基于密码身份验证协议和多生物特征识别技术的下一代电子护照方案(IJIEEB-V5-N2-6)

I.J. Information Engineering and Electronic Business, 2013, 2, 34-43

Published Online August 2013 in MECS (https://www.wendangku.net/doc/d210431621.html,/)

DOI: 10.5815/ijieeb.2013.02.06

Next Generation Electronic Passport Scheme using Cryptographic Authentication Protocols and Multiple Biometrics Technology

V.K. Narendira Kumar

Assistant Professor, Department of Information Technology, Gobi Arts & Science College (Autonomous),

Gobichettipalayam – 638 453, Erode District, Tamil Nadu, India.

Email ID: kumarmcagobi@https://www.wendangku.net/doc/d210431621.html,

B. Srinivasan

Associate Professor, PG & Research Department of Computer Science, Gobi Arts & Science College (Autonomous), Gobichettipalayam – 638 453, Erode District, Tamil Nadu, India.

Email ID: srinivasan_gasc@https://www.wendangku.net/doc/d210431621.html,

Abstract—Electronic passports (e-passports) are to prevent the illegal entry of traveller into a specific country and limit the use of counterfeit documents by more accurate identification of an individual. The e-passport, as it is sometimes called, represents a bold initiative in the deployment of two new technologies: cryptography security and biometrics (face, fingerprints, palm prints and iris). A passport contains the important personal information of holder such as photo, name, date of birth and place, nationality, date of issue, date of expiry, authority and so on. The goal of the adoption of

the electronic passport is not only to expedite processing

at border crossings, but also to increase security. The paper explores the privacy and security implications of this impending worldwide experiment in biometrics authentication technology.

Index Terms— Biometrics, Cryptographic, Electronic Passport, Face, Fingerprint, Palmprint, Iris.

I.INTRODUCTION

An electronic passport (e-Passport) is an identification document which possesses relevant biographic and biometric information of its bearer. It also has embedded in it a Radio Frequency Identification (RFID) Tag which is capable of cryptographic functionality. The successful implementation of biometric technologies in documents such as e-Passports aims to strengthen border security

by reducing forgery and establishing without doubt the identity of the documents' bearer.

The International Civil Aviation Organization has adopted a global, harmonized blueprint for the integration of biometric identification information into machine readable passports. The purpose of the new biometric passports is to prevent the illegal entry of travelers into a specific country and to limit the use of fraudulent documents by more accurate authentication

of individuals. This study aims to find out to what extent

the integration of biometric identification information into passports will improve their robustness against identity theft.

The International Civil Aviation Organization (ICAO), which plays a major role in setting global travel standards, has adopted a global, harmonized blueprint for the integration of biometric identification information into passports and other machine readable travel documents. The blueprint requires that a high-capacity contact-less integrated circuit containing a raw image file of the holder’s face in addition to other identity information such as name and date of birth be included in the machine readable passports and other travel documents.

The purpose of biometric passports is to prevent the illegal entry of travelers into a specific country and limit the use of fraudulent documents, including counterfeit and modified documents and the impostor’s use of legitimate documents.

The integration of biometrics can provide better verification performance than the individual biometrics. Biometrics will also increase robustness of the biometric systems against the spoofing attacks and solve the problem of non-universality. Since the facial image is the mandatory biometric identifier to be included in the future passports, researcher study focus on the use of the facial image, iris, palm print and finger prints for the identity verification of passport holders. In order of least secure and least convenient to most secure and most convenient, they are [1]:

Something you have - card, token, key.

Something you know- PIN, password.

Something you are - biometric.

The remaining sections are organized as follows: Brief outline of Biometric in the e-passports is presented in section 2. E-Passport methodology is mentioned in Section 3 and logical data structures are in the section 4. The other phases of the implementations of the e-passport protocol are briefly explained in section 5. Experimental results are given in Section 6. Finally, Section 7 describes the concluding remarks.

II.LITERATURE SURVEY

Juels et al (2005) discussed security and privacy issues that apply to e-passports. They expressed concerns that, the contact-less chip embedded in an e-passport allows the e-passport contents to be read without direct contact with an IS and, more importantly, with the e-passport booklet closed. They argued that data stored in the chip could be covertly collected by means of “skimming” or “eavesdropping”. Because of low entropy, secret keys stored would be vulnerable to brute force attacks as demonstrated by Laurie (2007). Kc and Karger (2005) suggested that an e-passport may be susceptible to “splicing attack”, “fake finger attack” and other related attacks that can be carried out when an e-passport bearer presents the e-passport to hotel clerks. There has been considerable press coverage (Johnson, 2006; Knight, 2006; Reid, 2006) on security weaknesses in e-passports. These reports indicated that it might be possible to “clone” an e-passport.

2.1. Purpose of the Study

The primary objective of the study is to produce new knowledge with respect to security of biometric techniques in an e-passport setting. The results of the work should be useful for those making e-passport design decisions with respect to security and biometric technologies in an e-passport setting.

2.2. Statement of the Problem

The purpose of biometric passports is to prevent the illegal entry of travelers into a specific country and to limit the use of fraudulent documents by more accurate identification of individuals. It is interesting to find out to what extent the integration of cryptographic security and biometric identification information into passports will improve their robustness against identity theft.

2.3. Biometric

Biometric technologies are automated methods of recognizing an individual based on their physiological or behavioral characteristics such as face, fingerprints, palm print and iris. Biometric systems are applications of biometric technologies and can be used to verify a person’s claimed identity and to establish a person’s identity [1].

In an ideal biometric system, every person possess the characte r is tic, no t wo p ers ons have the s a me characteristic, the characteristic remain permanent over time and does not vary under the conditions in which it is co llected and the b io met r ic s ys tem res is ts countermeasures. Evaluation of biometric systems quantifies how well biometric systems accommodate the properties of an ideal biometric system. All of existing biometric systems suffer from the same problems: false acceptance and false rejection caused by the variability of conditions at the human-machine interface. A common feature of any system that uses biometric is a trade-off between high security and a more usable system.

