Need and Challenges of Driving License Authentication Using Biometrics

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1 Need and Challenges of Driving License Authentication Using Biometrics Divya Gangamwar Akash Bande Pallavi Gaykar Dr. Nilesh J Uke Professor, ABSTRACT License authentication is a very difficult task for the government to monitor, now a days. To check non-licensees as of driving, the very unfailing person recognition system is biometric verification. Biometrics studies commonly include fingerprint, face, iris, voice, signature, and hand geometry recognition and verification. Among these available biometric traits fingerprint proves to be one of the best traits providing good mismatch ratio and also reliable. Our proposed system consists of a smart card capable of storing the finger print of a particular person. While issuing the license, the specific person s finger print is to be stored in the card. At the time that person s details are fully stored in that database. Cars will be having the reader capable of reading the particular license. The similar vehicle should have the capacity of fingerprint reader component. A man, who is going to drive the vehicle, should keep the thumb on the scanner in the vehicle and then swipe his/her card. If the fingerprint stored in the module and fingerprint stored in a card swiped in the device matches, he/she can drive the vehicle, or else ignition will not work. So that system increase the safekeeping of vehicles. The grand challenge in the system is biometrics recognition,which is based on distinctive personal traits but has a potential to become an irreplaceable part of the system. Keywords License Authentication, Biometric, Fingerprint Recognition, Driver Support System INTRODUCTION The advancement in the field of transportation leads to the increase in number of road users. Yet, the threat of road accidents is fast increasing in parallel to the count of vehicles on road [5]. One of the causes for road accidents is the unlicensed drivers on road.the rate of accidents caused by unlicensed drivers on road is found to be increasing as days go by. The another scaring issue is that drivers who are not eligible to hold a license drive the vehicle.6 out of 10 This may include suspended or revoked licenses else expired or cancelled or denied licenses. The verification of drivers on road individually is not an effortless process, rather on scanning the globalization process; it is quite a hard-hitting process. Considering the above mentioned scenarios it can be realized that there is an urge in need of a system which prohibits, a. Unlicensed drivers using vehicles on the road b. Driving a vehicle when the safety precautions viz, helmet and seat belt are not worn. The Table 1 shows the Historical evolution of vehicle ownership.[3] Table 1: Statistics of cars per 1000 people 398 Divya Gangamwar, Akash Bande, Pallavi Gaykar, Dr. Nilesh J Uke

2 BACKGROUND WORK Recently, different rule based methods are introduced by many researchers to authenticate the driver using biometrics. Driving license system is a very difficult task for the government to monitor. In this project, all the citizens images will scan and recorded. Whenever a citizen crosses the traffic rules, the police can scan his image and can collect fine from the defaulter. Using this method, the police can track the history of the driver. we can prevent the non-licensed person from driving. It consists of a smart card capable of storing the finger print of a particular person. While issuing the license, the specific person s finger print is to be stored in the card. At the time that person s details are fully stored in that database. So that anywhere the person should place on his finger on the finger print reader. That person s entire information will be displaying. The another system uses Iris Scanning technology of biometrics which is evident to be a more reliable one. Using a helmet (for two wheelers) and a glass (for four wheelers), the iris pattern of the driver is continuously scanned and processed by a specially designed system. A smart driving license which is embedded with the iris pattern of the driver is already inserted in the provided system. 1. In paper [1], they have used the Finger print authentication scheme which is a non-imitable biometric authentication scheme. By using this biometric authentication, it is possible to prevent the non-licensed person from driving. The proposed system consists of a smart card of EMV type capable of storing the finger print of a particular person. While issuing the license, the specific person s finger print is to be stored in the card. At the time that person s details are fully stored in that database. 2. In paper[4],they have used FIM 3030N high voltage module as a scanner. This module has in-built ROM, DSP and RAM.This module can operate in 2 modes they are Master mode and User mode. They have used Master mode to register the fingerprints. And in user mode they are verifying the scanned images with the stored images. 3. In paper[2], a novel approach which overcomes the drawbacks of existing verification methodologies is proposed. The method uses Iris Scanning technology of biometrics which is evident to be a more reliable one. Using a helmet (for two wheelers) and a glass (for four wheelers), the iris pattern of the driver is continuously scanned and processed by a specially designed system. A smart driving license which is embedded with the iris pattern of the driver is already inserted in the provided system. The novelty of the proposed design is that the engine of the vehicle opens only when the iris pattern of the driver matches with the pattern in the license. When a mismatch occurs the engine shuts down itself. As the pattern is continuously scanned, a license cannot be used by another personality. Many researchers are working on providing efficient driver support systems that help drivers react to changing road conditions can potentially improve safety, which is the key goal in intelligent vehicle development [6]. Many applications which helps commercial drivers are in place to ease out their driving skills like Road Sign Detection [7,11], measuring real time traffic [8,12], drowsiness detection [6], Real time lane detection [9,10] etc. PROPOSED SYSTEM Our system architecture consists of many different modules.mainly,there are two phases in the system. In each of the phases the users comes across different processes. Various Phases of our proposed architecture are given in Figure No User enrollment In user enrollment,the user is supposed to register the data while going through the license authentication process. This enrolled data is then stored in the RTO database which will used for further authentication of driver. The user Enrollment phase includes the following modules 1.1 User s personal data with biometric details In this module user has to provide his general details which already exists in the license process and add-on to it the user has to provide his biometric details(let us consider fingerprint sample of the user).the fingerprint is taken while issuing the license. 399 Divya Gangamwar, Akash Bande, Pallavi Gaykar, Dr. Nilesh J Uke

