Hop by-hop message authentication and source privacy in wire-copy-copy

1
Hop-by-Hop Message Authentication and Source
Privacy in Wireless Sensor Networks
Jian Li Yun Li Jian Ren Jie Wu
Abstract—Message authentication is one of the most effective
ways to thwart unauthorized and corrupted messages from being
forwarded in wireless sensor networks (WSNs). For this reason,
many message authentication schemes have been developed, based
on either symmetric-key cryptosystems or public-key cryptosys-
tems. Most of them, however, have the limitations of high com-
putational and communication overhead in addition to lack of
scalability and resilience to node compromise attacks. To address
these issues, a polynomial-based scheme was recently introduced.
However, this scheme and its extensions all have the weakness of
a built-in threshold determined by the degree of the polynomial:
when the number of messages transmitted is larger than this
threshold, the adversary can fully recover the polynomial. In
this paper, we propose a scalable authentication scheme based on
elliptic curve cryptography (ECC). While enabling intermediate
nodes authentication, our proposed scheme allows any node to
transmit an unlimited number of messages without suffering the
threshold problem. In addition, our scheme can also provide
message source privacy. Both theoretical analysis and simulation
results demonstrate that our proposed scheme is more efficient
than the polynomial-based approach in terms of computational
and communication overhead under comparable security levels
while providing message source privacy.
Index Terms—Hop-by-hop authentication, symmetric-key cryp-
tosystem, public-key cryptosystem, source privacy, simulation,
wireless sensor networks (WSNs), distributed algorithm, decen-
tralized control
I. INTRODUCTION
Message authentication plays a key role in thwarting unau-
thorized and corrupted messages from being forwarded in
networks to save the precious sensor energy. For this reason,
many authentication schemes have been proposed in literature
to provide message authenticity and integrity verification for
wireless sensor networks (WSNs) [1]–[5]. These schemes can
largely be divided into two categories: public-key based ap-
proaches and symmetric-key based approaches.
The symmetric-key based approach requires complex key
management, lacks of scalability, and is not resilient to large
numbers of node compromise attacks since the message sender
and the receiver have to share a secret key. The shared key
is used by the sender to generate a message authentication
code (MAC) for each transmitted message. However, for this
Jian Li and Jiaan Ren are with the Department of Electrical & Computer
Engineering, Michigan State University, East Lansing, MI 48824-1226. Email:
{lijian6, renjian}@egr.msu.edu.
Yun Li is with the SPD Department, Microsoft, Redmond, WA 98052. Email:
yunl@microsoft.com.
Jie Wu is with the Department of Computer & Information Sciences, Temple
University, Philadelphia, PA 19122. Email: jiewu@temple.edu
method, the authenticity and integrity of the message can only
be verified by the node with the shared secret key, which is
generally shared by a group of sensor nodes. An intruder can
compromise the key by capturing a single sensor node. In
addition, this method does not work in multicast networks.
To solve the scalability problem, a secret polynomial based
message authentication scheme was introduced in [3]. The idea
of this scheme is similar to a threshold secret sharing, where the
threshold is determined by the degree of the polynomial. This
approach offers information-theoretic security of the shared
secret key when the number of messages transmitted is less than
the threshold. The intermediate nodes verify the authenticity
of the message through a polynomial evaluation. However,
when the number of messages transmitted is larger than the
threshold, the polynomial can be fully recovered and the system
is completely broken.
An alternative solution was proposed in [4] to thwart the
intruder from recovering the polynomial by computing the
coefficients of the polynomial. The idea is to add a random
noise, also called a perturbation factor, to the polynomial so
that the coefficients of the polynomial cannot be easily solved.
However, a recent study shows that the random noise can be
completely removed from the polynomial using error-correcting
code techniques [6].
For the public-key based approach, each message is transmit-
ted along with the digital signature of the message generated
using the sender’s private key. Every intermediate forwarder
and the final receiver can authenticate the message using the
sender’s public key [7], [8]. One of the limitations of the public-
key based scheme is the high computational overhead. The
recent progress on elliptic curve cryptography (ECC) shows
that the public-key schemes can be more advantageous in
terms of computational complexity, memory usage, and security
resilience, since public-key based approaches have a simple and
clean key management [9].
In this paper, we propose an unconditionally secure and
efficient source anonymous message authentication (SAMA)
scheme based on the optimal modified ElGamal signa-
ture (MES) scheme on elliptic curves. This MES scheme is
secure against adaptive chosen-message attacks in the random
oracle model [10]. Our scheme enables the intermediate nodes
to authenticate the message so that all corrupted message can
be detected and dropped to conserve the sensor power. While
achieving compromise-resiliency, flexible-time authentication
and source identity protection, our scheme does not have the
threshold problem. Both theoretical analysis and simulation
IEEE Transactions on Parallel and Distributed Systems,Volume:25,Issue:5,Issue Date : May.2014