2.4. Multiple Biometric Systems

Limitations of unimodal biometric systems can be overcome by using multiple biometric systems. A multiple biometric system uses multiple applications to capture different types of biometrics. This allows the integration of two or more types of biometric recognition and verification systems in order to meet stringent performance requirements. Such systems are expected to be more reliable due to the presence of multiple, independent pieces of evidence. These systems are also able to meet the strict performance requirements imposed by various applications [3].

A multiple system could be, for instance, a combination of fingerprint verification, face recognition, voice verification and smart-card or any other combination of biometrics. This enhanced structure takes advantage of the proficiency of each individual biometric and can be used to overcome some of the limitations of a single biometric. For instance, it is estimated that 5% of the population does not have legible fingerprints, a voice could be altered by a cold and face recognition systems are susceptible to changes in ambient light and the pose of the subject's head. A multiple system, which combines the conclusions made by a number of unrelated biometrics indicators, can overcome many of these restrictions [5].

2.5. Technical Challenges

The electronic passport is secure will prove substantially more difficult than actually securing it biometric technology in passports. It is quite clear, however, that contactless chips offer significant advantages, including larger capacities and lower costs. The technology also has yet to experience widespread deployment in either the private or public sector, though such deployment can be expected in the private sector in the next few years. Contact-based chips simply lack the robustness of contactless technology. A lack of available barcodes, in addition to the fact that RFID is a superior tracking technology compared to virtually any available, has led major retailers like Walmart to investigate inclusion of RFID in its supply chain. As this deployment occurs, RFID may also become an integral part of numerous other everyday tasks, such as entering a place of work or making a credit card transaction.

III.SYSTEM METHODOLOGY

An e-passport bearer presents his/her document to a border security officer who scans the MRZ information in the e-passport through a MRZ reader and then places the e-passport near an e-passport reader to fetch data from the microchip. The current implementation consists of three protocols [7]:

Basic Access Control (BA C) protocol (optional): It provides encrypted communication between the chip and the Inspection System (IS).

Passive Authentication (PA) protocol (mandatory):

A border security officer reads and verifies the

authenticity of e-passport content stored in the chip.

Active Authentication (AA) protocol (optional): It provides integrity verification of e-passport’s data.

The two new protocols that intend to replace active authentication and thus now consists of the following four protocols:

Basic Access Control (BAC) protocol: It facilitates the e-passport and the IS to establish an encrypted

communication channel.

Chip Authentication (CA) protocol (mandatory): A mechanis m to detect cloned e-Passports

Passive Authentication (PA) protocol (mandatory): As in first generation passport standard.

Terminal authentication (TA): Only if all protocols are completed successfully, the e-passport releases

sensitive information like secondary biometric

identifiers. The e-passport performs the collection

of protocols as specified in the first generation e-

passports, therefore providing backward compatibility.

3.1. Biometrics in E-Passports

Biometrics in e-passports complying with the ICA O standard consists of a mandatory facial image and fingerprints. While the former are used by a significant number of countries and thus information on them is widely available, the latter is currently used seldom. Therefore, this section only covers the vulnerabilities of facial images, fingerprints, palm print and iris images [8].

3.2. Face Image

Facial images are the most common biometric characteristic used by humans to make a personal recognition, hence the idea to use this biometric in technology. This is a nonintrusive method and is suitable for covert recognition applications. The applications of facial recognition range from static ("mug shots") to dynamic, uncontrolled face identification in a cluttered background (subway, airport). Face verification involves extracting a feature set from a two-dimensional image of the user's face and matching it with the template stored in a database. The most popular approaches to face recognition are based

on either: 1) the location and shape of facial attributes such as eyes, eyebrows, nose, lips and chin, and their spatial relationships, or 2) the overall (global) analysis

of the face image that represents a face as a weighted combination of a number of canonical faces. It is questionable if a face itself is a sufficient basis for recognizing a person from a large number of identities with an extremely high level of confidence. Facial recognition system should be able to automatically detect a face in an image, extract its features and then recognize it from a general viewpoint (i.e., from any pose) which is a rather difficult task. Another problem is the fact that the face is a changeable social organ displaying a variety of expressions [4]. 3.3. Fingerprint

A fingerprint is a pattern of ridges and furrows located on the tip of each finger. Fingerprints were used for personal identification for many centuries and the matching accuracy was very high. Patterns have been extracted by creating an inked impression of the fingertip on paper. Today, compact sensors provide digital images of these patterns. Fingerprint recognition for identification acquires the initial image through live scan of the finger by direct contact with a reader device that can also check for validating attributes such as temperature and pulse. In real-time verification systems, images acquired by sensors are used by the feature extraction module to compute the feature values. The feature values typically correspond to the position and orientation of certain critical points known as minutiae points. The matching process involves comparing the two-dimensional minutiae patterns extracted from the user's print with those in the template. One problem with the current fingerprint recognition systems is that they require a large amount of computational resources

[2].

3.4. Palm Print

The palm print recognition module is designed to carry out the person identification process for the unknown person. The palm print image is the only input data for the recognition process. The person identification details are the expected output value. The input image feature is compared with the database image features. The relevancy is estimated with reference to the threshold value. The most relevant image is selected for the person’s identification. If the comparison result does not match with the input image then the recognition process i s declared as unknown person. The recognition module is divided into four sub modules. They are palm print selection, result details, ordinal list and ordinal measurement. The palm print image selection sub module is designed to select the palm print input image. The file open dialog is used to select the input image file. The result details produce the list of relevant palm print with their similarity ratio details [1]. The ordinal list shows the ordinal feature based comparisons. The ordinal measurement sub module shows the ordinal values for each region.

3.5. Iris Recognition

Iris recognition technology is based on the distinctly colored ring surrounding the pupil of the eye. Made from elastic connective tissue, the iris is a very rich source of biometric data, having approximately 266 distinctive characteristics. These include the trabecular meshwork, a tissue that gives the appearance of dividing the iris radically, with striations, rings, furrows, a corona, and freckles. Iris recognition technology uses about 173 of these distinctive characteristics. Iris recognition can be used in both verification and identification systems. Iris recognition systems use a small, high-quality camera to capture a black and white, high-resolution image of the iris. The systems then define the

boundaries of the iris, establish a coordinate system over the iris, and define the zones for analysis within the coordinate system [9].

