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10
A New Fingerprint Authentication Scheme
Based on Secret-Splitting for
Enhanced Cloud Security
Ping Wang1, Chih-Chiang Ku1 and Tzu Chia Wang2
1Department of Information Management, Kun Shan University,
2Institute of Computer and Communication Engineering,
National Cheng Kung University,
Taiwan
1. Introduction
The number of commercially-available web-based services is growing rapidly nowadays. In
particular, cloud computing provides an efficient and economic means of delivering
information technology (IT) resources on demand, and is expected to find extensive
applications as network bandwidth and virtualization technologies continue to advance.
However, cloud computing presents the IT industry not only with exciting opportunities,
but also with significant challenges since consumers are reluctant to adopt cloud computing
solutions in the absence of firm guarantees regarding the security of their information.
Two fundamental issues arise when users applying cloud computing to software as a
service (SaaS). First, if enterprise data is to be processed in the cloud, it must be encrypted to
ensure its privacy. As a result, efficient key management schemes are required to facilitate
the encryption (and corresponding decryption) tasks. Second, as the sophistication of the
tools used by malicious users continues to increase, the data processed in the cloud is at
increasing risk of attack. Consequently, there is an urgent requirement for robust
authentication schemes to ensure that the data can be accessed only by legitimate,
authorized users.
Network attacks such as phishing or man-in-the-middle (MITM) attacks present a serious
obstacle to consumer acceptance of cloud computing services. According to reports released
by privacy watchdog groups in the US, more than 148 identity theft incidents, affecting
nearly 94 million identities, occurred in 2005 in the US alone (Mark, 2006). Identity theft is
therefore one of the most severe threats to the security of online services. As a result, it is
imperative that SaaS providers have the means to authenticate the identity of every user
attempting to access the system. Due to the non-denial requirements of remote user identity
authentication schemes, this is most commonly achieved using some form of biometrics-
based method.
The term “biometrics” describes a collection of methods for identifying individuals based
upon their unique physiological or behavioral characteristics (Furnell et al. 2008). Generally
speaking, the physiological characteristics include the individual’s fingerprint, vein pattern,
DNA and shape of face, while the behavioral characteristics include the handwriting
dynamics, voice and gait. Automated biometric recognition systems are now widely used
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throughout the automotive; IT and banking industries (see Figs. 1 and 2). For example,
Miura et al. (2005) developed a biometric authentication system based on the individual’s
finger vein for accomplishing secure online authentication over small devices such as
notebook computers, cell phones, and so on.
Fig. 1. Fingerprint scanner and smart card reader
Fig. 2. Sensor-based scanning of user fingerprint template
However, existing biometric authentication systems cannot absolutely guarantee the
identity of the individual. For example, biometric features such as the fingerprint may be
acquired surreptitiously and then used by a malicious user. Similarly, even in multi-factor
authentication methods such as smart cards, in which the biometric information is protected
using a password, the password may be cracked by network hackers and the biometric
information then copied and counterfeited. These proposals are invariably based on the
assumption of employee honesty. Unfortunately, this assumption cannot also be guaranteed
in practical applications, and many real cases have been reported in which dishonest interior
staff have stolen users’ authentication details from the authentication database and have
then used these details to acquire the customers’ private information for financial gain (see
Fig.3).
A New Fingerprint Authentication Scheme Based on Secret-Splitting for Enhanced Cloud Security
185
Fig. 3. Theft of biometric features by dishonest staff
To resolve the security issues described above, the present study proposes a new remote
authentication scheme based on a secret-splitting concept. In the proposed approach, part of
the biometric data is encrypted and stored on a smart card, while part of the data is
encrypted and stored on a server (see Fig. 4). This approach not only resolves the problem of
data abuse by interior staff, but also helps protect the users’ information against malicious
attack such as hacking into the Certificate Authority (CA) since to counterfeit the entire
biometric information, dishonest staff or hackers must simultaneously decrypt two secret
keys rather than just one.