2
results demonstrate that our proposed scheme is more efficient
than the polynomial-based algorithms under comparable secu-
rity levels.
The major contributions of this paper are the following:
1) We develop a source anonymous message authentication
code (SAMAC) on elliptic curves that can provide un-
conditional source anonymity.
2) We offer an efficient hop-by-hop message authentication
mechanism for WSNs without the threshold limitation.
3) We devise network implementation criteria on source
node privacy protection in WSNs.
4) We propose an efficient key management framework to
ensure isolation of the compromised nodes.
5) We provide extensive simulation results under ns-2 and
TelosB on multiple security levels.
To the best of our knowledge, this is the first scheme that
provides hop-by-hop node authentication without the threshold
limitation, and has performance better than the symmetric-key
based schemes. The distributed nature of our algorithm makes
the scheme suitable for decentralized networks.
The rest of this paper is organized as follows: Section II
presents the terminology and the preliminary that will be used
in this paper. Section III discusses the related work, with a
focus on polynomial-based schemes. Section IV describes the
proposed source anonymous message authentication scheme on
elliptic curves. Section V discusses the ambiguity set (AS)
selection strategies for source privacy. Section VI describes key
management and compromised node detection. Performance
analysis and simulation results are provided in Section VII.
We conclude in Section VIII.
II. TERMINOLOGY AND PRELIMINARY
In this section, we will briefly describe the terminology and
the cryptographic tools that will be used in this paper.
A. Threat Model and Assumptions
The wireless sensor networks are assumed to consist of a
large number of sensor nodes. We assume that each sensor
node knows its relative location in the sensor domain and is
capable of communicating with its neighboring nodes directly
using geographic routing. The whole network is fully connected
through multi-hop communications. We assume there is a secu-
rity server (SS) that is responsible for generation, storage and
distribution of the security parameters among the network. This
server will never be compromised. However, after deployment,
the sensor nodes may be captured and compromised by attack-
ers. Once compromised, all information stored in the sensor
nodes can be accessed by the attackers. The compromised nodes
can be reprogrammed and fully controlled by the attackers.
However, the compromised nodes will not be able to create new
public keys that can be accepted by the SS and other nodes.
Based on the above assumptions, this paper considers two
types of attacks launched by the adversaries:
• Passive attacks: Through passive attacks, the adversaries
could eavesdrop on messages transmitted in the network
and perform traffic analysis.
• Active attacks: Active attacks can only be launched from
the compromised sensor nodes. Once the sensor nodes
are compromised, the adversaries will obtain all the in-
formation stored in the compromised nodes, including
the security parameters of the compromised nodes. The
adversaries can modify the contents of the messages, and
inject their own messages.
B. Design Goals
Our proposed authentication scheme aims at achieving the
following goals:
• Message authentication: The message receiver should be
able to verify whether a received message is sent by the
node that is claimed, or by a node in a particular group.
In other words, the adversaries cannot pretend to be an
innocent node and inject fake messages into the network
without being detected.
• Message integrity: The message receiver should be able
to verify whether the message has been modified en-route
by the adversaries. In other words, the adversaries cannot
modify the message content without being detected.
• Hop-by-hop message authentication: Every forwarder on
the routing path should be able to verify the authenticity
and integrity of the messages upon reception.
• Identity and location privacy: The adversaries cannot de-
termine the message sender’s ID and location by analyzing
the message contents or the local traffic.
• Node compromise resilience: The scheme should be re-
silient to node compromise attacks. No matter how many
nodes are compromised, the remaining nodes can still be
secure.
• Efficiency: The scheme should be efficient in terms of both
computational and communication overhead.
C. Terminology
Privacy is sometimes referred to as anonymity. Communica-
tion anonymity in information management has been discussed
in a number of previous works [11]–[16]. It generally refers to
the state of being unidentifiable within a set of subjects. This
set is called the ambiguity set (AS). Sender anonymity means
that a particular message is not linkable to any sender, and no
message is linkable to a particular sender.
We will start with the definition of the unconditionally secure
source anonymous message authentication scheme (SAMA).
Definition 1 (SAMA). A SAMA consists of the following two
algorithms:
• Generate (m, Q1, Q2, · · · , Qn): Given a message m
and the public keys Q1, Q2, · · · , Qn of the AS S =
{A1, A2, · · · , An}, the actual message sender At, 1  t 
n, produces an anonymous message S(m) using its own
private key dt.

3
• Verify S(m): Given a message m and an anonymous
message S(m), which includes the public keys of all
members in the AS, a verifier can determine whether S(m)
is generated by a member in the AS.
The security requirements for SAMA include:
• Sender ambiguity: The probability that a verifier success-
fully determines the real sender of the anonymous message
is exactly 1/n, where n is the total number of members in
the AS.
• Unforgeability: An anonymous message scheme is un-
forgeable if no adversary, given the public keys of
all members of the AS and the anonymous messages
m1, m2, · · · , mn adaptively chosen by the adversary, can
produce in polynomial time a new valid anonymous mes-
sage with non-negligible probability.
In this paper, the user ID and the user public key will be
used interchangeably without making any distinctions.
D. Modified ElGamal Signature Scheme (MES)
Definition 2 (MES). The modified ElGamal signature
scheme [17] consists of the following three algorithms:
Key generation algorithm: Let p be a large prime and g
be a generator of Z⇤
p. Both p and g are made public. For a
random private key x 2 Zp, the public key y is computed from
y = gx
mod p.
Signature algorithm: The MES can also have many vari-
ants [18], [19]. For the purpose of efficiency, we will describe
the variant, called optimal scheme. To sign a message m, one
chooses a random k 2 Z⇤
p 1, then computes the exponentiation
r = gk
mod p and solves s from:
s = rxh(m, r) + k mod (p 1), (1)
where h is a one-way hash function. The signature of message
m is defined as the pair (r, s).
Verification algorithm: The verifier checks whether the
signature equation gs
= ryrh(m,r)
mod p. If the equality
holds true, then the verifier Accepts the signature, and Rejects
otherwise.
III. RELATED WORK
In [1], [2], symmetric key and hash based authentication
schemes were proposed for WSNs. In these schemes, each
symmetric authentication key is shared by a group of sensor
nodes. An intruder can compromise the key by capturing a
single sensor node. Therefore, these schemes are not resilient
to node compromise attacks. Another type of symmetric-key
scheme requires synchronization among nodes. These schemes,
including TESLA [5] and its variants, can also provide message
sender authentication. However, this scheme requires initial
time synchronization, which is not easy to be implemented in
large scale WSNs. In addition, they also introduce delay in
message authentication, and the delay increases as the network
scales up.
A secret polynomial based message authentication scheme
was introduced in [3]. This scheme offers information-theoretic
security with ideas similar to a threshold secret sharing, where
the threshold is determined by the degree of the polynomial.
When the number of messages transmitted is below the thresh-
old, the scheme enables the intermediate node to verify the
authenticity of the message through polynomial evaluation.
However, when the number of messages transmitted is larger
than the threshold, the polynomial can be fully recovered and
the system is completely broken. To increase the threshold
and the complexity for the intruder to reconstruct the secret
polynomial, a random noise, also called a perturbation factor,
was added to the polynomial in [4] to thwart the adversary
from computing the coefficient of the polynomial. However,
the added perturbation factor can be completely removed using
error-correcting code techniques [6].
For the public-key based approach, each message is transmit-
ted along with the digital signature of the message generated
using the sender’s private key. Every intermediate forwarder
and the final receiver can authenticate the message using the
sender’s public key. The recent progress on elliptic curve cryp-
tography (ECC) shows that the public-key schemes can be more
advantageous in terms of memory usage, message complexity,
and security resilience, since public-key based approaches have
a simple and clean key management [9].
The existing anonymous communication protocols are
largely stemmed from either mixnet [11] or DC-net [12]. A
mixnet provides anonymity via packet re-shuffling through
a set of mix servers (with at least one being trusted). In
a mixnet, a sender encrypts an outgoing message, and the
ID of the recipient, using the public key of the mix. The
mix accumulates a batch of encrypted messages, decrypts and
reorders these messages, and forwards them to the recipients.
Since mixnet-like protocols rely on the statistical properties of
the background traffic, they cannot provide provable anonymity.
DC-net [12], [16] is an anonymous multi-party computation
scheme. Some pairs of the participants are required to share
secret keys. DC-net provides perfect (information-theoretic)
sender anonymity without requiring trusted servers. However, in
DC-net, only one user can send at a time, so it takes additional
bandwidth to handle collision and contention.
Recently, message sender anonymity based on ring signatures
was introduced [20]. This approach enables the message sender
to generate a source anonymous message signature with content
authenticity assurance. To generate a ring signature, a ring
member randomly selects an AS and forges a message signature
for all other members. Then he uses his trap-door information
to glue the ring together. The original scheme has very limited
flexibility and very high complexity. Moreover, the original
paper only focuses on the cryptographic algorithm, and the
relevant network issues were left unaddressed.
IV. PROPOSED SOURCE ANONYMOUS MESSAGE
AUTHENTICATION (SAMA) ON ELLIPTIC CURVES
In this section, we propose an unconditionally secure and
efficient source anonymous message authentication scheme

