which are assumed to be compromised easily, when compared with other two levels; hence it is in the weaker level of security. In addition there are also pseudonymous certificates installed in the vehicles, which protect the privacy of the vehicles.

Safety Applications

There are basic set of applications which can be deployed in V2V and V2I communications. Applications like stationary vehicle warning which sends out warning information to other nodes, which is further forwarded to nearest RSU's. Applications such as traffic condition warning sends out the updated traffic situations in the nearest vicinity. In decentralized floating car data application, various warnings such as road adhesion, precipitation are sent to the vehicles which are in potential dangers. Broadcasting Traffic information and other access restrictions are the functionality of certain applications. In Emergency vehicle warning application, the emergency vehicle periodically broadcast its position, speed and warns the locals to pave way for the emergency vehicle to pass through. Other interesting applications are slow vehicle warning, wrong way driving warning, fleet management, personal data synchronization and media download.

Routing in Vanets

Vanets are a specific class of ad-hoc networks designed for ad-hoc routing protocols. These protocols are initially intended to design for Manets and later tested and put into practice in Vanets. Vanet differs from MANETs in many ways such as large scale of networks, routing structure and its features. Adhoc network follows proactive routing (Discovering new routes), reactive routing protocol (updating existing routing tables) and position based routing protocols (Geographical Location Information).

In conventional networks, packet forwarding, routing and other routing management is possible by nodes. While the adhoc networks differ by the nodes doing collaborating operations. In mantes, due to the lack of central point, and because of dynamic topology they lack security, they can't perform these operations. But Vanet follows generic dynamic topology where the topology changes very often. Here the warning messages are sent based on position based addressing(PBR), where the messages can be sent to many or selected node. Messages can be sent as control flooding, where vehicles broadcast their messages to other nodes. An assumption is made as each node constantly measures its position by Gps and maintains a location table with ID, along with the geographical positions of other nodes. They periodically, broadcast the collected information to its neighbours. PBR supports geographically scope broadcast [13] means the message is specified to the current cell and also helps in determining the cell broadcast message is new by considering Cell width and Location Area Width. PBR is basically divided into three components, such as beaconing, location service and forwarding.

In Beaconing, nodes transmit packet, with their Unique ID and geographical location. When it receives a packet destined to a destination it simply sends the packet, then they re-directs the packet to that node. In Location service, the node which needs to know about the location of other nodes, which are not available in the routing table, sends for the request with node ID and hop limits. In Geographical Broadcast, the data packets are flooded where the nodes rebroadcast the packets, by determining the appropriate geographical area. Beaconing process is done by the sender is authenticated and identified by building a reliable routing table. The warning messages are only allowed to be sent from the trustworthy vehicles to Infrastructure or vice versa.

There are way's where position based routing can be spoofed. One way to prevent the attack is by in-region verification. Here the vehicle verifies the position of the vehicle, whether they are actually located and claimed from that position. Position based verification is further classified as infrastructure based and non-infrastructure based schemes [14].

Other kinds of routing performed in the Vanets are GroBroadcast, Fleetnet Routing Protocol, but the advantages of position based networking are there are no routing/management, well suited for node mobility.

Security and Privacy

The objective of the security is the Information or Identities sent between two nodes are not revealed to any nodes and they are not authorized to receive the information. The location of the node is completely protected from the unauthorized user's access. The integrity of the information is also preserved between the nodes, by not allowing any modification or deletion in the messages sent between them. The Management information sent either from V2V or V2I is protected against any modification or manipulation during the transmission. The system should establish the liability of the users, by preserving the privacy of the drivers. Moreover, the unauthorized user should not pose like a legitimate user when communication in Vanets.

Attacks on Vehicular Networks

The attack is further classified as active tracking and passive tracking. Active tracking is the messages obtained from real time system. These attacks are caused by the nodes which are authorized to operate within the network. Some of the nodes, drop the packets which are not destined to them, the attacker also modify the content of the node to perform operations within the network. Few attacks like forging the packets come under this category. The attacker forges the messages, without even receiving it.