Fig. 4. Proposed authentication scheme based on secret-splitting
In addition to the secret-splitting concept, the proposed authentication scheme utilizes the
Diffie-Hellman key exchange / agreement algorithm (Diffie & Hellman, 1976) to guarantee
the security of the data transmissions between the terminal and the server. The main
differences between the scheme proposed in this study and existing methods can be
summarized as follows: (i) the smart card stores only part of the fingerprint template used in
the identity authentication process. As a result, the user’s identity is protected even if the
card is lost or stolen. (ii) the template information stored on the smart card and server,
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186
respectively, is independently encrypted. Consequently, the information obtained by a
hacker or dishonest member of staff from a successful attack on the authentication database
is insufficient to pass the liveness test.
A remote authentication scheme based on a secret-splitting concept is proposed for
resolving the problem of user privacy in cloud-computing applications. In contrast to
existing multi-factor authentication schemes, the proposed method minimizes the threat of
attacks by dishonest interior employees since only a subset of the information required to
pass the liveness test is stored on the user authentication database.
The remainder of this chapter is organized as follows. Section 2 briefly reviews the essential
properties of identity authentication schemes and presents the related work in the field.
Section 3 introduces the remote identity authentication scheme proposed in this study.
Section 4 examines the robustness and computational efficiency of the proposed approach.
Finally, Section 5 presents some brief concluding remarks.
2. Existing multi-factor authentication methods
Remote authentication is essential in ensuring that only legitimate individuals are able to
access a network and make use of its resources. Typically, remote authentication is achieved
using one of the following well-known schemes: (1) user account / password, (2) network
address / domain name, (3) shared secret keys, (4) public keys, (5) digital signatures, (6)
biometric authentication, (7) digital certificates, or (8) smart cards. Figure 5 shows a typical
authentication procedure using a smart card in conjunction with the user’s fingerprint.
Fig. 5. Remote authentication using smart card and fingerprint
Password-based authentication schemes have the advantage of simplicity, but are reliant
upon the user memorizing the password and remembering to modify it periodically in
order to maintain the security of their account. Smart cards, in which the user’s identity
authentication information is encrypted on an embedded chip, have a number of benefits
compared to traditional password-based methods, namely (i) the user’s information is
protected by a simple Personal Identity Number (PIN); (ii) the risk of identity theft is
minimized by means of sophisticated on-chip defense measures; and (iii) single smart cards
can be programmed for multiple uses, e.g. banking credentials, medical entitlement, loyalty
programs, and so forth. Consequently, various multi-factor authentication schemes based
upon smart cards and integrated biometric sensors have been proposed.
In a pioneering work of multifactor authentication schemes, For example, J.K. Lee et al.
(2002) proposed a remote identity authentication scheme in which a smart card was
A New Fingerprint Authentication Scheme Based on Secret-Splitting for Enhanced Cloud Security
187
integrated with a fingerprint sensor. In the proposed approach, the smart card, a secret
password, and the user’s fingerprint were taken as inputs in the login process and the
fingerprint minutiae, encrypted with the time stamp and the user’s authentication template,
were then compared with the authentication value stored on the card. To enhance the
security of the ElGamal public key system (ElGamal, 1985) used in J.K. Lee et al. (2002), the
encryption parameters were randomly generated in accordance with both the user’s
fingerprint minutiae and the time stamp. However, while the proposed method is therefore
robust toward replay attacks, clock synchronization is required at all the hosts, which is a
significant challenge in open network environments.
Kim et al. (2003) proposed an integrated smart card / fingerprint authentication scheme in
which a password list was not maintained at the server such that the users were able to
change their passwords at will. Moreover, protection against replay attacks was provided by
means of Nonce technology, thereby avoiding the need for clock synchronization at the
hosts. However, Scott (2004) showed that the Nonce-based design rendered the system
vulnerable to imitation attacks given the collection by a hacker of a sufficient number of
network packets to calculate the authentication value.