4
(SAMA). The main idea is that for each message m to be
released, the message sender, or the sending node, generates
a source anonymous message authenticator for the message
m. The generation is based on the MES scheme on elliptic
curves. For a ring signature, each ring member is required to
compute a forgery signature for all other members in the AS.
In our scheme, the entire SAMA generation requires only three
steps, which link all non-senders and the message sender to the
SAMA alike. In addition, our design enables the SAMA to be
verified through a single equation without individually verifying
the signatures.
A. Proposed MES Scheme on Elliptic Curves
Let p > 3 be an odd prime. An elliptic curve E is defined
by an equation of the form:
E : y2
= x3
+ ax + b mod p,
where a, b 2 Fp, and 4a3
+ 27b2
6⌘ 0 mod p. The set E(Fp)
consists of all points (x, y) 2 Fp on the curve, together with a
special point O, called the point at infinity.
Let G = (xG, yG) be a base point on E(Fp) whose order is
a very large value N. User A selects a random integer dA 2
[1, N 1] as his private key. Then, he can compute his public
key QA from QA = dA ⇥ G.
Signature generation algorithm: For Alice to sign a
message m, she follows these steps:
1) Select a random integer kA, 1  kA  N 1.
2) Calculate r = xA mod N, where (xA, yA) = kAG. If
r = 0, go back to step 1.
3) Calculate hA
l
h(m, r), where h is a cryptographic
hash function, such as SHA-1, and
l
denotes the l
leftmost bits of the hash.
4) Calculate s = rdAhA + kA mod N. If s = 0, go back to
step 2.
5) The signature is the pair (r, s).
Signature verification algorithm: For Bob to authenticate
Alice’s signature, he must have a copy of her public key QA,
then he:
1) Checks that QA 6= O, otherwise invalid
2) Checks that QA lies on the curve
3) Checks that nQA = O
After that, Bob follows these steps to verify the signature:
1) Verify that r and s are integers in [1, N 1]. If not, the
signature is invalid.
2) Calculate hA
l
h(m, r), where h is the same function
used in the signature generation.
3) Calculate (x1, x2) = sG rhAQA mod N.
4) The signature is valid if r = x1 mod N, invalid other-
wise.
B. Proposed SAMA on Elliptic Curves
Suppose that the message sender (say Alice) wishes to
transmit a message m anonymously from her network node to
any other nodes. The AS includes n members, A1, A2, · · · , An,
e.g., S = {A1, A2, · · · , An}, where the actual message sender
Alice is At, for some value t, 1  t  n. In this paper, we
will not distinguish between the node Ai and its public key
Qi. Therefore, we also have S = {Q1, Q2, · · · , Qn}.
Authentication generation algorithm: Suppose m is a
message to be transmitted. The private key of the message
sender Alice is dt, 1  t  N. To generate an efficient SAMA
for message m, Alice performs the following three steps:
1) Select a random and pairwise different ki for each 1 
i  n 1, i 6= t and compute ri from (ri, yi) = kiG.
2) Choose a random ki 2 Zp and compute rt from (rt, yt) =
ktG
P
i6=t
rihiQi such that rt 6= 0 and rt 6= ri for any
i 6= t, where hi
l
h(m, ri).
3) Compute s = kt +
P
i6=t
ki + rtdtht mod N.
The SAMA of the message m is defined as:
S(m) = (m, S, r1, y1, · · · , rn, yn, s).
C. Verification of SAMA
Verification algorithm: For Bob to verify an alleged
SAMA (m, S, r1, y1, · · · , rn, yn, s), he must have a copy of
the public keys Q1, · · · , Qn. Then he:
1) Checks that Qi 6= O, i = 1, · · · , n, otherwise invalid
2) Checks that Qi, i = 1, · · · , n lies on the curve
3) Checks that nQi = O, i = 1, · · · , n
After that, Bob follows these steps:
1) Verify that ri, yi, i = 1, · · · , n and s are integers in
[1, N 1]. If not, the signature is invalid.
2) Calculate hi
l
h(m, ri), where h is the same function
used in the signature generation.
3) Calculate (x0, y0) = sG
nP
i=1
rihiQi
4) The signature is valid if the first coordinate of
P
i
(ri, yi)
equals x0, invalid otherwise.
In fact, if the SAMA has been correctly generated without
being modified, then we compute:
(x0, y0) = sG
nX
i=1
rihiQi
= (kt +
X
i6=t
ki + rtdtht)G
X
i
rihiQi
=
X
i6=t
kiG + (ktG
X
i6=t
rihiQi)
=
X
i6=t
(ri, yi) + (rt, yt)
=
X
i
(ri, yi).
Therefore, the verifier should always Accept the SAMA.
Remark 1. It is apparent that when n = 1, SAMA becomes a
simple signature algorithm.