3.6. Biometric System Modules

Enrollment Unit: The enrollment module registers individuals into the biometric system database. During the phase, a biometric reader scans the individual’s biometric characteristic to produce its digital representation.

Feature Extraction Unit: The module processes the input sample to generate a compact representation called the template, which is then stored in a central database or a smartcard issued to the individual.

Matching Unit: The module compares the current input with the template. If the system performs identity verification, it compares the new characteristics to the user’s master template and produces a score or match value (one to one matching). A system performing identification matches the new characteristics against the master templates of many users resulting in multiple match values (one too many matching).

Decision Maker: The module accepts or rejects the user based on a security threshold and matching score. IV.E-PASSPORT LOGICAL DATA STRUCTURE The ICAO issued a standardized data structure called Logical Data Structure (LDS) for the storage of data elements. This was to ensure that global interoperability for e-Passport Tags and Readers could be maintained. The specifications state that all the 16 data groups are write protected and can be written only at the time of issue of the e-Passport by the issuing state shown in table 1. A hash of data groups 1-15 are stored in the security data element (SOD), each of these hashes should be signed by the issuing state.

TABLE 1: Passport Logical Data Structure

Requirements of the Logical Data Structure:ICA O has determined that the predefined, standardized LDS must meet a number of mandatory requirements:

Ensure efficient and optimum facilitation of the rightful holder. Ensure protection of details recorded in the optional capacity expansion technology. Allow global interchange of capacity expanded data based on the use of a single LDS common to all. Address the diverse optional capacity expansion needs of issuing state. It provides expansion capacity as user needs and available technology evolve.

Researcher analyzes e-passport protocols by first identifying their security goals. Researcher assumes that a country implements the highest level of Cryptographic security and multiple biometrics for e-passports.

4.1. Data Confidentiality

Data confidentiality ensures the privacy of e-passport details and encryption is the common technique that provides confidentiality [11]. In the case of e-passport, encryption is used to create a secure channel between the e-passport reader and the microchip. Note that the cryptographic keys used for encryption have to be guarded against unauthorized access (data elements within the LDS or keys stored in the DF).

4.2. Data Integrity

Data integrity prevents against illegal modifications of information exchanged between the e-passport reader and the microchip. Also the DF, SOD and LDS should be secure against any unauthorized modifications, i.e., any data tampering should be easily detectable by the border security centre.

4.3. Data Authentication

Data origin authentication ensure that the source of the transmission in a protocol is authentic, i.e., the data on the chip should be bound to information on MRZ and to the data that appears in the e-passport bio-data page currently being examined by a border security officer.

4.4. Mutual Authentication

Mutual authentication is the process where both participants prove their identities to each other. As in the goal 3, where the e-passport reader authenticates an e-passport, this goal protects the e-passport bearer, as it is crucial for an e-passport to authenticate the e-passport reader before divulging any personal information. This prevents an unauthorized e-passport reader from obtaining biometric and personal details from an e-passport.

4.5. Certificate Manipulation

Certificates acts as an off-line assurance from a trusted authority that the certified public key really does belong to the principal who is in possession of corresponding secret key. However, it is the responsibility of the protocol to validate that the corresponding secret key is actually held by the principal claiming ownership of the public key. The e-passport reader should have a guarantee that certificates presented by the e-passport are valid and match the data on the e-passport. ICA O has implemented a PKI which

would store signature certificates from issuing state and organizations.

V.IMPLEMENTATION OF E-PASSPORT

SYSTEM

In order to implement this electronic passport system using cryptographic security and multiple biometrics technology efficiently, https://www.wendangku.net/doc/d210431621.html, program is used. This program could speed up the development of this system because it has facilities to draw forms and to add library easily. There are three ways of doing authentication and authorization in https://www.wendangku.net/doc/d210431621.html,:

Windows Authentication:In this methodology https://www.wendangku.net/doc/d210431621.html, web pages will use local windows users and groups to authenticate and authorize resources.

Forms Authentication:This is a cookie based authentication where username and password are stored on client machines as cookie files or they are sent through URL for every request. Form-based authentication presents the user with an HTML-based Web page that prompts the user for credentials. Passport Authentication:Passport authentication is based on the passport website provided by the https://www.wendangku.net/doc/d210431621.html,. So when user logins with credentials it will be reached to the passport website where authentication will happen. If Authentication is successful it will return a token to your website.

Anonymous Access: If you do not want any kind of authentication then you will go for Anonymous access. 5.1. E-Passport Authenticate

Figure 1 shows the different entities involved in authenticate with e-Passport scenario and the traffic that is exchanged between them. A TCP connection from the e-Passport to the user is created as soon as the user loads the login page. In the current implementation this is accomplished by placing an https://www.wendangku.net/doc/d210431621.html, owned by the identity provider on the web page (to be more precise, what is placed on the web page is an HTML tag linking to code on the web server). The website is signed by the identity provider and also loaded from the passport web server so that the Runtime Environment at the user’s client trusts this piece to allow it to set up a connection back to the passport server. The website was given permission to connect to the contactless reader in a passport policy file which was installed during enrollment. The TCP connection is used for subsequent communication between the identity provider and the user’s e-Passport.

Using the managed passport acquired during enrollment the user can attempt to login. One extra step is taken by the identity provider after receiving a token request from the client. In this extra step the identity provider checks if the user has a valid passport and it reads the user’s details from the passport. As soon as the client actually requests a token at the identity provider, the identity provider will look at the provided token and send the appropriate BA C data to the passport authenticating the identity provider at the passport. The identity provider will request the e-Passport’s AA public key and SOD. With the SOD it can check if the public key has been signed by the issuing country. It can then send a random challenge to the e-Passport which encrypts it using the AA private key. This proves that the passport is authentic and not a simple clone. The identity provider will request the minimal needed information from the e-Passport to confirm to the token request. The token is sent back to the client and from here on the normal Information scenario continues [6].