Later on, Lin and Lai (2004) showed that under certain circumstances, the method proposed
by Lee et al. was unable to resist identity masquerade attacks. Accordingly, the authors
proposed a new scheme for enhancing the security of the method presented in J.K. Lee et al.
(2002) by allowing the users to choose and change their passwords at will. However,
Mitchell and Tang (2005) showed that the method proposed by Lin and Lai also contained a
number of serious flaws, most notably (i) hackers may simply copy the fingerprint from the
imprint cup; (ii) the time stamp generated during a legal login procedure may be detected
by a malicious user and then modified in order to login illegally at some future point in
time; and (iii) the system contains no rigorous mechanism for preventing malicious users
from using old passwords to perform an illegal login operation when the legitimate users
change their passwords.
Recently, Fan et al. (2006) proposed a three-factor remote authentication scheme based on a
user password, a smart card and biometric data. Importantly, in the proposed approach, the
server only stores an encrypted string representing the user identity. That is, the biometric
data is not revealed to any third party; including the remote server. The scheme is
implemented using a two-step procedure. In the first step (the registration step), an
encrypted user template is constructed by mixing a randomly-chosen string with the
biometric characteristics of the user via an exclusive-or operation (XOR). In the second step
(the login step), the fingerprint minutiae obtained via a sensor are encrypted using a second
randomly-chosen string, and the two strings are then sent to a sensor for matching. The
scheme has the advantage that all three security factors (the password, the smart card and
the biometric data) are examined at the remote server, i.e., the system is a truly three-factor
remote authentication system. Furthermore, the authentication process performed at the
remote server does not require the exact value of the user’s biometric data to be known. As a
result, the security of the user’s biometric information is improved. However, when the
registration process is performed in a centralized way (e.g., a central Certificate Authority
(CA) is used to issue certified users with a certificate), the scheme is vulnerable to the theft
of the user’s fingerprint minutiae by interior dishonest staff. In other words, while the
scheme preserves the privacy of the users in the login and authentication phases, the
security of the biometric data is not guaranteed during the registration phase.
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3. A secret-splitting remote authentication scheme
This section proposes a novel remote authentication protocol for network services based on
the secret-splitting concept. The proposed protocol comprises three phases, namely the
initialization phase, the registration phase, and the authentication phase (see Fig. 6).
Fig. 6. Proposed fingerprint matching concept
In the initialization phase, the manufacturer produced a smart card and wrote a set of
unique security parameters (AN) into it. In the registration phase, the user registers with a
CA organization, and verifies their legal identity by means of traditional physical identity
documents such as an identity card or a social security card. Encrypted fingerprint template
A (EA’) is generated from the information extracted by a fingerprint scanner (EA) and the
smart card information obtained from a card reader (AN), and the remaining part of the
encrypted fingerprint template B (EB’) is directly extracted from the authentication
database. Once the two templates (EA’, EB’) have been combined into a complete template
by the terminal, the comparison results are sent to the server to verify the legality of the
user, that is, (EF = EF’). Note that this step is designed to prevent counterfeit attacks in
which a malicious hacker sends a “legal user” message directly from the terminal in order to
deceive the server.
Fig. 7 presents the function flow diagram of the proposed remote authentication scheme.
The details of each phase in the scheme are presented in Sections 3.1~3.3.
A New Fingerprint Authentication Scheme Based on Secret-Splitting for Enhanced Cloud Security
189
Fig. 7. Function flow diagram of proposed remote authentication scheme
3.1 Initialization phase
When the smart card manufacturer accepts an order from the CA, it writes various security
parameters into the cards (e.g., the card number or authentication number (AN)) and then
sends the cards to the CA. The detailed procedure is shown in Fig. 8
Step 1.1: Manufacturer randomly chooses a large prime number p and determines its root α.
Step 1.2: Manufacturer generates a unique Authentication Number (AN) based on a pre-
defined coding rule.