5
D. Security Analysis
In this subsection, we will prove that the proposed SAMA
scheme can provide unconditional source anonymity and prov-
able unforgeability against adaptive chosen-message attacks.
1) Anonymity: In order to prove that the proposed SAMA
can ensure unconditional source anonymity, we have to prove
that: (i) for anybody other than the members of S, the prob-
ability to successfully identify the real sender is 1/n, and (ii)
anybody from S can generate SAMAs.
Theorem 1. The proposed source anonymous message authen-
tication scheme (SAMA) can provide unconditional message
sender anonymity.
Proof: The identity of the message sender is uncondi-
tionally protected with the proposed SAMA scheme. This is
because, regardless of the sender’s identity, there are exactly
(N 1)(N 2) · · · (N n) different options to generate the
SAMA. All of them can be chosen by any members in the AS
during the SAMA generation procedure with equal probability
without depending on any complexity-theoretic assumptions.
The proof for the second part, that anybody from S can generate
the SAMA, is straightforward. This finishes the proof of this
theorem.
2) Unforgeability: The design of the proposed SAMA relies
on the ElGamal signature scheme. Signature schemes can
achieve different levels of security. Security against existential
forgery under adaptive-chosen message attacks is the maximum
level of security.
In this section, we will prove that the proposed SAMA
is secure against existential forgery under adaptive-chosen
message attacks in the random oracle model [21]. The security
of our result is based on elliptic curve cryptography (ECC),
which assumes that the computation of discrete logarithms on
elliptic curves is computationally infeasible. In other words, no
efficient algorithms are known for non-quantum computers.
We will introduce two lemmas. Lemma 1 is the Splitting
Lemma, which is a well-known probabilistic lemma from
reference [10]. The basic idea of the Splitting Lemma is that
when a subset Z is “large” in a product space X ⇥ Y , it will
have many “large” sections. Lemma 2 is a slight modification
of the Forking Lemma presented in [10]. The proofs of the two
lemmas are mainly probability theory related. We will skip the
proofs of these two lemmas here.
Lemma 1 (The Splitting Lemma). Let Z ⇢ X ⇥ Y such that
Pr[(x, y) 2 Z] ". For any ↵ < ", define W = {(x, y) 2
X ⇥ Y | Pr
y02Y
[(x, y0
) 2 Z] " ↵}, and ¯W = (X ⇥ Y )W,
then the following statements hold:
1) Pr[W] ↵.
2) 8(x, y) 2 W, Pry02Y [(x, y0
) 2 Z] " ↵.
3) Pr[W|Z] ↵/".
Lemma 2 (The Forking Lemma). Let A be a Probabilistic
Polynomial Time (PPT) Turing machine. Given only the pub-
lic data as input, if A can find, with non-negligible proba-
bility, a valid SAMA (m, S, r1, y1, · · · , rn, yn, h1, · · · , hn, s)
within a bounded polynomial time T, then with non-negligible
probability, a replay of this machine, which has control
over A and a different oracle, outputs another valid SAMA
(m, S, r1, y1, · · · , rn, yn, h0
1, · · · , h0
n, s), such that hi = h0
i, for
all 1  i  v, i 6= j for some fixed j.
Theorem 2. The proposed SAMA is secure against adaptive
chosen-message attacks in the random oracle model.
Proof: (Sketch) If an adversary can forge a valid SAMA
with non-negligible probability, then according to the Fork-
ing Lemma, the adversary can obtain two valid SAMAs
S(m) = (m, S, r1, y1, · · · , rn, yn, h1, · · · , hn, s), and S(m) =
(m, S, r1, y1, · · · , rn, yn, h0
1, · · · , h0
n, s), such that for 1  i 
n, i 6= j, hi = h0
i, hj 6= h0
j and sG
nP
i=1
rihiQi =
P
i
(ri, yi),
s0
G
nP
i=1
rih0
iQi =
P
i
(ri, yi).
Subtracting these two equations, we obtain (s s0
)G =
rj(hj h0
j)Qj. Equivalently, we have:
Qj =
s s0
rj(hj h0
j)
G.
Therefore, we can compute the elliptic curve discrete loga-
rithm of Qj in base G with non-negligible probability, which
contradicts the assumption that it is computationally infeasible
to compute the elliptic discrete logarithm of Qj in base G.
Therefore, it is computationally infeasible for any adversary to
forge a valid SAMA.
V. AS SELECTION AND SOURCE PRIVACY
The appropriate selection of an AS plays a key role in
message source privacy, since the actual message source node
will be hidden in the AS. In this section, we will discuss
techniques that can prevent the adversaries from tracking the
message source through the AS analysis in combination with
local traffic analysis.
Before a message is transmitted, the message source node
selects an AS from the public key list in the SS as its choice.
This set should include itself, together with some other nodes.
When an adversary receives a message, he can possibly find
the direction of the previous hop, or even the real node of the
previous hop. However, the adversary is unable to distinguish
whether the previous node is the actual source node or simply
a forwarder node if the adversary is unable to monitor the
traffic of the previous hop. Therefore, the selection of the AS
should create sufficient diversity so that it is infeasible for the
adversary to find the message source based on the selection of
the AS itself.
Some basic criteria for the selection of the AS can be
described as follows:
• To provide message source privacy, the message source
needs to select the AS to include nodes from all directions
of the source node. In particular, the AS should include
nodes from the opposite direction of the successor node.
In this way, even the immediate successor node will not