To summarize, the identity provider uses BAC, AA, and PA and then reads Data Group. Based on the results of the security protocols the identity provider knows that the information in Data Group correctly identifies a citizen of the issuing country (for as far as the identity provider trusts the country’s CSC, of course). Remember that Data Group contains basic textual card holder information (name, date of birth, date of expiry of document, document number, gender, nationality, and in the case even the citizen ID). The information in this data group is used in the token created by the identity provider and only the required fields (as requested by the relying party’s policy) are sent to the relying party (via the user’s client). No other information is sent to the relying party and the relying party needs to trust the identity provider that it has done its job in checking the validity of the user’s e-Passport.

5.2. E-Passport Initial Setup

All entities involved in the protocol share the public quantities p, q, g where:

p is the modulus, a prime number of the order 1024 bits or more.

q is a prime number in the range of 159 -160 bits.

g is a generator of order q, where Ai < q, g i ≠ 1 mod

p.

Each entity has its own public key and private key pair (PK i,SK i) where PK i = g(SK i) mod p

Entity i’s public key (PK i) is certified by its root certification authority (j), and is represented as

CERT j(PK i, i).

The public parameters p, q, g used by an e-Passport are also certified by its root certification authority. 5.3. Phase One – IS Authentication

Step 1 (IS) When an e-Passport is presented to an IS, the IS reads the MRZ information on the e-

Passport using an MRZ reader and issues the command GET CHA LLENGE to the e-Passport

chip.

Step 2 (P) The e-Passport chip then generates a randomeP ￡ R 1 ≤ eP ≤ q - 1 and computes KeP =

geP mod p, playing its part in the key agreement

process to establish a session key. The e-Passport

replies to the GET CHA LLENGE command by sending KeP and its domain parameters p, q, g.

eP → IS : KeP , p, q, g

Step 3 (IS) On receiving the response from the e-Passport, the IS generates a random IS ￡R 1 ≤ IS≤

q - 1 and computes its part of the session

key as KIS = gIS mod p. The IS digitally signs the

message containing MRZ value of the e-Passport

and KeP.

SIS = SIGNSKIS (MRZ || KeP)

It then contacts the nearest DV of the e-Passports

issuing country and obtains its public key. The IS

encrypts and sends its signature SIS along with the

e-Passport’s MRZ information and KeP using the

DV’s public key PKDV.

IS → DV: ENCPK DV (SIS, MRZ, KeP),

CERTCVCA (PKIS, IS)

Step 4 (DV) The DV decrypts the message received from the IS and verifies the CERTCVCA (PKIS, IS) and the signature SIS. If the verification holds, the

DV knows that the IS is genuine, and creates a digitally-signed message SDV to prove the IS’s authenticity to the e-Passport.

SDV = SIGNSKDV (MRZ || KeP || PKIS),

CERTCVCA (PKDV, DV)

The DV encrypts and sends the signature SDV

using the public key PKIS of IS.

DV → IS: ENCPKIS (SDV, [PKeP])

The DV may choose to send the public key of the e-

Passport if required. This has an obvious advantage,

because the IS system now trusts the DV to be genuine. It can obtain a copy of e-Passport’s PK to

verify during e-Passport authentication.

Step 5 (IS) after decrypting the message received, the IS computes the session key KePIS = (KIS) eP

and encrypts the signature received from the DV,

the e-Passport MRZ information and KeP using

KePIS. It also digitally signs its part of the session

key KIS.

IS → eP: KIS, SIGNSKIS (KIS, p, q, g),

ENCKePIS (SDV, MRZ, KeP)

Step 6 C On receiving the message from the IS, the e-Passport computes the session key KePIS =

(KIS)eP. It decrypts the message received using the

session key and verifies the signature SDV and

VERIFYPKIS (SIGNSKIS (KIS, p, q, g)). On successful verification, the e-Passport is convinced

that the IS system is genuine and can proceed further in releasing its details. All further communications between an e-Passport and IS are

encrypted using the session key KePIS.

5.4. Phase Two - e-Passport Authentication

Step 1 C The IS issues an INTERNA L AUTHENTICATE command to the e-Passport. The

e-Passport on receiving the command, the e-

Passport creates a signature SeP = SIGNSKeP

(MRZ || KePIS) and sends its domain parameter certificate to the IS. The entire message is encrypted using the session key KePIS.

eP → IS : ENCKePIS (SeP , CERTDV (PKeP),

CERTDV (p, q, g))

Step 2 (IS) The IS decrypts the message and verifies CERTDV (p, q, g), CERTDV (PKeP) and

SeP. If all three verifications hold then the IS

convinced that the e-Passport is genuine and authentic.

During the IS authentication phase, and IS sends the e-Passport’s MRZ information to the nearest e-Passport’s DV, which could be an e-Passport country’s embassy. Embassies are DV’s because they are allowed to issue e-Passports to their citizens and because most embassies are located within an IS’s home country, any network connection issues will be minimal. Sending the MRZ information is also advantageous, because the embassy now has a list of all its citizens that have passed through a visiting country’s border security checkpoint. We do not see any privacy implications, because, in most cases, countries require their citizens to register at embassies when they are vi siting a foreign country.

VI.EXPERIMENTA L RESULTS

A successful design, deployment and operation of biometric passport systems depend highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their passport system performance. However it is often forgotten that the biometric (iris, finger, face, palm prints.) is only one part of a fully deployed application. As biometric (sub) systems are often not designed with security and or privacy in mind, system integrators will need to address the requirements of the deployed application in this light. The fears and concerns of a significant segment of the user population need to be addressed as early as possible in the design process, to ensure that appropriate mechanis ms are in place to reassure such users. These concerns may relate to privacy or to safety issues, which may be addressed in part through legal and regulatory measures. This article discusses the requirements, design and application scenarios of biometrical systems in general and the introduction of a new biometrical passport in particular.

The e-passport authentication system is divided into enrollment module and authentication module. The passport users who are included in the enrollment module are e-passport holder, Immigration administrator. Figure 2 shows the enrollment module in the e-passport authentication architecture design.