Step 1.3: Manufacturer randomly selects a 128-bit string K as a key for symmetric
encryption and keeps (p, α, AN, K) secret.
Step Executor Actions
1.1 Manufacturer Randomly choose a large prime number p and determines its
root α
1.2 Manufacturer Generate a unique Authentication Number (AN)
1.3 Manufacturer Randomly select a 128-bit string K as a key for symmetric
encryption and keep [ p, α, AN, K ] Smart card secret.
Fig. 8. Initialization phase
3.2 Registration phase
The user registers with the CA and receives a smart card once he or she has confirmed their
legal identity using some form of physical identity document. As shown in Fig. 9, the
registration phase comprises five steps, namely:
Step 2.1: Let user Ui with identity IDi be about to register with the server. The user chooses a
card password, PWi , the password is then saved to the smart card, and then protected by
the encryption mechanism of smart card.
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190
Step 2.2: The fingerprint image of User Ui is obtained via a sensor and the minutiae are
extracted from this image to form a fingerprint template Fi. The terminal separates Fi into
two parts, FiA and FiB, where FiA and FiB represents part A and part B of fingerprint template,
respectively.
Step 2.3: The terminal computes EAi= h (FiA⊕AN), EBi= h (FiB⊕AN), and HEFi =h
(EAi∪EBi ), where ∪ is a merge operation and h(.) is a public one-way hash function.
Step 2.4: The terminal sends (IDi, hEBi, p, α, K, HEFi) to the server over a secure channel
Step 2.5: The terminal stores (IDi , PWi, hEAi) in the smart card.
Step Executor Actions
2.1 Ui Determine a card password PWi
2.2 Ui
Terminal
Form a fingerprint template Fi using the fingerprint
minutiae obtained via a sensor. (Note that Fi represents the
fingerprint template of user Ui.) Separate Fi into two parts,
FiA and FiB .
2.3 Terminal Compute EAi= FiA⊕AN, EBi= FiB⊕AN
HEFi=h(EAi∪EBi)
2.4 TerminalÎServer Send (IDi, hEBi, p,α,K, HEFi)
2.5 Terminal Store (IDi , PWi , hEAi) on smart card
Terminal ÎUi [ IDi , PWi, hEAi, p ,α, AN, K ] Smart card
Fig. 9. Registration phase
3.3 Authentication phase
Users insert their smart card, containing a partial authentication template into a card reader
and a login request is then sent to the authentication server. The fingerprint information is
checked using the following eight-step procedure (see Figs. 10 and 11):
Step 3.1: User Ui inputs his or her password PWi* into the terminal. If the password is
correct, the AN is extracted; else the login request is rejected.
Step 3.2: Users “provide their fingerprint via a sensor, and the fingerprint is then
compared with that stored on the authentication server. Let Fi* represent the fingerprint
minutiae extracted by the sensor. The terminal separates Fi* into FiA* and FiB*, and then
computes EAi*= FiA*⊕AN and EBi*= FiB*⊕AN. The two parts (i.e., EAi* , EBi*) are then
merged to generate the full biometric template of the user, i.e., EFi*= EAi*∪EBi*. The server
sends EBi to the terminal for comparison purposes in order to verify the user’s legal
identity. If a match is obtained (i.e., EBi==EBi*), the authentication process proceeds to
Step 3.3; else it terminates.
Step 3.3: (Diffie-Hellman key exchange algorithm). The terminal randomly selects a
number A
Xsuch that A
Xp
<
, and then computes mod
A
X
T
Yp
α
=and YA= IDi ||YT, where
α and p are both stored on the smart card. The terminal then sends YA to the server.
Similarly, the server randomly selects a number B
X such that B
Xp<,
computes mod
B
X
B
Yp
α
=, and then sends YB to the terminal.
A New Fingerprint Authentication Scheme Based on Secret-Splitting for Enhanced Cloud Security
191
Step 3.4: The terminal uses YB to compute the session key
()
mod
A
X
B
SK Y
p
=. Similarly, the
server uses YA to compute the common session key,
()
mod
B
X
A
SK Y
p
=. Note that SK is a
shared secret between the terminal and the server.