3 Fig 1: System Architecture Input device To collect the biometric information many input devices are needed through which we are going to take inputs of the user. There can be different input devices. In our proposed architecture we will be needing Fingerprint scanner and computer GUI. 1.3 Database This is very important module as it will be containing the information about biometric information of the licensee. Each and every details are stored here, and when needed the data will be retrieved from the database. 2. User Authentication This phase is for verification or authentication of the user. It contains different modules. The modules in this phase are 2.1 Input device While authentication of user again the different input devices are required. In user authentication phase according to our requirements we need fingerprint scanner and license card reader. 2.2 Extracting features This module involves extracting the biometric information that is features which are required for authentication. The features includes the details of license and the fingerprint sample. So it extracts the features from the database. 2.3 Check license authentication After extracting features of the user from the database it checks for the enrolled data and authenticated data. The response is given by the database. And Even the input is taken after random time and verifies it continuously. There can be 2 cases Successful authentication : If the authentication becomes successful then it permits the drive to ignite the car. Unsuccessful Authentication :If the authentication is unsuccessful then the system restricts the driver to ignite the car. Swim lane diagram of license authentication using biometrics The swim lane diagram of license authentication illustrated in figure 2 is described as follows: 400 Divya Gangamwar, Akash Bande, Pallavi Gaykar, Dr. Nilesh J Uke

4 Figure 2: Swim Lane Diagram There are mainly three actors in the swim lane diagram. That are 1. Driver : Lane 1 Step 1 : Driver enters in the car. Step 2 : Keep your finger on fingerprint scanner. 2. Car : Lane 2 Step 1 : Driver inserts the smart card in card reader. Step 2 : The car scanner takes input from the database. Step 3 : It sends license details and biometric data to RTO Server. 3. RTO server : Lane 3 Step 1 : The RTO server verifies license. Step 2 : If verification is successful then permission is given to driver to start ignition. Step 3 : If verification fails then takes precautionary actions against driver. CHALLENGES IN AUTHENTICATION USING BIOMETRIC (1) Biometric Sample Recovery : In this case, the goal of the adversary is to determine a fresh biometric template which is accepted by the authentication server. The consequences of a successful attack are similar to the reference recovery attack, apart from the fact that the produced matching template may differ from the user s real one, and so the adversary can recover less information regarding the user s private information (e.g., physical characteristics and DNA). (2) Biometric Reference Recovery : A non authorized party (usually called the adversary) succeeds in recovering the (plaintext) reference biometric template. This is the most harmful threat since by recovering the reference template the adversary may gain unauthorized access to any system that uses as a reference template and also collect sensitive information about the user s physical characteristics and health. (3) User s Traceability: An unauthorized party (e.g., the adversary) is able to trace a user s authentication attempts over different applications. Consequences of a successful traceability attack are cross-matching, profiling, and tracking of individuals. 401 Divya Gangamwar, Akash Bande, Pallavi Gaykar, Dr. Nilesh J Uke

5 (4) User s Distinguishability : The adversary recovers the link between a biometric template, or, and a user identity. Compromising this relation may lead to the disclosure of more sensitive information and often breaks the anonymity of the system. CONCLUSION This project is undertaken to design and develop a system which is able to authenticate the driver using license before ignition of a car, such that on using the proposed system the rate of accidents can be considerably reduced and non licensees on the road can also be eradicated. REFERENCES [1] Priyadarshinee Patnaik D. Archana Thilagavathy, Prasanna R. and Rama P. Finger print based license authentication scheme for indian scenario: A review. Archives of Applied Science Research, 7(5):49 53, [2] L. L. Laudis, A. K. Sinha, P. D. Saravanan, and S. Anand. Fpga implementaion: Smart card based license management using iris scanning approach. In 2014 International Conference on Science Engineering and Management Research (ICSEMR), pages 1 5, Nov [3] NDTV. [4] J. A. Rubella, M. Suganya, K. Senathipathi, B. S. Kumar, K. R. Gowdham, and M. Ranjithkumar. Fingerprint based license checking for auto-mobiles. [5] Wikipedia1. [6] Nilesh J. Uke, Dr. RC Thool, Drowsiness Detection A Visual System for Driver Support, International Journal of Electronics Communication and Computer Engineering (IJECCE), Impact Factor 1, Volume 3, Issue 2, pp , March [7] Nilesh J. Uke, Ravindra C Thool, A Vision Based Driver Support System for Road Sign Detection, Int. J. on Recent Trends in Engineering and Technology, Vol. 10, No. 1, Jan 2014, pp [8] Nilesh J. Uke, Dr. RC Thool, Moving Vehicle Detection for Measuring Traffic Count Using OpenCV, Journal of Automation and Control Engineering (JOACE), ISSN: , Volume 1, No. 4, 2013, pp [9] A. A. Assidiq, O. O. Khalifa, M. R. Islam and S. Khan, "Real time lane detection for autonomous vehicles," 2008 International Conference on Computer and Communication Engineering, Kuala Lumpur, 2008, pp [10] H. Wu, Y. Liu and J. Rong, "A Lane Detection Approach for Driver Assistance," 2009 International Conference on Information Engineering and Computer Science, Wuhan, 2009, pp [11] G. A. Tagunde and N. J. Uke, Detection, classification and recognition of road traffic signs using color and shape features, International Journal of Advanced Technology & Engineering Research, vol. 2, no. 4, pp , [12] Nilesh J. Uke, Dr. RC Thool, Moving Vehicle Detection for Measuring Traffic Count Using OpenCV, Journal of Automation and Control Engineering (JOACE), ISSN: , Volume 1, No. 4, 2013, pp Divya Gangamwar, Akash Bande, Pallavi Gaykar, Dr. Nilesh J Uke