Active attacks can be classified as internal attacks and external attacks. An internal attack is performed by the node which belongs to the same network. Here the attacker should be having access to the network, while external attacks are performed by the node outside the network. By posing as legitimate vehicles in the network, outsiders can perform varieties of attacks such as producing false messages [6]. The types of attacks against messages are distinguished as ID disclosure attack, Sybil attack etc. One of the common attacks performed are impersonating a person or generating erroneous messages within the system. On transport layer, Vanets are vulnerable to the attacks like session hi-jacking. Passive attack and disruption of IEEE 802.11's carried out in data link layer, while jamming and eavesdropping takes place in physical layer.

In passive attack, the information is captured by listening to the traffic. The unauthorized node finds out the information about the network and causes damages to the network, attacks such as eavesdropping and traffic analysis. Later this information can be downloaded into the computer and readings are recorded.

Certain GPS tracking systems have the ability to generate summary reports of the historical data of a specific vehicle. The detailed vehicle's position can be plotted on stored in a database and can be viewed on various statistical tools.

There are several attacks possible in V2V communications. Attacks can be broadly classified into three different categories, such as Threats to availability, Threats to authenticity, and threats to confidentiality [6]. Denial of service attack, broad cast tampering, Malware, Black hole attack are various kind of threads to availability which are identified in the V2V and V2I communication system.

Similarly attacks like Masquerading, Replay Attack, GPS Spoofing, position faking, Message Tampering/Suppression/Alteration/Fabrication are classified as various treats to authenticity. They involve protecting the legitimate nodes from outsider's infiltrating the network with false identity.

Threats to confidentiality states the messages transferred between the nodes are vulnerable as the intruder listen and gather the information of a user without their knowledge and perform attacks by violating the privacy of the users. Common attacks such passive eavesdropping or active impersonation targets our interest in identifying the impersonator.

Collecting the information of a given vehicle, by putting the owner's privacy at a great risk. The same case can be applied on location tracking, by studying the location of a vehicle at a certain moment of time or certain path is considered as violation of privacy. Thus by observing the various attributes of a vehicle, the driver's information is gathered for n numbered of vehicles. In cases where bypassing non-repudiation, the two parties share the same credentials. This attack is classified as impersonation attack.

Chapter 2

Methods

Usually the vehicle can be compromised by either trusted relationship or by impersonation of a person. By posing as legitimate users in the network, outsiders can attack the network by sending false messages [1]. The attacker may construct a profile of a vehicle by observing the various services used by the user regularly at various time and location, thus by gaining the traffic information; the attacker can appear it as an emergency vehicle to carry out attacks. These attacks are known as impersonating attacks or masquerade attack [7].

Impersonating the user involves the attacker to generate many identities to simulate multiple nodes for transferring messages, to the neighbouring nodes. This kind of attack is known as Sybil attack. The node is considered suspect, when it's position or identity mismatch with the evaluated one. Generally by creating false gps co-ordinates in the message, Sybil attacks can be implemented.

Impersonation can be prevented by two factor authentication, such as physical token which is assumed that it cannot be stolen and the other this is encrypted data which is sent via the channel. Other traditional way for preventing the attacks is by including authentication techniques. The idea is the nodes which join the network should be authenticated. Authentication is provided by either symmetric or asymmetric cryptographic operations. The involvement of keys in the network and the key management give rise to Certification authority and Kerberos

Tracking systems

For measuring the movement of vehicles, there are various tracking systems, which can be installed in the vehicle and can be tracked by third party applications. Most commonly used tracking devices are Global positioning system (gps). The Gps based vehicle tracking systems is used in asset management or fleet management functions. Gps satellite system is built by the government and makes the system available in cheaper way to use. The movement of vehicles is monitored by Gps satellite and it's reported to the cellular tower which uses GSM/GPRS network for the data transfer. These data are made available to the server, which can be viewed by the user through web services. Many organizations with the large fleet of vehicle wanted to monitor the presence of their vehicle.