Step Executor Actions
3.1 Ui Input password PWi*
Terminal Examine PWi* and gain AN
3.2 Ui Scan finger to provide information required to
construct fingerprint template Fi*
Terminal Separate Fi* into FiA* and FiB*, where
EAi*= FiA*⊕AN , EBi*= FiB*⊕AN, and EFi*= EAi*∪EBi*
ServerÎ Terminal Extract EBi from server. If a match is obtained (i.e.,
EBi== EBi*), go to Step 3.5; else terminate the
authentication process
3.3 Terminal Randomly select a number XA such that XA <p
Compute mod
A
X
T
Yp
α
=.
TerminalÎ Server YA= IDi ||YT
Server Randomly select a number XB such that XB <p
Server ÎTerminal Send YB to terminal
3.4 Terminal
()
mod
A
X
B
SK Y
p
=
Server
()
mod
B
X
A
SK Y
p
=
Fig. 10. Authentication phase (Steps 3.1~3.4).
Step 3.5: The server generates a one-time symmetric key RK, computes M=Esk(EBi||RK),
and then sends M to the terminal. Note that Esk(.) denotes a symmetric encryption function
(such as the AES method) based on the session key SK.
Step 3.6: The terminal acquires EBi and RK by performing the decryption process DSK (M),
and extracts EAi from the smart card. EAi and EBi, are then merged to obtain EFi=
EAi∪EBi, where Dsk(.) denotes a symmetric decryption function based on the session key
SK.
Step 3.7: The terminal compares EFi* and EFi. If a match is obtained, the legal user is
successfully identified; else the terminal sends RM=ERK(h(EFi)||CM) to the server for
reconfirmation purposes. Note that ERK is a symmetric decryption function based on the key
RK, and CM is a message indicating the matching result.
Step 3.8: The server re-verifies the match h(EFi) == HEFi . If a match is obtained, the server
accepts the login request of Ui; else it rejects the request.
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Ste
p
Executor Actions
3.5 Serve
r
Generate a one-time
p
rivate ke
y
RK
Serve
r
ÎTerminal Compute
M
=Es
k
(EBi||R
K
) and send
M
3.6 Terminal Decr
yp
t DSK (
M
) to obtain EBiand R
K
Extract EAi using card reader, then merge two parts of
template, i.e., EFi= EAi∪EBi
3.7 Terminal If Match
(
E
F
i*== E
F
i
)
,then CM=true; else CM=false
Terminal ÎServe
r
Return the Comparison Messa
g
e (CM) and E
F
i with
encr
yp
tion RM=ER
K
(
h
(
E
F
i
)
||CM
)
3.8 Server Decr
yp
t DRK (RM) to obtain h(E
F
i) and CM
Verify (h(EFi) == HEFi)
Accept the login request of Ui if match is obtained; else
re
j
ect lo
g
in re
q
uest.
Fig. 11. Authentication phase (Steps 3.5~3.8).
Summarizing the procedures shown in Figs. 9~11, the overall sequence diagram of the
proposed remote authentication scheme can be illustrated as shown in Fig. 12.
Fig. 12. Sequence diagram of proposed remote authentication scheme
4. The security performance and computational efficiency
This section discusses the security performance and computational efficiency of the
proposed remote authentication scheme.
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4.1 Security analysis
This sub-section demonstrates the robustness of the proposed authentication scheme toward
three common forms of attack, namely (i) authentication factor attacks; (ii) network attacks;
and (iii) interior attacks originating from the card-issuing organization.
4.1.1 Authentication factor attacks
Given a three-factor authentication scheme (i.e., password, smart card and user biometrics),
a hacker requires all three factors in order to successfully complete the authentication
process. It is possible that the smart card and password may be stolen or duplicated.