The e-passport holder registers to the system by providing the personal data and some important documentation to the immigration officer. After that, Immigration Administrator will make the enrollment for the e-passport holder by filling the data into the enrollment system. After enrollment process, the data of the e-passport holder will be encrypted by proposed cryptography technique and stored into immigration database and RFID tag inside the e-passport. Besides that, Enrollment module also includes the modifying process and deleting process. Modifying process will be carried out if there was a special request from e-passport holder to change the information of the e-passport, the e-passport spoil, or finished pages. Deleting process will

be carried out if the previous e-passport validation date was expired or the e-passport holder lost their passport. They have to register a new e-passport in order to get an e-passport again.

Figure 1: Message sequence chart of authenticate with e-Passport scenario

Figure 2: Enrollment Module of E-passport Authentication Architecture

The passport user involve in the authentication module are e-passport holder and check point officer. When e-passport holder arrives to check point, e-passport holder will put the e-passport onto RFID reader, and a signature required key in by e-passport holder so that authentication process can be performed to verify an e-passport holder. After authentication process authenticated the e-passport holder, RFID reader will read the encrypted data which was stored inside the RFID tag in e-passport. The encrypted data will be sent to the system to match with the encrypted data in the database system. If the encrypted data in the e-passport match with the encrypted data which is stored inside the database during enrollment process, the encrypted data in the e-passport will be decrypted by a certain key. Then the check point officer has to check and verify the identity of the e-passport holder. Figure 3 shows the authentication module in the e-passport authentication architecture design. The attributes inherent in the e-Passport provide a here to fore unavailable means of improving the security of the international travel system.

Figure 3: Authentication Module of E-passport Authentication Architecture

These are described below under three general categories: preventing the use of multiple identities; linking the bearer to the document in a traditional border operations environment; and serving as a strong token to drive a biometric identification process. After these uses have been explored in some detail, the paper will examine why the e-Passport may not be universally accepted by states as the sole device used to fully automate the border clearance process for registered participants as envisioned by the process flow.

Accuracy of the biometric matching functions of the system. Issuing States must encode one or more facial, fingerprint, palm print or iris biometrics on the MRTD as per LDS standards (or on a database accessible to the Receiving State). Given an ICAO standardized biometric image and/or template, receiving States must select their own biometric verification software, and determine their own biometric scoring thresholds for identity verification acceptance rates – and referral of imposters.

-Passport Holder RFID Reader

E-Passport Authentication

System

Check Point Officer

TABLE 2: Comparison of Biometric Technologies

Every type of biometric measurement can be classified with a number of characteristics that should be considered in a selection process see table 2. Being familiar with these characteristics will help you to better understand how to think objectively about each type. Sure, some of the available biometric technologies are cool, but it’s no longer we have to make rational decisions about purchasing and using technology. Universality: This refers to whether each person has the characteristic being measured. For instance, nearly everyone in your organization will have at least one finger for fingerprint biometrics, but gait-based biometrics may be more difficult if you have any wheelchair-bound staff members.

Uniqueness: How well the particular biometric distinguishes people. Palm is the best, and fingerprints and iris scans are pretty good too.

Permanence: A good biometric system should measure something that changes slowly (if at all) over time. DNA and fingerprints are very good over the long term; handwriting and voice change somewhat from decade to decade.

Collectability: This refers to how easily the biometric can be measured. face scores very low (it isn’t easy to collect); fingerprint and palm-scan biometrics rate quite high. Gait requires a person to walk over a distance, which would be hard to do while sitting at a workstation. Retina scan requires the subject get really close to a digital camera.

Performance: This refers to the overall technology burden: how much equipment, time, and calculation go into performing a comparison. The fingerprint method fares very well; fingerprint readers are small, compact, and accurate. Biometrics tends to be costly, slow, and labor-intensive.

Accuracy: How well does a biometric system distinguish between subjects, and what are the false acceptance and false rejection rates?

Acceptability: W ill users be willing to use the biometric technology? face will score low because of privacy reasons. Retina scans will score low because some people will be uncomfortable putting their eye really close to something that seems intrusive. Similarly, people won’t mind swiping a finger across a surface-type fingerprint scanner or getting an iris photographed from a few feet away, but some are squeamish about sticking their fingers into a device (too many “B” movies).

Circumvention: This refers to how easily a forgery can be made that will fool the biometric system (early fingerprint devices, for example, could be fooled with “gummy fingers”). Proof of life testing — a feature that determines whether a sample comes from a living body part — is incorporated into many biometric systems so digital images of body parts are less likely to fool the system. But circumvention also refers to whether someone can attack a biometric system in other ways, such as replaying known good credentials through a network connection.

VII.CONCLUSIONS

The work represents an attempt to acknowledge and account for the presence on e-passport using biometrics recognition towards their improved identification. The application of facial, fingerprint, palm print and iris recognition in passports requires high accuracy rates; secure data storage, secure transfer of data and reliable generation of biometric data. The passport data is not required to be encrypted, identity thief and terrorists can easily obtain the biometric information. The discrepancy in privacy laws between different countries is a barrier for global implementation and acceptance of biometric passports. A possible solution to un-encrypted wireless access to passport data is to store a unique cryptographic key in printed form that is also obtained upon validation. The key is then used to decrypt passport data and forces thieves to physically obtain passports to steal personal information. More research into the technology, additional access and auditing policies, and further security enhancements are required before biometric recognition is considered as a viable solution to biometric security in passports. The adversaries might

exploit the passports with the lowest level of security. The inclusion of multiple biometric identification information into machine readable passports will improve their robustness against identity theft if additional security measures are implemented in order

to compensate for the limitations of the biometric technologies. It enables countries to digitize their security at border control and provides faster and safer processing of an e-passport bearer. E-passports may provide valuable experience in how to build more secure and biometric identification platforms in the years to come.

REFERENCES

[1] A.K.Jain, R.Bolle, “Biometrics-Personal

Identification in Networked Society” Norwell,

1999, Page No. 23-36.