The security is Vanet is considered to be in a vital role, thus ensuring the transmission comes from the trusted source and not tampered by others.

It is assumed that every vehicle is equipped with some computational resources. There are certain attributes of the user which are taken into consideration. The most common things like on-board information, driving behaviour of the driver like his driving style; POI'S, AOR (Area of Relevance) [16], polygon geo- fencing, speed and idle times are monitored. Each vehicle is assumed to carry out certain operations like time stamping and auto check in's to record their identity. By integrating the security systems, the position coordinates sent by the gps device, will be logged at periodic intervals. Thus they can keep a regular check on the location of the vehicle. The watchdog mechanism in Manet's used to monitor the dropping of packets to the next node. The system actively monitors the dropping packet by a node, whether it exceeds the threshold level, if any miss appropriate happens within it, it is considered as misbehaving node. Here each node is responsible for monitoring the other node and report their status.

The type of data recorded from the gps device is the NMEA data. The basic messages received from the vehicle may tell about its current position and time of that particular vehicle. Vehicles are solely responsible for providing their location information and thus impersonation can be made impossible [1]. Thus vehicle is responsible to the legitimate users while disseminating messages. These kinds of messages are used for attacking a vehicle and for other various purposes.

It's assumed that the adversary is considered to simulate multiple entities.

These messages transferred between the systems might be altered or hacked by certain adversary, by stealing the identity of other individual. Our case is to prove the adversary, who stole the identity is a wrong person when they started appearing in different places.

Security requirements in Vanets

Here the major concern depends upon security and private issues such as identity legitimacy, privacy preservation, data integrity and non-repudiation [2]. Each vehicle has its unique identifiers. In liability, the sending vehicle should need to prove its identity for authentication purposes.

Privacy preservation in the vehicles is attained from the two factors such as untraceability and unlinkability[15]. The action of each vehicle should not be traced back and the identity should not be linked with linked with any other vehicle,

Non-repudiation marks a major role, by making it impossible for an entity of not denying or sending messages.

In confidentiality the messages are only read by the authorized members, while in availability, each node should be in a state of sending messages at any time. Finally data should maintain the trust by fulfilling the terms of data integrity and accuracy. Falsified data may lead to disaster situations and this is the reason, why the Vanet should follow all the security requirements.

Messages sent by the individual should contain digital signature. The digital signature is verified with the public key provided from the CA. In some cases, the digital signature doesn't guarantee non-repudiation. Other significant approaches like biometric information can be combined with digital signature, to make it difficult to repudiate [3].

Vanet Security Architecture

The key management is the core for security of applications. They are responsible for both key distribution and key revocation. (Trusted third party) TTP provides the management service and PKI ensures about confidentiality, authentication and non repudiation. It starts with PKI starts distributing the public keys to all the nodes the network and CA is responsible for the distribution of public and private keys.

Vanet is subjected to identity based attack, such as impersonating a user. Such kind of attack is solved by PKI. In the PKI system, the sending vehicle which sends the message has its public and private key of its own. Similarly the receiving vehicle holds both the pair wise key. The certificate of both the vehicle is mainly used in authentication and also lets to know who has sent the message. The certificate of the public key of the vehicle contains signature of the CA's private key along with public key of the vehicle and CA's ID.

Figure 2.1: General PKI Architecture

The key distribution also involves registration, initialization, certificate and key update. Registering involves, registering the user with name and other personal details where the user are certified by using CA certificate and public-private key generated by the user. The key has date of issue and other details. Each vehicle node will perform the actions such as, Registering itself with the CA at time of purpose, thus by obtaining a unique ID in form of electronic license plate and public private key pairs [5].

The CRL s also known as public key is hosted by the CA. This CRL s is updated, whenever the certificates are updated or revoked.

The user authentication is done by CA. To verify the authenticity of the user, while messaging to the neighbouring nodes, messaging authentication is done. This process helps in validating the identity of the sender and also helps in protecting the integrity of the message, thus preserving non-repudiation. Signature and the code are sent along with the message. Authentication services like X.509 certificate is used create and modify certificates. For preserving user's privacy the certificates needed to be changed from time to time.