However, in the scheme proposed in this study, the biometrics template is strongly
protected using a secret-splitting technique. Thus, even if a hacker manages to obtain the
partial fingerprint template EBi, he or she cannot generate the partial template EAi without
possessing the knowledge of the authentication number (AN) stored on the smart card.
Besides, hackers have no matters to generate the other part of biometrics template (EAi),
except they crack the program which is used for merging EAi* and EBi*, however, this
program generally is an executive binary code and burn in the ROM of card issuing
machine. In other words, it is extremely difficult for a hacker or a dishonest member of staff
to obtain all three authentication factors for a particular user, and thus the proposed scheme
is as safe as other multi-factor authentication schemes.
As described above, in the proposed approach, the biometric data of a user is separated into
two parts (EAi , EBi), encrypted and stored on a smart card and a server, respectively. This
approach not only preserves the privacy of the users in the login and authentication phases,
but also helps protect the users’ information against the theft of the user’s fingerprint
minutiae by interior dishonest staff.
4.1.2 Network attacks
This section demonstrates the robustness of the proposed authentication scheme toward
three common types of network attack, namely (i) man-in-the-middle attacks, (ii) dictionary
attacks, (iii) replay attacks.
Strong encryption authentication helps prevent man-in-the-middle attacks. In the proposed
scheme, the authentication template, encrypted using a 128-bit AES symmetric encryption
algorithm, is split into two parts; stored on the smart card and the server, respectively. To
prevent from the man-in-the-middle attacks, the data transmissions between the terminal
and the server are protected by a session key generated using the Diffie-Hellman key
exchange algorithm. Therefore, hackers are not easily able to steal the complete set of
biometric data. Thus, the security of the biometric data is further enhanced since solving the
Discrete-Logarithm Problem (DLP) in order to crack the Diffie-Hellman protected
transmissions is extremely hard within a finite period of time [14]. In addition, the
decryption process is further complicated (from the hacker’s perspective) by the fact that the
session key is changed on a periodic basis. Thus, a hacker not only faces a major challenge in
determining the AN of the smart card and the coding used to construct the partial
authentication template EAi, but also encounters severe difficulties in cracking the encrypted
transmission packets exchanged between the terminal and the server.
For dictionary attacks, cracking a password needs either weak password strength or large
quantity of hash of the target password; two cases can be prevented by both strong hash
function algorithms such as MD5 and the SHA family and long character password with
numbers, mixed case, and symbols in Step 2.1.
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Assume that a hacker has attained the formation of the terminal (AN, EAi* , EBi*) in Steps
3.1~3.4 from the terminal and smart card, and then launches a replay attack to counterfeit a
legal user in the authentication process. In Step 3.5, a one-time session key (RK) is randomly
generated by the server. This key is valid only for the current authentication process. In
other words, old session keys cannot be re-used, and thus imitation attacks are thwarted.
4.1.3 Attacks originating within card issuing organization
This section demonstrates the robustness of the proposed scheme toward interior staff
attacks in the registration phase and authentication phase, respectively.
Registration phase
In the registration process, the users scan their finger in order to provide the system with the
fingerprint minutiae required to construct the finger template (see Step 2.2). The fingerprint
template Fi, stored in the Random Access Memory (RAM) of the terminal is utilized only in
the subsequent registration process. That is, to prevent exposure of the user’s biometric data
to any unauthorized third party, Fi and its related parameters are deleted as soon as the
authentication process is complete. Therefore, interior staff and external hackers have little
chance of acquiring Fi since it exists within the system for only a short period of time and,
moreover, its location within the terminal RAM varies dynamically.
Authentication phase
As shown in Fig. 6, the three components of the authentication template generated in the
proposed scheme are stored separately in the cards, terminal and servers (“on two different
physical components, namely (i) EAi is stored on the smart card; (ii) and (iii) EBi is stored at
the authentication server. Thus, even if the template data at the authentication server is
stolen by a dishonest member of staff, the authentication process cannot be completed since
the remaining template information is missing. In practice, a dishonest member of staff can
only complete the authentication without password and smart card, except someone is
capable of copying process by somehow copying the user’s card and acquiring the user’s
fingerprint from the imprint cup.
