Fingerprint Identification Keyless Entry System
Abstract
Nowadays, keyless entry systems are widely adopted for vehicle immobilizer systems due to both advantages of security and convenience. Keyless entry systems could overcome brute-force key guessing attack, statistics attack and masquerade attack, however, they can't prevent from thieves stealing behavior. In this paper, we proposed a new architecture try to improve the existent flaws. The integration of the keyless entry system and the fingerprint identification technology is more suitable to implement on the portable transponder to achieve higher security needs. We also adopt and modify AES security protocol for life expectancy and security of the portable transponder. In addition, the identification of a driver's fingerprint makes the service of automatic reinstatement of a driver's preferences become possible. Our design can satisfy not only the three kinds of previous illegal attacks, but also the stealing situation. Furthermore, many practical factors, such as costs, life expectancy and performance, have been well considered in the design of portable transponder.
Keywords Keyless entry-system, fingerprint identification, AES security protocol, vehicle immobilizer system.
I. INTRODUCTION
CURRENTLY there are three ways to enter your car and start the engine, and they are mechanical key-lock system, remote keys system and keyless entry-system. However, either way, the driver has to have a key for the car to recognize. At present, for the security design of car keys, encryption with radio communications is most commonly used to prevent brute- force key guessing attack, statistics attack and masquerade attack. The key that a driver carries may be stolen or picked up by someone after it is lost, creating a security breach for theft prevention. In addition, the verification with a driver’s key does not guarantee that the key holder is really the driver. Therefore it is impossible to provide the service of automatic reinstatement of a driver’s preferences.
Biometric identification provides solutions for the above problems. Biometric identification identifies by using the biological features of a driver as the basis of identification, thus reducing the risks of theft or loss of property due to driver’s negligence. In addition, the biometric features of every driver are perfect for driver identification, or even for automatic reinstatement of a driver’s preferences in the future as they are unique to the driver him/herself. So far there are many ways of biometric identification, such as fingerprint, face profile, iris, palm print, voice, vein and multi-pattern identification. According to International Biometric Group (IBG), AFIS/Live-Scan accounts for the highest share in biometric identification market in 2007 with 33.6%, followed by fingerprint ID (25.3%), face profile （12.9%), intermediate software (5.4%), iris ID (5.1%), palm print (4.7%), voice (audio) (3.2%), vein patterns (3.0%), multi-pattern ID (2.9%) and other types of identification (4.0%). Among all, AFIS/Live-Scan and fingerprint ID account for 58.9% of all identification methods. It is clear that fingerprint ID has become the mainstream of biometric identification. The reason is that it costs less and requires less calculation compared to other types of biometric identification, thus more acceptable in the market.
In this study, fingerprint identification is integrated in keyless entry-systems. Integrated with fingerprint identification, keyless entry-systems are able to prevent brute-force key guessing attacks, statistics attacks, masquerade attacks and thief stealing attacks. Also, drivers’ fingerprints are adopted for driver identification in order to provide the automatic reinstatement of a driver’s preferences.
Ⅱ.BACKGROUND INFORMATION
A. Fingerprint Identification
Fingerprint identification has been widely used in our daily life. The most commonly seen adaptation is on laptop computers, where fingerprint identification has been adapted in place of entering personal password on keyboard. Another adaptation is mobile personal device, such as USB flash drive or cell phone. It is also fairly common to see a security system at a dormitory and residence using fingerprint identification. For the use of fingerprints for identification, the following procedure is introduced :
- In the fingerprint acquisition phase, the gray-scale images of fingerprint are obtained from fingerprint sensor. There are several types of fingerprint sensors, for example, optical sensors, capacitance-based silicon sensors, thermal silicon sensors, and ultrasonic sensors. At present, the most popular ones in the market are capacitance based silicon sensors. The capacitance-based silicon sensors use minute electric current signals to simulate the epidermis, and store the changes in electric signals using tightly packed matrices of capacitors all over the surface of sensors. The distance between the skin and the sensor surface differs between ridges, which directly touch the sensor surface, and valleys, which are separated by an air gap from the sensor surface. This difference in distance causes a difference in capacitance, which is measured by the sensor and finally results in an image describing the contours of the fingertip.
- In the fingerprint image pre-processing phase, it is to normalize the data and apply filters to remove the distortion introduced by noise, manufacturing tolerances and environmental conditions.
- In the fingerprint feature extraction phase, fingerprints are converted into feature values, and it has to be ensured that different fingerprints do not generate the same value. The algorithm looks for minutiae in
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