Authenticating the user, using private key doesn't actually tells who has created the message. Therefore hashing functions are used along with the message to condense the length of the message. The advantages of the hashing functions are their transmission through one way functions. It's also known as Message digest or Compression function, because it takes the variable-length input string and converts into a fixed length binary sequence. Digital signatures are chosen for messaging authentication.

Digital signatures are preferred over symmetric authentication mechanisms, here the messages are sent to the receivers as soon as possible and the handshake is not possible. The messages are not only identified with their signatures but with the help of hashing functions. SHA1 and MD5 are widely used one way hash functions. When the hash is employed with cryptography it serves as additional functions. By Combining Certification and Session keys the sender can be identified.

Authentication is the ability to claim the node, by introducing them to the system by telling, whom they are and what they have. If the message is said to be authenticated, they must contains details such as User ID, Electronic License Plate, and Time stamp. These messages are encrypted with the public key. Later the CA signs the message with the encrypted key, to allow both RSU and TPM (Trusted Platform Module) to identify the authenticity of the message. TPM is basically a hardware mounted in the vehicle with cryptographic capabilities which protect the data by generating RSA keys and verifying signatures. Usually the embedded credentials are signed up by the manufacturer. The challenge response protocol in the car checks for the nearest cars temperature and location and challenges for its neighbouring cars.

Here the Digital certificates play a major role while helping in protecting against vehicle against impersonation attacks. These digital certificates basically contains, the owner's public key, the owner's pseudo name, validate period of the certificate, from the date of issue and other details. This electronic document uses digital signature to combine the public key with an identity. As mentioned earlier, CA has the authority to evict the node and invoke the certificates at any point of time, by placing them in CRL's. If any nodes are assumed to be blacklisted, their information is made available to other vehicles.

Before the vehicle sends the safety message, it signs with its private key and includes CA

V -->*: M, SigPrKV [M][T],CertV [8]

Equation 2.1

V - Sending vehicle

* denotes receivers of the message,

M - Message

T - Time stamp for the message freshness

The receivers of the message will verify the public key and signature of V from its certified public key which is obtained from CA.

Detection and Localization of the nodes

In detection mechanism, the physical location of vehicles is compared with the location it's claimed to be. It should be difficult for two different vehicles of same identity, to pass though same RSU at the same time. By comparing the timestamps of a given vehicle from different RSU could possibly locate the position of the vehicle in a given region. If the adversary tries to send any warning messages and imitate as an original vehicle, it's time stamps are compared by the nearest RSU's and the traces are compared. If the traces match with its previous time stamps, the vehicle is said to be authenticated.

In our protocol we check the identity and the behaviour of the user. By combining session keys and digital certificates, each individual can be identified.

Driving pattern of a driver 2.png

Figure 2.: Original User's travelling pattern in his primary location.

save1.png

Figure 2.3: Original User's travelling pattern in his primary location with extra check-ins.

Driving Pattern of different driver.png

Figure 2.4: User's travelling pattern impersonating the primary user.

For example, if a user tries to send a message and imitate an original user. The nearest RSU will look for the user's timestamp's and compare with its earlier records. If there is any immediate jump in the latitude or longitudes, the vehicle is suspected as adversary and all its CRL's are sent to CA, thus passing the information of the adversary to other vehicles.

Chapter 3

Results

Two way of identity mechanism

3.1) Private and public key mechanism

3.2) Binning and patterns mechanism

Private and public key Mechanism

The security mechanism is basically done by using the identity management information such as electronic license plate and private public key pair.

The driver ID provides the suitable solution to the driver, no matter which part of the system they are assigned to. Driver ID collects and stores all the driving data whilst logging the entire driver's activity. The main advantage of this Driver ID'S is all about accountability and identification. Every vehicle is believed to own their identity, such as vehicle ID. Every time the driver starts up the vehicle, the certain "Access key" is generated by combining both the Driver ID and vehicle ID. Various sectors provide a kind of Driver ID in which the driver is entitled to drive only certain vehicles in the system.