4.2 Computational complexity
In this section, the computational complexity of the proposed scheme is compared with that
of the schemes presented by Fan et al. (2006), Lin and Lai (2004), Kim et al. (2003) and J.K.
Lee et al. (2002) (see Table 1). Among the various computations performed by the different
schemes, the exponential operation in the decryption procedure (E) is the most time
consuming. It is observed that the number of exponential operations in the schemes
proposed by Lee et al. and Lin and Lai, respectively, is slightly higher than that in the
proposed scheme and significantly higher than that in the scheme proposed by Fan et al. In
addition, it is seen that the overall computational complexity of the scheme proposed in this
study is slightly higher than that of the scheme proposed by Fan et al. due to the separation
of the authentication data and the encryption of the symmetric keys during transmission.
Compared to the scheme proposed by Fan et al., the proposed scheme requires three
additional exponential operations and two additional merge operations. However, the
number of symmetric decryption operations is reduced by one, while the number of hash
and XOR operations is reduced by three and one, respectively. Significantly, the scheme
proposed by Fan et al. utilizes the Rabin algorithm (Rabin, 1979) to protect the symmetric
keys during transmission. Whilst this approach reduces the number of exponential
operations required, the security of the communications between the terminal and the
A New Fingerprint Authentication Scheme Based on Secret-Splitting for Enhanced Cloud Security
195
authentication server cannot be guaranteed in an open environment. By contrast, the scheme
proposed in this study uses the Diffie-Hellman key exchange /agreement algorithm to
protect the terminal-server communications. Thus, while a greater number of exponential
operations are required (i.e., to solve the Discrete-Log Problem), the security of the
transmissions is significantly improved relative to that in Fan et al.’s scheme.
It is acknowledged that the proposed scheme has certain limitations. For example, in the
event that the user loses his or her smart card, the CA cannot immediately re-issue a new
card since they do not possess the complete fingerprint template. In other words, the users
must repeat the registration process in order to obtain a new card. Furthermore, the
computational complexity of the proposed scheme is slightly higher than that of existing
schemes. However, compared to existing methods, the proposed scheme ensures the
security of the users’ biometric information even if the contents of the authentication
database are stolen. In other words, the proposed scheme achieves a compromise between
the need to reduce the computational cost of the remote authentication process and the need
to minimize the security threat posed by dishonest interior staff.
Scheme
Characteristic
Computational cost of lo
g
in
and authentication
p
hases
Store complete
biometric tem
p
late
Clock
s
y
nchronization
Pro
p
osed scheme 4E+3SE+3SD+H+2X+2M No No
Fan et al.
(
2006
)
E+3SE+4SD+4H+3X Client No
Lin and Lai (2004) 5E+3H+4X Client Yes
Kim et al. (2003)
(
Timestam
p
-based
)
4E+2H Server Yes
Kim et al. (2003)
(
Nonce-based
)
4E+1H Server No
J.K. Lee et al.
(
2002
)
7E+2H+2X Server Yes
Table 1. Comparison of related schemes (revised from Lee S.W. et al., 2005)
Note that E represents the computational time required to perform modular exponentiation;
SE denotes the computational time required to perform modular symmetric encryption; SD
is the computational time required to perform modular symmetric decryption computation;
H denotes the computational time required to perform a one-way hash function; X is the
computational time required to perform a modular exclusive-or operation; and M represents
the computational time required to perform a modular merge operation.