[2]Barral and A. Tria. “Fake Fingers in Fingerprint

Recognition: Glycerin Supersedes Gelatin”, In

Formal to Practical Security. Springer, 2000. Page

No. 83-92.DOI:10.1007/978-3-642-02002-5_4. [3]Bergman, “Multi-Biometric Match-on-Card

Alliance Formed,” Biometric Technology Today,

vol. 13, no. 5, 2003. Page No. 1-9.

[4] C.Hesher, A.Srivastava, G.Erlebacher, “A Novel

Technique for Face Recognition using Range

Images” in the Proceedings of Seventh International Symposium on Signal Processing and

Its Application, 2005. Page No. 58-69.

DOI:10.1109/ISSPA.2003.1224850.

[5]Chang, “New Multi-Biometric Approaches for

Improved Person Identification,” PhD Dissertation,

Department of Computer Science and Engineering,

University of Notre Dame, 2006. Page No. 153-

159.

[6] D. Monar, A. Juels, and D. Wagner, “Security and

Privacy Issues in E-Passports”, Cryptology ePrint

Archive, Report 2005/095, 2007. Page No. 72-78.

DOI:10.1109/SECURECOMM.2005.59.

[7]Gaurav S. Kc and Paul A. Karger. “E-Passport

Authentication Protocols”, IBM Technical Report

(RC 23575), IBM T. J.Watson Research Labs,

April 2008. Page No. 315-322.

[8]HOME AFFAIRS JUSTICE, “EU Standard

Specifications for Security Features and

Biometrics in Passports and Travel Documents”,

Technical report, European Union, 2010. Page No.

62-65.

[9]John Daugman, “How Iris Recognition Works.”

IEEE Transactions on Circuits and Systems for

Video Technology, 14(1):21–30, 2010. Page No.

103-109.DOI:10.1109/TCSVT.2003.818350.

[10]KLUGLER, D., “Advance Security Mechanisms

for E-Passport Protocols Implementation, Technical Report”, Federal Office for Information

Security (BSI), Germany, 2011. Page No. 41-46. [11]Riscure Security Lab, “E-Passport Privacy Attack”,

at the Cards Asia Singapore, April 2011. Page No.

1-56. First Author Profile:

Mr. V.K. NARENDIRA

KUMAR M.C.A., M.Phil.,

Assistant Professor, Department of

Information Technology, Gobi

Arts & Science College

(Autonomous), Gobichettipalayam

– 638 453, Erode District, Tamil

Nadu, India. He received his M.Phil Degree in Computer Science from Bharathiar University in 2007. He has author more than 40 international journal article publications. He has authored or co-authored more than 60 technical papers and conference presentations. He is an editorial board member for several scientific international journals. His research interests are focused on Internet Security, Biometrics, Advanced Networking, Visual Human-Computer Interaction, and Multiple Biometrics Technologies.

Second Author Profile:

Dr. B. SRINIVASAN M.C.A.,

M.Phil., M.B.A., Ph.D., Associate

Professor, PG & Research

Department of Computer Science,

Gobi Arts & Science College

(Autonomous), Gobichettipalayam

– 638 453, Erode District, Tamil

Nadu, India. He received his Ph.D. Degree in Computer Science from Vinayaka Missions University in 11.11.2010. He has author or co-authored more than 30 international journal article publications.

He has authored or co-authored more than 70 technical papers and conference presentations. He is a reviewer

for several scientific e-journals. His research interests include automated biometrics, computer networking, Internet security, and performance evaluation.

技术开发合作协议

技术开发合作协议文件编码（GHTU-UITID-GGBKT-POIU-WUUI-8968）

合同编号： 技术开发合同 项目名称：PC预制件模具开发 委托方(甲方)： 受托方(乙方)： 签订时间： 签订地点： 有效期限：2016年04月22日～2018年04月22日 委托方(甲方)： 住所地： 法定代表人： 项目联系人： 通讯地址： 电话：传真：/ 电子信箱： 受托方（乙方）： 住所地： 项目负责人： 项目联系人： 通讯地址： 电话：传真：/ 电子信箱： 本合同甲方委托乙方研究开发PC预制件模具开发项目，并支付项目合作费，乙方接受委托并进行此项研究开发工作。双方经过友好协商，在真实、平等、自愿的基础上，根据《中华人民共和国合同法》规定，达成如下协议并由双方共同恪守。 第一条合作形式、技术目标、任务指标、分工要求和提交成果 1.1合作形式 甲方与乙方采取长期战略合作的开发形式，与该项目有关的知识产权归属甲方所有。 1.2技术目标：

本次项目通过完成PC预制件模具开发产品设计开发，使产品主要技术性能达到国内领先水平，并形成甲方自有风格和知识产权。 1.3任务指标 见甲乙双方确认的PC预制件模具开发具体的《项目任务书》。 1.4分工要求 1)方案设计、技术设计、工程图设计、力学计算等工作以乙方为主、甲方协助； 2)技术文件、样机试制、试验整改、项目定型等工作以甲方为主、乙方协助； 3)乙方完成方案设计后，技术设计阶段由甲方安排专业组进行对接参与，详细分工计划由双方协商。 1.5提交成果 乙方向甲方提交该项目的研究成果为总体设计方案、全套工程图纸、产品清单。 第二条合同履行计划 依据需要制定开发计划，以甲方书面通知为准，作为本合同附件具备同等效力。 第三条双方责任 甲方责任： 1)甲方向乙方提供开展该项目研发工作所需的技术资料，负责对乙方技术设计和工程图设计提供工艺指导和制造规范要求； 2)甲方按合同规定准时向乙方支付研发经费； 3)甲方负责样机试制、试验、整改生产组织； 4)甲方负责产品定型、鉴定和项目验收组织。 乙方责任： 1)乙方按甲方要求安排专业研发人员参与PC预制件模具开发产品研发，确保项目设计质量及项目可持续性。 2)乙方设计开发时要充分考虑甲方生产制造和采购平台体系，满足甲方生产工艺制造要求。 3)乙方按本协议第一条第1.4项要求，向甲方提供该合作项目的研究成果。