6
D
S
Network
A
Active routing pathNodes in the AS Nodes not in the AS
Fig. 1. Anonymous set selection in active routing
be able to distinguish the message source node from the
forwarder based on the message that it receives.
• Though the message source node can select any node in
the AS, some nodes in the AS may not be able to add any
ambiguity to the message source node. For instance, the
nodes that are apparently impossible or very unlikely to
be included in the AS based on the geographic routing.
Therefore, these nodes are not appropriate candidates for
the AS. They should be excluded from the AS for energy
efficiency.
• To balance the source privacy and efficiency, we should
try to select the nodes to be within a predefined distance
range from the routing path. We recommend selecting an
AS from the nodes in a band that covers the active routing
path. However, the AS does not have to include all the
nodes in the routing path.
• The AS does not have to include all nodes in that range,
nor does it have to include all the nodes in the active
routing path. In fact, if all nodes are included in the AS,
then this may help the adversary to identity the possible
routing path and find the source node.
As an example, suppose we want to transmit a packet from
source node S to destination node D in Fig. 1. We select the
AS to include only nodes marked with , while nodes marked
as • will not be included in the AS. Of all these nodes, some
of them are on the active routing path, while others are not.
However, all these nodes are located within the shaded band
area surrounding the active routing path. Suppose node A is
compromised, unless node A collaborates with other nodes and
can fully monitor the traffic of the source node S, it will not
be able to determine whether S is the source node, or simply
a forwarder. Similar analysis is also true for other nodes.
Any node in the active routing path can verify the contents’
authenticity and integrity. However, anybody who receives a
packet in the transmission can possibly exclude some of the
nodes in the WSNs as the possible source node. Inclusion of
these nodes in the AS will not increase the source privacy.
Nevertheless, the more the nodes included in the AS are, the
higher the energy cost will be. Therefore, the selection of the
AS has to be done with care so that the energy cost and the
source privacy can both be optimized.
In addition, to balance the power consumption between
authenticity and integrity verification, and the possibility that
corrupted messages are being forwarded, the verification ser-
vice may not have to take place in every hop; instead, it may
be configured to take place in every other hop, for instance.
AS1
AS3
AS2
Fig. 2. Compromised node detection
VI. KEY MANAGEMENT AND COMPROMISED NODE
DETECTION
In our scheme, we assume that there is an SS whose
responsibilities include public-key storage and distribution in
the WSNs. We assume that the SS will never be compromised.
However, after deployment, the sensor node may be captured
and compromised by the attackers. Once compromised, all
information stored in the sensor node will be accessible to the
attackers. We further assume that the compromised node will
not be able to create new public keys that can be accepted by
the SS.
For efficiency, each public key will have a short identity. The
length of the identity is based on the scale of the WSNs.
A. Compromised Node Detection
As a special scenario, we assume that all sensor information
will be delivered to a sink node, which can be co-located with
the SS. As described in Section V, when a message is received
by the sink node, the message source is hidden in an AS. Since
the SAMA scheme guarantees that the message integrity is
untampered, when a bad or meaningless message is received by
the sink node, the source node is viewed as compromised. If the
compromised source node only transmits one message, it would
be very difficult for the node to be identified without additional
network traffic information. However, when a compromised
node transmits more than one message, the sink node can
narrow the possible compromised nodes down to a very small
set.
As shown in Fig. 2, we use the circle to represent an AS.
When only one message is transmitted, the sink node can only
obtain the information that the source node will be in a set,
say AS1. When the compromised source node transmits two
messages, the sink node will be able to narrow the source
node down to the set with both vertical lines and horizontal
lines. When the compromised source node transmits three
messages, the source node will be further narrowed down to
the shaded area. Therefore, if the sink node keeps tracking
the compromised message, there is a high probability that the
compromised node can be isolated.

7
If the compromised nodes repeatedly use the same AS,
it makes traffic analysis of the compromised nodes feasible,
which will increase the likelihood for the compromised nodes
to be identified and captured.
When a node has been identified as compromised, the SS
can remove its public key from its public key list. It can also
broadcast the node’s short identity to the entire sensor domain
so that any sensor node that uses the stored public key for an AS
selection can update its key list. Once the public key of a node
has been removed from the public key list, and/or broadcasted,
any message with the AS containing the compromised node
should be dropped without any process in order to save the
precious sensor power.
VII. PERFORMANCE ANALYSIS
In this section, we will evaluate our proposed authentica-
tion scheme through both theoretical analysis and simulation
demonstrations. We will compare our proposed scheme with the
bivariate polynomial-based symmetric-key scheme described
in [3], [4]. A fair comparison between our proposed scheme and
the scheme proposed in [4] should be performed with n = 1.
A. Theoretical Analysis
Key management is one of the major issues for secret-key
based authentication schemes. This is especially true for large
scale WSNs. While many of these schemes are designed to
provide node authentication, they can only provide end-to-end
node authentication using the secret key shared between the
two nodes, which implies that only the receiver can verify
the authenticity of the messages en-route. This means that
no intermediate node can authenticate the message in general.
The intermediate nodes may have to forward a manipulated
message for many hops before the message can finally be
authenticated and dropped by the receiving node. This not only
consumes extra sensor power, but also increases the network
collision and decreases the message delivery ratio. In addition
to performance improvement, enabling intermediate node au-
thentication will thwart adversaries from performing denial-of-
service attacks through message manipulation to deplete the
energy and communication resources of the wireless network.
Therefore, developing a protocol that can provide hop-by-hop
intermediate node authentication is an important research task.
Most of the authentication schemes are based on symmetric-
key schemes, including the polynomial evaluation based thresh-
old authentication scheme [4]. The secret bivariate polynomial
is defined as [3]:
f(x, y) =
dxX
i=0
dy
X
j=0
Ai,jxi
yj
,
where each coefficient Ax,y is an element of a finite field Fp,
and dx and dy are the degrees of this polynomial. dx and dy
are also related to the message length and the computational
complexity of this scheme. From the performance aspect, dx
and dy should be as short as possible.
On the other hand, it is easy to see that when either more
than dy + 1 messages transmitted from the base station are
received and recorded by the intruders, or more than dx + 1
sensor nodes have been compromised, the intruders can recover
the polynomial f(x, y) via Lagrange interpolation. In this case,
the security of the system is totally broken and the system
cannot be used anymore. This property requires that both dx
and dy be very large for the scheme to be resilient to node
compromise attacks.
An alternative approach based on perturbation of the polyno-
mial was also explored. The main idea is to add a small amount
of random noise to the polynomial in the original scheme so that
the adversaries will no longer be able to solve the coefficients
using Lagrange interpolation. However, this technique is proved
to be vulnerable to security attacks [6], since the random noise
can be removed from the polynomial using error-correcting
techniques.
While hop-by-hop authentication can be achieved through
a public-key encryption system, the public-key based schemes
were generally considered as not preferred, mainly due to their
high computational overhead. However, our research demon-
strates that it is not always true, especially for elliptic curve
public-key cryptosystems.
In our scheme, each SAMA contains an AS of n randomly
selected nodes that dynamically changes for each message. For
n = 1, our scheme can provide at least the same security as the
bivariate polynomial-based scheme. For n > 1, we can provide
extra source privacy benefits. Even if one message is corrupted,
other messages transmitted in the network can still be secure.
Therefore, n can be much smaller than the parameters dx and
dy. In fact, even a small n may provide adequate source privacy,
while ensuring high system performance.
In addition, in the bivariate polynomial-based scheme, there
is only one base station that can send messages. All the other
nodes can only act as intermediate nodes or receivers. This
property makes the base station easy to attack, and severely
narrows the applicability of this scheme. In fact, the major
traffic in WSNs is packet delivery from the sensor nodes to
the sink node. In this case, our scheme enables every node to
transmit the message to the sink node as a message initiator.
The recent progress on elliptic curve cryptography (ECC)
has demonstrated that the public-key based schemes have more
advantages in terms of memory usage, message complexity, and
security resilience, since public-key based approaches have a
simple and clean key management [9].
B. Experimental Results
In this section, we implement the bivariate polynomial-based
scheme and our proposed scheme in a real world comparison.
The comparison is based on comparable security levels.
The implementation in [4] was carried out on Mica2 plat-
form, which is 8MHz, while our implementation is carried out
on Telosb platform, which is 4MHz. We first provide simulation
in Table I to compare and justify our parameter selections. From
the table, we can see that our results is comparable with the

