International Journal of Distributed Sensor Networks 3
registration phase, where 𝑏is a high-entropy random number
selected by 𝑈
𝑖
and not revealed to the GW-node. In addition,
Sun’s scheme [11]suggestedthat𝑈
𝑖
only submits his/her
ID
𝑖
to the GW-node until receiving the smart-card which
includes the initial password selected by GW-node; 𝑈
𝑖
is
abletochangetheinitialpasswordimmediatelybyusingthe
password change operation.
2.2. User Impersonation Attack. User impersonation attack
canbecausedbymanyothersecurityawssuchasthe
privileged-inside attack discussed in Section 2.1, other legal
users being malicious, or the parameters in the smart-card
being extracted by attackers.
In registration phase, many users will receive the unique
and personalized smart-card from the identical GW-node.
However, the secret parameters which are generated by the
GW-node and related to smart-card, such as 𝐾 and 𝑥
𝑎
,are
kept unchanged for dierent users in some proposed scheme.
In other words, dierent users and identical GW-nodes share
the same secret parameters; namely, every entity does not
have the secret parameter or key belonging to it. If the smart-
card is stolen or the secret parameters are compromised,
then the whole sensor network will be vulnerable to the user
impersonation attack. For example, Li et al. [13]showedthat
an attacker 𝑈
𝑒
who has registered as a user of GW-node
can restore ℎ(𝐾) = 𝑁
𝑒
⊕ℎ(ID
𝑒
‖ PW
𝑒
) from his/her own
password and smart-card in Das’s scheme [1]. Note that 𝑥
𝑎
can be extracted from 𝑈
𝑒
’s smart-card directly. erefore, the
attacker 𝑈
𝑒
is able to impersonate another legal user or forge
nonregistered user to log in GW-node legally without being
noticed.
We suggest that GW-node distinguishes dierent users
by dierent secret parameters. For example, GW-node can
compute ℎ(ID
𝑖
‖𝑥
𝑎
) instead of 𝑥
𝑎
in registration phase,
takeasecurebillingserviceintroducedinLi’sscheme[13]
which stores a password/verier table, or add biometric keys
in register/login phase, and so forth. However, these tricks
are at the expense of anonymity. Namely, we can see from the
tricks that if the user’s identity ID
𝑖
or biometric keys are added
to register/login phase, the vulnerable schemes are robust
against user impersonation attack. erefore, to accomplish
secure aims, the schemes do not have the anonymity. In order
to avoid anonymity loss, it is essential to design a secure user
authentication scheme with anonymity for WSNs.
2.3. Guessing Attack. Guessing attack is a crucial concern
in any password-based system. e attacker can recover
ℎ(PW
𝑖
‖∗∗∗)through privileged-inside attack, node
compromise attack, or smart-card loss attack, where “∗∗
∗”isanacquiredformula.us,theattackercanguess
𝑈
𝑖
’s password in a relatively small dictionary containing all
the words about 𝑈
𝑖
. For example, in Das’s scheme [1], the
attacker 𝑈
𝑒
who has registered as a legal user of GW-node can
compute ℎ(ID
𝑖
‖ PW
𝑖
)=DID
𝑖
⊕ℎ(ID
𝑒
‖ PW
𝑒
)⊕DID
𝑒
[2], or
an adversary can obtain any user’s ℎ(ID
𝑖
‖ PW
𝑖
)=ℎ(𝑥
𝑎
‖𝑇)⊕
DID
𝑖
aer the secret parameter 𝑥
𝑎
stored in designated sensor
node is compromised through node compromise attack [14].
Nyang and Lee [2] suggested that the prevention of the oine
password guessing attack is using ℎ(ID
𝑖
‖ PW
𝑖
‖𝑥
𝑎
)
instead of ℎ(ID
𝑖
‖ PW
𝑖
). e other common improvement
method is sending user’s identity ID
𝑖
and ℎ(𝑏 ⊕ PW
𝑖
) to the
GW-node in registration phase; then 𝑈
𝑖
enters 𝑏 into his/her
smart-card aer receiving the personalized smart-card from
GW-node. ey claimed that their methods can resist oine
password guessing attack. However, they would not achieve
that goal if smart-card loss attack was taken into account (see
Section 2.6).
In fact, the improvements discussed above are not a
solution, which people fail to realize. Symmetric key tech-
niques and oine validation are widely used in login phase
of “smart-card-password” two-factor user authentication
schemes in WSN at present. Namely, 𝑈
𝑖
inserts its smart-
card to a terminal in login phase and keys ID
𝑖
and PW
𝑖
.
en the smart-card uses secret parameters and PW
𝑖
to com-
putesomeformulas.ecorrectnessoftheseformulaswill
determine whether users log in to the scheme successfully,
while it is independent of GW-node. Technically, there is
anunavoidableloophole;thatis,ifthesmart-cardisstolen
and secret parameters such as 𝑥
𝑎
and 𝑏 are leaked, the
scheme will not be safe anymore. is problem exists in
almost two-factor user authentication scheme. For example,
in He’s scheme [5], 𝐻
𝑖
,𝑉
𝑖
,𝑏 arestoredin𝑈
𝑖
’s smart-card,
where 𝐻
𝑖
=ℎ(𝑇
𝑖
)=ℎ(𝑉
𝑖
⊕ℎ(ID
𝑖
‖ ℎ(𝑏 ⊕ PW
𝑖
))).Ifthe
attacker obtains these parameters and user’s ID
𝑖
, he/she also
can attack by guessing. erefore, designing a genuine two-
factor user authentication scheme that can defeat guessing
attack is meaningful for the application.
2.4. Node Compromise Attack. Node compromise attack
refers to a series of attacks caused by a malicious or captured
sensornode.eseattacksincludeguessingattackbyobtain-
ing the hash of password, impersonation of other sensor
nodes by using secret parameters in captured sensor node,
and GW-node bypassing attack. GW-node bypassing attack
[3] means that the attacker can compute the legal messages to
gain the trust of other sensor nodes by bypassing GW-node.
e basic cause of above vulnerabilities is that several sensor
nodes 𝑆
𝑛
and GW-node share the same secret parameters
such as 𝑥
𝑎
.
To avoid node compromise attack, Huang et al. [14]
suggested using ℎ(𝑥
𝑠
‖ SID
𝑖
) instead of 𝑥
𝑠
as a shared key
between sensor node 𝑆
𝑖
and GW-node. ℎ(𝑥
𝑠
‖ SID
𝑖
) is stored
in sensor node beforehand, where 𝑥
𝑠
is generated securely
by the GW-node. Even if sensor node 𝑆
𝑖
is captured, the
attacker cannot recover the value of 𝑥
𝑠
and the shared key
ℎ(𝑥
𝑠
‖ SID
𝑗
). erefore, sensor node that had been captured
has no inuence on other sensor nodes and GW-node.
2.5. GW-Node Impersonation Attack. ere are at least two
situations where the attack occurred. e rst situation is
GW-node bypassing attack, namely, adversary steals the
secret shared key of GW-node from a captured sensor node
to impersonate GW-node (GW-node bypassing attack can
be regarded as GW-node impersonation attack). e second
situation is “smart-card loss attack.” at means adversary
steals secret parameters from smart-card, or a malicious
legitimate user recovers secret parameters from their own
smart-card and impersonates GW-node. In many schemes,