化学工程与工业生物工程专业就业方向与就业前景

化学工程与工业生物工程专业就业方向与就 业前景 1、化学工程与工业生物工程专业简介 化学工程与工业生物工程专业以生物学、化学、工程学的基本理论为依据，利用酶工程、细胞工程、发酵工程研究生物产品的生产过程，研制开发新的生物工程产品以及对生物产品进行分析测定的技术。旨在培养能在化学工程及生物技术领域从事科学研究、产品及过程设计、新技术与设备研发以及技术管理的高级专门人才，能立足于服务于石油化工、环境保护、能源、食品等传统石油化学工业及生物工程与技术、生物化学工程、生物医药工程等新兴产业。 2、化学工程与工业生物工程专业就业方向 本专业学生毕业后可在工业企业、金融银行、咨询服务或政府部门担任化学工程与工业生物工程师、系统分析员、生产工程师、管理顾问、操作分析员以及类似的职位。 从事行业： 毕业后主要在制药、石油、新能源等行业工作，大致如下：1制药/生物工程 2石油/化工/矿产/地质 3新能源 4环保

5其他行业 6快速消费品(食品、饮料、化妆品) 7机械/设备/重工 8建筑/建材/工程 从事岗位： 毕业后主要从事销售工程师、电气工程师、ie工程师等工作，大致如下： 1化学工程师 2工艺工程师 3研发工程师 4销售工程师 5全国代理商 6销售经理 7区域代理商 8化验员 工作城市： 毕业后，上海、广州、北京等城市就业机会比较多，大致如下： 1上海 2广州 3北京 4杭州 5深圳 6苏州

7南京 8武汉 3、化学工程与工业生物工程专业就业前景怎么样 化学工程与工业生物工程专业在专业学科中属于工学类中的化学与制造类，其中化学与制造类共5个专业，化学工程与工业生物工程专业在化学与制造类专业中排名第5，在整个工学大类中排名第139位。 截止到2013年12月24日，46122位化学工程与工业生物工程专业毕业生的平均薪资为4406元，其中应届毕业生工资3805元，0-2年工资3855元，3-5年工资4704元，10年以上工资5704元，6-7年工资6290元，8-10年工资6736元。化学工程与工业生物工程专业就业岗位最多的地区是武汉。薪酬的地区是常德。

几种常见的生物特征识别方式

生物识别技术主要是指通过人类生物特征进行身份认证的一种技术，这里的生物特征通常具有唯一的(与他人不同)、可以测量或可自动识别和验证、遗传性或终身不变等特点。所谓生物识别的核心在于如何获取这些生物特征，并将之转换为数字信息，存储于计算机中，利用可靠的匹配算法来完成验证与识别个人身份的过程。 方法/步骤 1.指纹识别 指纹是指人的手指末端正面皮肤上凸凹不平产生的纹线。纹线有规律的排列形成不同的纹型。纹线的起点、终点、结合点和分叉点，称为指纹的细节特征点。指纹识别即指通过比较不同指纹的细节特征点来进行鉴别。由于每个人的指纹不同，就是同一人的十指之间，指纹也有明显区别，因此指纹可用于身份鉴定。 指纹识别技术是目前最成熟且价格便宜的生物特征识别技术。目前来说指纹识别的技术应用最为广泛，我们不仅在门禁、考勤系统中可以看到指纹识别技术的身影，市场上有了更多指纹识别的应用：如笔记本电脑、手机、汽车、银行支付都可应用指纹识别的技术。 2.静脉识别 静脉识别系统就是首先通过静脉识别仪取得个人静脉分布图，从静脉分布图依据专用比对算法提取特征值，通过红外线CMOS摄像头获取手指静脉、手掌静脉、手背静脉的图像，将静脉的数字图像存贮在计算机系统中，将特征值存储。静脉比对时，实时采取静脉图，提取特征值，运用先进的滤波、图像二值化、细化手段对数字图像提取特征，同存储在主机中静脉特征值比对，采用复杂的匹配算法对静脉特征进行匹配，从而对个人进行身份鉴定，确认身份。全过程采用非接触式。 3.虹膜识别 虹膜是位于人眼表面黑色瞳孔和白色巩膜之间的圆环状区域，在红外光下呈现出丰富的纹理信息，如斑点、条纹、细丝、冠状、隐窝等细节特征。虹膜从婴儿胚胎期的第3个月起开始发育，到第8个月虹膜的主要纹理结构已经成形。除非经历危及眼睛的外科手术，此后几乎终生不变。 虹膜识别通过对比虹膜图像特征之间的相似性来确定人们的身份，其核心是使用模式识别、图像处理等方法对人眼睛的虹膜特征进行描述和匹配，从而实现自动的个人身份认证。英国国家物理实验室的测试结果表明：虹膜识别是各种生物特征识别方法中错误率最低的。从普通家庭门禁、单位考勤到银行保险柜、金融交易确认，应用后都可有效简化通行验证手续、确保安全。如果手机加载“虹膜识别”，即使丢失也不用担心信息泄露。机场通关安检中采用虹膜识别技术，将缩短通关时间，提高安全等级。 4.视网膜识别 视网膜是眼睛底部的血液细胞层。视网膜扫描是采用低密度的红外线去捕捉视网膜的独特特征，血液细胞的唯一模式就因此被捕捉下来。视网膜识别的优点就在于它是一种极其固定的生物特征，因为它是“隐藏”的，故而不可能受到磨损，老化等影响;使用者也无需和设备进行直接的接触;同时它是一个最难欺骗的系统，因为视网膜是不可见的，故而不会被伪造。另一方面，视网膜识别也有一些不完善的，如：视网膜技术可能会给使用者带来健康的损坏，这需要进一步的研究;设备投入较为昂贵，识别过程的要求也高，因此角膜扫描识别在普遍推广应用上具有一定的难度。 5.面部识别 面部识别是根据人的面部特征来进行身份识别的技术，包括标准视频识别和热成像技术两种。 标准视频识别是透过普通摄像头记录下被拍摄者眼睛、鼻子、嘴的形状及相对位置等面部特征，然后将其转换成数字信号，再利用计算机进行身份识别。视频面部识别是一种常见