8
TABLE I
PERFORMANCE COMPARISON OF THE BIVARIATE POLYNOMIAL-BASED
SCHEME IN TWO DIFFERENT SCENARIOS: (A) THE ORIGINAL
IMPLEMENTATION UNDER 8MHZ MICA2 PLATFORM, AND (B) OUR
IMPLEMENTATION UNDER 4MHZ TELOSB.
(a). Original implementation [4]
dx, dy = 3 dx, dy = 4
ROM RAM Sign Verf ROM RAM Sign Verf
(KB) (B) (ms) (ms) (KB) (B) (ms) (ms)
14.78 1938 5.8 57.89 15.04 2211 7.59 70.8
(b). Our implementation
dx, dy = 3 dx, dy = 4
ROM RAM Sign Verf ROM RAM Sign Verf
(KB) (B) (ms) (ms) (KB) (B) (ms) (ms)
13.61 1938 9 108 13.65 2302 11.73 126.93
original paper. This justifies that the performance comparisons
between our scheme and the algorithm proposed in [4] using
different parameters are consistent and reasonable.
1) Simulation parameter setup: The bivariate polynomial-
based scheme is a symmetric-key based implementation, while
our scheme is based on ECC. This requires us to determine the
comparable key sizes. If we choose the key size to be l for the
symmetric-key cryptosystem, then the key size for our proposed
ECC should be 2l according to [22], which is much shorter than
the traditional public-key cryptosystem. This progress facilitates
the implementation of the authentication scheme using ECC.
In our simulation setting, we choose five security levels,
which are indicated by the symmetric-key sizes l: 24bit, 32bit,
40bit, 64bit, and 80bit, respectively. The comparable key sizes
of our scheme are 48bit, 64bit, 80bit, 128bit, and 160bit,
respectively.
We also need to determine dx and dy for the bivariate
polynomial-based scheme, and the n for our scheme. In our
simulation, we select dx equal to dy and choose three values for
them: 80, 100, and 150. We assume that WSNs do not contain
more than 216
nodes in our simulation, which is reasonably
large. For size n of the AS, we choose three values in the
simulation: 10, 15 and 20.
We will compare the computational overhead, communica-
tion overhead, delivery ratio, energy consumption, transmission
delay, and memory consumption of our proposed scheme with
the bivariate polynomial-based scheme.
2) Computational overhead: For a public-key based authen-
tication scheme, computational overhead is one of the most
important performance measurements. So we first performed
simulation to measure the process time. The simulations were
carried out in 16-bit, 4 MHz TelosB mote.
Table II shows the process time of our scheme and the bivari-
ate polynomial-based scheme for both authentication generation
and verification. In the simulations, we assume that the key
length of our scheme is 2l.
From the table, we have the following findings:
• For the bivariate polynomial-based scheme, the authenti-
cation generation time is much longer than the verifying
time; while for our proposed scheme, the verifying time
is about half of the authentication generation time, except
when n = 1, the generation time is shorter than the
verification time.
• Comparing bivariate polynomial-based scheme with our
proposed scheme for n = 1, we find that the generation
time of our scheme is less than 5% of the bivariate
polynomial-based scheme for all dx, dy, but the verifying
time is slightly longer when dx, dy is less than 100. When
dx, dy is longer than 150, the verifying times of the two
schemes are comparable.
• The memory consumption of our proposed scheme is
slightly less than the bivariate polynomial-based scheme
in all scenarios.
• For our proposed scheme, to provide source privacy, the
cost of generation time and verifying time increase linearly
with n.
3) Communication overhead and message transmission de-
lay: The communication overhead is determined by the mes-
sage length. For the bivariate polynomial-based scheme, each
message is transmitted in the form of < m, MAFm(y) >,
where MAFm(y) is defined as: MAFm(y) = f(h(m), y) =
Pdy
j=0 Mjyj
. MAFm(y) is represented by its dy+1 coefficients
Mi, 2 Zp, 0  i  dy, where p 2 (2l 1
, 2l
) is a large prime
number. The total length of the message is l(dy + 1).
For our scheme, the message format is:
(m, S, r1, y1, · · · , rn, yn, s), where m, s, ri, yi are all numbers
with length L = 2l. S is the ID list for all the nodes included
in the AS. Assuming the network is composed of nodes
in total, each ID will be of the length: dlog2 e. When n
nodes are included in the AS, the length of S is ndlog2 e.
Therefore, the total length of one message for our scheme is:
4l(n + 1) + ndlog2 e.
The large communication overhead of the polynomial-based
scheme will increase the energy consumption and message
delay. The simulation results in Fig. 3(a) and Fig. 3(b) demon-
strate that our proposed scheme has a much lower energy con-
sumption and message transmission delay. These simulations
were carried out in ns-2 on RedHat Linux system. The security
levels 1, 2, 3, 4 correspond to symmetric key sizes 24bit, 32bit,
40bit, 64bit, and elliptic curves key size 48bit, 64bit, 80bit,
128bit, respectively.
We also conduct simulations to compare the delivery ratios
using ns-2 on RedHat Linux system. The results show that our
scheme is slightly better than the bivariate polynomial-based
scheme in delivery ratio. The results are given in Fig. 3(c).
Our simulation on memory consumption derived in TelosB,
see Table III, shows the overall memory consumption for
bivariate polynomial-based scheme is at least 5 times larger
than our proposed scheme.
VIII. CONCLUSION
In this paper, we first proposed a novel and efficient source
anonymous message authentication scheme (SAMA) based on
elliptic curve cryptography (ECC). While ensuring message
sender privacy, SAMA can be applied to any message to
provide message content authenticity. To provide hop-by-hop