We assume that our network follows the standard PKI system and each vehicle generates its own public-private key pair and the driver is being responsible for the liability of message transaction. For the private key generation, we pass in the instance of keys either through one of the tracking system mentioned earlier. It takes a set of multiple values to generate a key. The maximum length of the private key is assumed to be 16 digits. If the generating key exceeds the maximum digits, the generated Key is considered as void. We also assume the user travels in a particular area quite often and the user's most common visited places are marked as check-in by the vehicle.

The pattern which the user travels quite often will become our area of interest. By fetching the latitude and longitude data for that pattern of the user area and passing the instance of the key generator, we generate unique key for that user. By considering the running time and parking time of the vehicle, we can eliminate the duplicate records of the user. The key generator produces a key, which we remains the private key for that user. This access key is generated within the vehicle.

Example:

Latitude

longitude

user access key

56.6587220

56.6597900

56.6604920

56.6609730

12.8965280

12.8957920

12.8958800

12.8957880

USRSAT01

USRSAT01

USRSAT01

USRSAT01

Figure 3.1

The key generator will generate AT01206500572058

Binning and patterns mechanism

The vehicle is assumed to travel in the places, where Road side units are installed. To identify the vehicle travelling in its same region, we are in need to store the latitude and longitude of the vehicles. The vehicle can reach the same location multiple times, thus we can determine the vehicle's regular route and it's unique path. So we are in need to create patterns.

Binning Technique

Binning is a way to group a number of more are less continues values into to a similar number of bins. For example if you have data about group of latitude and longitude. You might want to arrange group of latitude and longitude into similar number of latitude and longitude intervals it can also temporarily grouped and create a bins.

Binning is a way point - based data conversion. This data conversion design only gives a general arrangement of objects and class. Modifying point data is to create an interpolated surface though this predicted data values are calculated for the areas where points do not exist, converts data to a raster surface and can modify the data to a greater extent than desired. The point - based data design pattern only gives a general arrangement of objects and classes involved in the solution of a general problem. This solution has to be tailored and adapted to the problem actually solved.

For representing the point-based data, we aggregate the datasets into polygons. We need to modify the large scale of data in obtained in a certain region. The aim is to avoid the mash up of data across a range of various scales. Data binning a great choice in mapping the point based data, by converting them into polygons. The mapping of data is created by viewed as closest zoom level. Web maps provide a way to visualize the data at various scales. The multi scale environment for processing the data is a way great to represent, classify and symbolize the data at each scale [11].

Mobility of the user

For studying traces of different travelling behaviour of drivers, we set our experimental purpose in collecting data's (GPS Traces) through the mobile phone with enabled 3G connection and its location services turned on. The result which we obtained is the trajectories of data's from the starting location to the end, where the data's are meant to be recorded. The final form in collecting the data resulted in data-time values that are recorded for each and every person [10]. Simplifying these data's by considering different alternatives in representing the best approach was the most challenging thing to us. By considering the two factors, Exploration and Preferential return [9]; we made the assumptions of a particular user. Exploration is about, we could observe the person's trajectory, regardless of not considering the user's vicinity such as their home/workplace. The preferential return is the places which they visits quite often and the check-in's which are made from these places. These places are most often regarded as the commonly visited places by a user. Further the obtained data is solved binning techniques.

Binning

Binning the data is more like organizing the data into groups, which are known as classes. Binning data is been 'classified' and thus some level of data analysis is taking place in it, which means that the data is no longer raw. A data class is a group of data which is related by some user defined property. For example, if you were collecting the place of the driver who has travelled through the country, we could group them into classes as those in their town, city, market, schools and so on. Each of those groups is called a class.

representation 1.jpg

Figure 3.2: Representation of data in a form histogram format.

representation 2.jpg

Figure 3.3: Representation of data in histogram format with different intervals.