5. Conclusions
This paper has presented a novel remote authentication scheme based on a secret-splitting
concept for cloud computing applications. Compared to existing methods, the proposed
scheme has a number of important advantages, namely (i) the users can choose passwords
(PWi) for their smart cards at will; (ii) the smart card and server each store a partial
biometric template rather than the full template; and (iii) the partial templates are integrated
only when the users have successfully completed the login process in the authentication
phase. The proposed scheme is robust toward three common forms of attack, i.e., man-in-
the-middle attacks, dictionary attacks and replay attacks. As a result, it provides an effective
solution for enhancing the security of cloud computing applications, and is therefore
beneficial to SaaS service providers in improving user acceptance of their services.
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6. Acknowledgements
This study was supported partly by TWISC@NCKU, and by the National Science Council
under the Grants Nos. NSC100-2219-E-006-001 and NSC 99-2219-H-168-001.
7. References
Diffie W. & Hellman M. E. (1976). Multiuser Cryptographic Techniques, Proceedings of
National Computer Conference, New York, June 7-10, 1976
ElGamal T. (1985). A Public-Key Cryptosystem and a Signature Scheme Based on Discrete
Logarithms, Proceedings of IEEE Transactions on Information Theory, Vol.31, No. 4, pp.
469–472, ISSN 0018-9448
Fan C. I.; Lin Y. H. & Hsu R. H. (2006). Remote Password Authentication Scheme with Smart
Cards and Biometrics, Proceedings of 49th annual IEEE Global Telecommunications
Conference (GLOBECOM), pp.1-5, San Francisco, California, USA, 27 Nov, 2006
Jeong J.; Chung M. Y. & Choo H. (2006). Secure User Authentication Mechanism in Digital
Home Network Environments, Lecture Notes in Computer Science (LNCS), Vol.4096,
pp.345-354
Kim H. S.; Lee S. W. & Yoo K. Y. (2003). ID-based Password Authentication Scheme Using
Smart Cards and Fingerprints, ACM SIGOPS Operating Systems Review, Vol.37,
No.2, pp.32-41, ISSN 0163-5980
Lee J. K.; Ryu S. R. & Yoo K. Y. (2002). Fingerprint-based remote user authentication scheme
using smart cards, Electronics Letters, Vol.38, No.12, pp.554-555, ISSN 0013-5194.
Lee S. W.; Kim H. S. & Yoo K. Y. (2005). Efficient nonce-based remote user authentication
scheme using smart cards, Applied Mathematics and Computation, Vol.167, No.1, pp.
355-361, ISSN 0096-3003
Lin C. H. & Lai Y. Y. (2004). A flexible biometrics remote user authentication Scheme,
Computer Standards & Interfaces, Vol. 27, No.1, , p.19-23, ISSN 0920-5489
Mark K. H. (2006). Data theft scandal - what we can learn from India Opinion, In:
Offshoring, 6 Oct 2006. Available from
http://services.silicon.com/offshoring/0,380000487 7,39163049,00.htm
Mitchell C. J. & Tang O. (2005). Security of the Lin-Lai smart card based user authentication
scheme, Technical Report, Royal Holloway, University of London, 2005
Available from from http://www.rhul.ac.uk/mathematics/techreports
Miura N.; Nagasaka A. & Miyatake T. (2005). Extraction of Finger-Vein Patterns Using
Maximum Curvature Points in Image Profiles, Proceedings of the 9th IAPR Conference
on Machine Vision Applications (MVA2005), pp.347-350, Tsukuba Science City, Japan,
2005.
Pfitzmann A. (2008). Biometrics---How to Put to Use and How Not at All, In: TrustBus 2008,
Furnell S.M.; Katsikas S.K. & Lioy A. (Ed.), LNCS 5185, pp. 1–7, Springer-Verlag,
ISSN 0302-9743
Rabin M. O. (1979). Digitalized Signatures and Public-key Functions As Intractable As
Factorization, Technical Report of MIT/LCS/TR212, MIT Labatory, Computer Science
Cambridge, MA, USA
Scott M. (2004). Cryptanalysis of an ID-based password authentication scheme using smart
cards and fingerprints, ACM SIGOPS Operating Systems Review, Vol. 38, No. 2,
pp.73-75, ISSN:0163-5980