9
TABLE II
PROCESS TIME (S) FOR THE TWO SCHEMES (16-BIT, 4 MHZ TELOSB MOTE)
Polynomial-based approach Proposed approach
dx, dy = 80 dx, dy = 100 dx, dy = 150 n = 1 n = 10 n = 15 n = 20
Gen Verify Gen Verify Gen Verify Gen Verify Gen Verify Gen Verify Gen Verify
l = 24 9.31 0.25 14.45 0.31 31.95 0.46 0.24 0.53 4.24 2.39 6.16 3.51 8.38 4.44
l = 32 12.95 0.33 20.05 0.41 44.60 0.62 0.34 0.80 5.99 3.32 8.92 5.05 12.19 6.42
l = 40 13.32 0.35 20.57 0.44 45.73 0.65 0.46 1.05 8.03 4.44 11.94 6.71 16.18 8.50
l = 64 21.75 0.57 33.64 0.71 74.85 1.06 1.18 1.77 20.53 11.03 30.12 16.41 41.44 21.10
l = 80 26.40 0.70 41.03 0.88 90.86 1.30 1.46 2.22 25.58 13.90 37.66 20.96 50.96 26.18
TABLE III
MEMORY (KB) FOR THE TWO SCHEMES (TELOSB) (F STANDS FOR FLASH MEMORY).
Polynomial-based approach Proposed approach
dx, dy = 80 dx, dy = 100 dx, dy = 150 n = 1 n = 10 n = 15 n = 20
ROM RAM F ROM RAM F ROM RAM F ROM RAM F ROM RAM F ROM RAM F ROM RAM F
l = 24 21 3 26 21 4 40 26 4 90 21 1 0 21 2 0 21 2 0 21 2 0
l = 32 21 4 39 21 5 60 26 6 135 21 2 0 21 2 0 21 2 0 21 2 0
l = 40 21 4 39 21 5 60 26 6 135 21 2 0 21 2 0 21 2 0 21 3 0
l = 64 21 6 64 21 7 100 26 9 225 21 2 0 22 3 0 22 3 0 22 3 0
l = 80 21 7 77 21 8 120 26 10 270 20 2 0 21 3 0 21 3 0 21 4 0
1 1.5 2 2.5 3 3.5 4
1
2
3
4
5
6
7
Security Level
Energy/Joule
dx,dy = 80
dx,dy = 100
dx,dy = 150
n = 10
n = 15
n = 20
(a) Energy consumption
1 1.5 2 2.5 3 3.5 4
0
5
10
15
20
25
30
Security Level
Delay/seconds
dx,dy = 80
dx,dy = 100
dx,dy = 150
n = 10
n = 15
n = 20
(b) Message delay
1 1.5 2 2.5 3 3.5 4
0.96
0.965
0.97
0.975
0.98
0.985
0.99
0.995
1
1.005
Security Level
DeliveryRatio
dx,dy = 80
dx,dy = 100
dx,dy = 150
n = 10
n = 15
n = 20
(c) Delivery ratio
Fig. 3. Performance comparison of our proposed scheme and bivariate polynomial-based scheme.
message authentication without the weakness of the built-
in threshold of the polynomial-based scheme, we then pro-
pose a hop-by-hop message authentication scheme based on
the SAMA. When applied to WSNs with fixed sink nodes,
we also discussed possible techniques for compromised node
identification. We compared our proposed scheme with the
bivariate polynomial-based scheme through simulations using
ns-2 and TelosB. Both theoretical and simulation results show
that, in comparable scenarios, our proposed scheme is more
efficient than the bivariate polynomial-based scheme in terms
of computational overhead, energy consumption, delivery ratio,
message delay, and memory consumption.
REFERENCES
[1] F. Ye, H. Lou, S. Lu, and L. Zhang, “Statistical en-route filtering of
injected false data in sensor networks,” in IEEE INFOCOM, March 2004.
[2] S. Zhu, S. Setia, S. Jajodia, and P. Ning, “An interleaved hop-by-hop
authentication scheme for filtering false data in sensor networks,” in IEEE
Symposium on Security and Privacy, 2004.
[3] C. Blundo, A. De Santis, A. Herzberg, S. Kutten, U. Vaccaro, and
M. Yung, “Perfectly-secure key distribution for dynamic conferences,”
in Advances in Cryptology - Crypto’92, ser. Lecture Notes in Computer
Science Volume 740, 1992, pp. 471–486.
[4] W. Zhang, N. Subramanian, and G. Wang, “Lightweight and compromise-
resilient message authentication in sensor networks,” in IEEE INFOCOM,
Phoenix, AZ., April 15-17 2008.
[5] A. Perrig, R. Canetti, J. Tygar, and D. Song, “Efficient authentication and
signing of multicast streams over lossy channels,” in IEEE Symposium
on Security and Privacy, May 2000.
[6] M. Albrecht, C. Gentry, S. Halevi, and J. Katz, “Attacking crypto-