Each of those classes is of a certain width and this is referred to as the Class Interval or Class Size. This class interval is very important when it comes to drawing Histograms and Frequency diagrams. All the classes may have the same class size or they may have different class of varying sizes depending on how you bin your data. The class interval is always a whole number.

Instead of displaying all data values individually on a map, we can bin them and represent as an output. Binning involves grouping individual data values into one instance of a graphic element. A bin may be a point that indicates the number of clusters in it. It may be also a histogram point which indicates the places of driver travelled like below image.

Histogram .jpg

Figure 3.4: Representing clusters on a map, where the places of the driver travelled.

Creating Patterns

A Pattern is a formal approach in describing a design problem and any other factors that might affect the problem or the solution. A successful pattern should establish itself for leading a good solution. In our approach we create a map, by placing our recorded data. We are tracing different driver travelling behaviour. The travelling might be the time, the user stay between the times of certain intervals. If the driver travels some different routes but same latitude and longitude in the sense it is considered as the same track. So we needed to create sketches, with one or more alternatives.

To create patterns we are using binning concepts. The simple example shows how a data model, contains a lot of the same sort of information. In this way having a mapped, we get the abstract not only the mapping but the communication with the data domain; however we need to write a mapped class for each type. While for analyzing the Geographical data, the data should be binned for analysing it. In Cartesian product, the space is divided into x and y squares, the geographical equivalent is to bin up the data in equal latitude and longitude squares. The main reason behind this is both in arctic and Antarctic poles; the longitude tends to converge at their ends. In binning concept, each bin has the same angular measurement in both latitude and longitude.

Binning of data.jpg

Figure 3.5: Representing polygons of data through binning.

Here in binning concept large data sheet of data are stored in to database. This data (latitude and longitude) is read from database and converted into many hexagonal polygons. Now we have a latitude/longitude coordinate point and we draw a polygon (hexagon) around it on a Google map. Here's the code to calculate the hexagon coordinates:

For (var i= 0; i< 6; i++)

{

x= lat+ r* Math.sin(i* 2 * Math.PI/ 6);

y= lon+ r* Math.cos(i* 2 * Math.PI/ 6);

}

Equation 3.

This calculates all coordinates in a regular hexagon and we can draw it on the map without any problem, even if its centre is near (0 lat, 0 lon). Usually the raw data obtained from the user will be large amount of geographical patterns, but we need the data to be represented to explore patterns in it. By identifying the point based data into regular polygons and making the aggregation of data to fall into it.

The attributes of the user can be considered as the time interval which the user spends between the travels on any given day.

The regular route is represented in the form of nodes, obtained from different latitude and longitude along the route. If the user travels in the same latitude and longitude, a pattern is created from it, considering the regular check-in's made by the user. The cluster of nodes determines the counts made by the particular user in a given location. The other way of saying it is the total number of counts, represents the frequently visited places by the user. Any given node on the map will help us to track the identity of the place, visited by the user.

For this process we have created a table and store the user records into a database.

While reading the data from the runtime, various patterns will be generated for each user. If any anonymous user claims to own the place, with the same latitude and longitude as of the Original user, the trace of the new user can be compared from his earlier check-ins and other attributes.

Let say for example, the user A has 4 traces of his path, while the user B has only two traces, the maximum number of trace count is considered as primary route for that user.

Binning of data 2.jpg

Figure 3.6: traces of two different users on a map

Chapter 4

Conclusions

This paper has briefly introduced the various attacks in vehicular networks. We presented two concepts such as binning and public-private key mechanism for determining and eradicating the adversary who pretends to be of original user.

Appendix

Proofs of theoretical results could be given here. If the results are based on computer programs written by the author, then the program code should be presented here.

Notation

Lat

Starting point of X

Lon

Starting point of Y

i

Distance in Number

PI/6

Return Angle, in degrees, in range -180 to +180

(i* 2 * Math.PI/ 6)

Converts the radian number to the equivalent number in degrees

Acknowledgments

We would like to thank our parents and friends for our continuous support.

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