2020年(生物科技行业)生物技术创新与生物产业促进计划

（生物科技行业）生物技术创新与生物产业促进计划

附件2： 生物技术创新和生物产业促进计划 简介 壹、背景 2008年4月18日，中国科学院生命科学和生物技术局在天津举行的中国工业生物技术发展高峰论坛?2008上，倡议成立“中国工业生物技术产业化促进会”。 2008年5月23日，在北京举行的绿色农业技术集成和示范研讨会上，成立了“中国绿色生态农业科技创新联盟”，37家科研院所和企业单位加盟。 2008年6月22日，在长沙举行的第二届中国生物产业大会上，中国科学院研究机构和40余家工业生物技术企业建立了工业生物产业创新联盟伙伴关系，且签署了备忘录。 2008年8月2日，在常州举行的中国药物产业科技创新高峰论坛上，45家医药研究机构和40多家企业成立了中国药物产业科技创新联盟。 工业生物技术科技创新联盟、绿色生态农业科技创新联盟和药物产业科技创新联盟共同组成了生物产业科技创新联盟（简称“创新联盟”），共募集意向性的企业科技创新基金逾25亿元。目前，生物产业科技创新联盟得到了越来越多的科研机构、企业、地方政府的关注和支持，联盟的规模和影响不断扩大。 在推动生物产业科技创新联盟的基础上，2008年底，中国科学院启动《生物技术创新和生物产业促进计划》（简称“专项计划”）。在国家有关部门的支持下，该计划作为应对金融危机支撑经济发展的科技创新专项行动计划之壹，力争为“保增长、扩内需、调结构”发挥重要作用。

二、中国科学院的生物技术概况 中国科学院作为国立科研机构，致力于解决事关国家全局和长远发展的基础性、战略性、先导性、系统性的重大科技问题，致力于促进科技成果的转移转化和高技术产业化，致力于支持和提升我国产业的竞争力。 中国科学院的生命科学和生物技术研究发展迅速，近年来取得了壹批具有国际先进水平的理论创新成果。和此同时，在农业、人口健康、生态环境、工业生物技术领域形成了壹批高水平的技术创新成果。知识创新工程三期以来，中国科学院以提升科技创新能力为主线，以促进我国生物产业快速、持续、健康发展为目标，依托人口健康和医药创新基地、先进工业生物技术创新基地和现代农业科技创新基地，全面推动生命科学的原始创新研究和生物技术的应用和推广研究。在新药创制、诊断试剂开发、农作物品种培育、生物农药研制、工业酶和大宗发酵产品开发等若干重要领域又形成了壹批关键核心技术，积累了壹批有潜在应用价值的技术成果，有望产生重大的经济和社会效益。 三、主要任务 瞄准国家重大需求，通过国家资金引导，优化资源配置，强强联合，使国内外生物技术创新成果不断向国内优势企业、行业龙头企业转移转化，带动国家和地方生物产业发展。 1、探索高效的产学研结合技术转移模式，促使壹批自主创新的关键技术实现产业化，为传统产业的结构调整和振兴，为新兴产业的形成和发展提供强有力的科技支撑。 2、将技术研发和产业发展结合起来，促进企业成为技术创新的

食品生物技术论文

姓名： ** 班级： *** 学号： *** 指导老师： *** 完成日期：2012****

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技术开发合作协议书范本(一)

编号：_______________ 本资料为word版本，可以直接编辑和打印，感谢您的下载 技术开发合作协议书范本（一） 甲方：___________________ 乙方：___________________ 日期：___________________

委托方：(甲方)_____________ 研究开发方(乙方)_____________ 一、 签订地点：____省____市(县) 签订日期：__年__月__日 有效期限：__年__月__日至__年__月__日 二、应达到的技术指标和参数： 三、研究开发计划： 四、研究开发经费、报酬及其支付或结算方式： (一)研究开发经费是指完成本项研究开发工作所需的成本;报酬是指本项目开发成是的使用费和研究开发人员的科研补贴。 本项目研究开发经费及报酬：____元 其中：甲方提供____元，乙方提供____元。如开发成本实报实销，双方约定如下：______。 (二)经费和报酬支付方式及时限(采用以下第种方式)： ①一次总付：____元，时间：______ ②分期支付：____元，时间：__________元，时间：______ ③按利润____%提成，期限：______ ④按销售额____%提成，期限：______ ⑤其它方式：____________ 五、利用研究开发经费购置的设备、器材、资料的财产权属： 六、履行的期限、地点和方式：____________________ 本合同自____年____月____日至____年____月____日在______(地点)履行。 本合同的履行方式：_____________

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从事岗位： 毕业后主要从事销售工程师、电气工程师、ie工程师等工作，大致如下： 1化学工程师 2工艺工程师 3研发工程师 4销售工程师 5全国代理商 6销售经理 7区域代理商 8化验员 工作城市： 毕业后，上海、广州、北京等城市就业机会比较多，大致如下： 1上海 2广州 3北京 4杭州 5深圳 6苏州 7南京 8武汉

3、化学工程与工业生物工程专业就业前景 化学工程与工业生物工程专业在专业学科中属于工学类中的化学 与制造类，其中化学与制造类共5个专业，化学工程与工业生物工程 专业在化学与制造类专业中排名第5，在整个工学大类中排名第139位。 截止到2013年12月24日，46122位化学工程与工业生物工程专业毕业生的平均薪资为4406元，其中应届毕业生工资3805元，0-2年工资3855元，3-5年工资4704元，10年以上工资5704元，6-7年工 资6290元，8-10年工资6736元。化学工程与工业生物工程专业就业 岗位最多的地区是武汉。薪酬的地区是常德。

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[标签: titlecontent] 合同编号：_________ 甲方：_________ 住所：_________ 法定代表人：_________ 项目联系人：_________ 联系方式：_________ 通讯地址：_________ 电话：_________ 传真：_________ 电子信箱：_________ 乙方：_________ 住所：_________ 法定代表人：_________ 项目联系人：_________ 联系方式：_________ 通讯地址： _________

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