10
graphic schemes based on ”perturbation polynomials”,” Cryptology ePrint
Archive, Report 2009/098, 2009, http://eprint.iacr.org/.
[7] R. Rivest, A. Shamir, and L. Adleman, “A method for obtaining digital
signatures and public-key cryptosystems,” Communications. of the Assoc.
of Comp. Mach., vol. 21, no. 2, pp. 120–126, 1978.
[8] T. A. ElGamal, “A public-key cryptosystem and a signature scheme
based on discrete logarithms,” IEEE Transactions on Information Theory,
vol. 31, no. 4, pp. 469–472, 1985.
[9] H. Wang, S. Sheng, C. Tan, and Q. Li, “Comparing symmetric-key and
public-key based security schemes in sensor networks: A case study of
user access control,” in IEEE ICDCS, Beijing, China, 2008, pp. 11–18.
[10] D. Pointcheval and J. Stern, “Security proofs for signature schemes,” in
Advances in Cryptology - EUROCRYPT, ser. Lecture Notes in Computer
Science Volume 1070, 1996, pp. 387–398.
[11] D. Chaum, “Untraceable electronic mail, return addresses, and digital
pseudonyms,” Communications of the ACM, vol. 24, no. 2, pp. 84–88,
February 1981.
[12] ——, “The dinning cryptographer problem: Unconditional sender and
recipient untraceability,” Journal of Cryptology, vol. 1, no. 1, pp. 65–75,
1988.
[13] A. Pfitzmann and M. Hansen, “Anonymity, unlinkability, unobservabil-
ity, pseudonymity, and identity management a proposal for terminol-
ogy,” http://dud.inf.tu-dresden.de/literatur/Anon Terminology v0.31.pdf,
Feb. 15 2008.
[14] A. Pfitzmann and M. Waidner, “Networks without user observability–
design options.” in Advances in Cryptology - EUROCRYPT, ser. Lecture
Notes in Computer Science Volume 219, 1985, pp. 245–253.
[15] M. Reiter and A. Rubin, “Crowds: anonymity for web transaction,” ACM
Transactions on Information and System Security, vol. 1, no. 1, pp. 66–92,
1998.
[16] M. Waidner, “Unconditional sender and recipient untraceability in spite
of active attacks,” in Advances in Cryptology - EUROCRYPT, ser. Lecture
Notes in Computer Science Volume 434, 1989, pp. 302–319.
[17] D. Pointcheval and J. Stern, “Security arguments for digital signatures
and blind signatures,” Journal of Cryptology, vol. 13, no. 3, pp. 361–
396, 2000.
[18] L. Harn and Y. Xu, “Design of generalized ElGamal type digital signature
schemes based on discret logarithm,” Electronics Letters, vol. 30, no. 24,
pp. 2025–2026, 1994.
[19] K. Nyberg and R. A. Rueppel, “Message recovery for signature schemes
based on the discrete logarithm problem,” in Advances in Cryptology
- EUROCRYPT, ser. Lecture Notes in Computer Science Volume 950,
1995, pp. 182–193.
[20] R. Rivest, A. Shamir, and Y. Tauman, “How to leak a secret,” in Advances
in Cryptology–ASIACRYPT, ser. Lecture Notes in Computer Science, vol
2248/2001. Springer Berlin / Heidelberg, 2001.
[21] M. Bellare and P. Rogaway, “Random oracles are practical: A paradigm
for designing efficient protocols,” in CCS’93, 1993, pp. 62–73.
[22] BlueKrypt, “Cryptographic key length recommendation,” http://www.
keylength.com/en/3/.
Jian Li received the BE and MA degrees in elec-
trical engineering both from Tsinghua University in
2005 and 2008, respectively. He is currently a PhD
candidate in electrical and computer engineering at
Michigan State University. His research interests are
in cyber security, network coding and distributed
storage.
Yun Li received the BE from Xidian University in
2005, and Ph.D. degree in electrical and computer
engineering from Michigan State University in May
2010. He joined the Network Operating System Tech-
nology Group (NOSTG) of Cisco System in 2010. Dr.
Li joined the Server & Tools Division of Microsoft in
2012. His current research interests include wireless
sensor networks, network security and cloud based
data services.
Jian Ren received the BS and MS degrees both in
mathematics from Shaanxi Normal University, and
received the Ph.D. degree in EE from Xidian Uni-
versity, China. He is an Associate Professor in the
Department of ECE at Michigan State University.
His current research interests include cryptography,
network security, energy efficient sensor network se-
curity protocol design, privacy-preserving communi-
cations, and cognitive networks. He is a recipient of
the US National Science Foundation Faculty Early
Career Development (CAREER) award in 2009. Dr.
Ren is a senior member of the IEEE.
Jie Wu is the chair and a professor in the Department
of Computer and Information Sciences, Temple Uni-
versity. Prior to joining Temple University, he was
a program director at National Science Foundation.
His research interests include wireless networks and
mobile computing, routing protocols, fault-tolerant
computing, and interconnection networks. He serves
in the editorial board of the IEEE Transactions on
Computers and Journal of Parallel and Distributed
Computing. Dr. Wu is program cochair for IEEE
INFOCOM 2011. He was also general cochair for
IEEE MASS 2006, IEEE IPDPS 2008, and DCOSS 2009. He is serving as
an ACM distinguished speaker and is the chairman of the IEEE Technical
Committee on Distributed Processing (TCDP). Dr. Wu is a Fellow of the IEEE.

Hop by-hop message authentication and source privacy in wire-copy-copy

More Related Content

What's hot (16)

Similar to Hop by-hop message authentication and source privacy in wire-copy-copy (20)

Recently uploaded (20)

Hop by-hop message authentication and source privacy in wire-copy-copy