International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
Determine and Checking Authentication of Adjacent
Nodes in Mobile Ad hoc Networks
1
2
N.R.Anitha
M.Tech Student
Department of CSE
SISTK, Puttur, INDIA
Abstract- A large number of temporary nodes consisting of
set of rules and destination based services require that mobile
nodes learn the nearest places. A process can be easily improper
usage or interrupt by opposition nodes. In being away of
fixed nodes the discover and verifying of nearest places that
have been hardly inquired in the existing system .In this
thesis by introducing a complete distributed answer that is
strong and secret against adjacent nodes and can be
damaged only by an huge number of neighbor nodes . Results
that a set of rules can occur more than 99 percent of the
threats . under the best possible state the original nodes are
to be searched.
Keywords— Temporary nodes; Destination based services;
Interrupt; Threats; Neighbor nodes;
I
INTRODUCTION
Destination based services has become an important in mobile
systems where a wide range of set of rules require knowledge
of the place of nodes participation. Routing in networks, data
collecting in sensor networks among robotic nodes, location
based services for handheld devices and danger warning or
traffic perfect in vehicular networks are all examples of
services are available in neighbor position information.
Node locations is to be set right is an main issue in
mobile networks and it becomes particular challenges in the
presence of nodes aiming at injuring the system. In these
situation we need solutions that let nodes:
1. Location are to be establish based on false location
information in spite of threats.
2. Neighbor positions are to be verified, and which have false
locations are to be identified.
In this thesis the main aspect, here in after referred as
neighbor position verification (NPV for short). In wireless
adhoc networks where a services accessed by sources is not
present, and the location data are to be obtained through node
-to-node communication such a scenario are used in location
aware services. For example, data collecting process, routing
in geographical areas, attracting traffic networks or discarding
it, similarly position counterfeit access unauthorized
information are to be accessed by services dependent location.
In this thesis is to perform in absence of fixed nodes, a fully
divided, easy analyse of NPV procedure enables that each
node to retrieve the place advertised by its nearest nodes.
Therefore NPV protocol that has the following features:
1. It is designed for ad hoc networks and it does not rely on the
presence of a priority based nodes.
2. Action are to be performed by a node it allows all
comparision procedures separately.
ISSN: 2231-5381
E. Murali M.TECH.
AssistantProfessor
Department of CSE
SISTK,Puttur,INDIA
3. It can be executed by any node with out priority knowledge
of the nearest node are to be respond.
4. It is strong against independent and together nodes.
5. It is easy analyse, as it generates low traffic time.
Additionally our NPV scheme is used in security
architectures, including the vehicular networks [1], [2], which
represent a neighbor position verification environment.
II. RELATED WORK
Ad hoc security protocols carries a number of problems
related to NPV, there are no strong solutions, easy analyse to
NPV that can executed with in short time with out any priority
based nodes.
Some of the NPV-related problems are secure
positioning and secure disclosure and then solution address to
NPV.
A. Securely finding own place:
In wireless environments, Global Navigation Satellite
Systems are mainly achieved through self-localization e.g.,
Global Positioning System, whose security can be provided by
defense mechanism [3]. Alternate infrastructure of terrestrial
are to be used [4], [5], along with distribution with nonhonest
beacons [6]. some of the safely resolve their own place and
reference time.
B. Secure neighbor detection:
It deals with the establishment of nodes with which a
link can be found with in a given distance [7]. Secure neighbor
detection is only a solution toward the step we are after : an
nearest node can be simply secure discover as neighbor with
in range of SND, but it could still its place with in same
range. In different words, SND is a set of the NPV problem
,since a node can be accessed whether another node is a an
closest of actual one but it place are not to be verified. SND is
mostly used to counting the wormhole attacks [8], [9],[10];
some of the solutions to proposed system related to SND
problem [11], SND as set of rules to prove based on secure
solutions can be in [12], [13].
C. Neighbor place verification:
In the ad hoc and sensor networks; existing NPV
schemes often rely on fixed[14], [15] or mobile[16] fixed
nodes, are to assume always available of places are to be
verified declared by third parties. In temporary locations,
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
either neighbor nodes or infrastructure can be faith unrealistic.
Thus a set of rules does not consist of fixed neighbors.
[16]; also, some of the techniques for precise ToF-based RF
ranging have been developed.
In [17], an NPV consist of set of rules are to be purposed that
first nodes distance are to be calculated, and then which nodes
consist pair of nodes are to be encircled act as verifiers of the
position of their pairs, This information does not used in
priority based nodes, but it is designed for sensor networks are
to be constant and it consists of of multiround computation
lengthy involves many nodes that on a same nearest
comparison . Futher, the resilience of the set of rules in [17],
the information are to be hacked is not explained. The
information in [18], suits constant sensor networks too, and it
consists of many nodes information are to be exchange by a
node signal to be emitted whose place has to be identified.
Nodes carry a different identity and can secure information of
other nodes through public key cryptography [23]. We assume
each node X owns a private key, kX, and a public key, KX ,as
well as set of use one-time keys {k0X; KX0}, as proposed in
emerging architectures for authentication and privacy
enhancing communication [2], [21]. Node X can encrypt and
decrypt data with its keys and public keys of other nodes; It
can produce digital signatures (SigX) with its private key. Any
node, a secure communication architectures [2], [22] , can be
binding between X and KX.
Our NPV solution allows any node to calculate the
position of all the of its neighbors through a message one-time
are to be exchange, which makes is used in wireless and
temporary networks. Addition to NPV scheme is strong
against many attackers hack the information. Some of the
differences can be in the work and [19].
In [20], the authors are identify NPV consist of set of rules
that allows to identify the correct position of neighbor nodes
through some calculations only. This performs checks whether
correct position identified by one neighbor movement may be
possible. This approach in [20], a node several data are to be
collected before take a decision to be taken, based on
situations the solution are to be made where the information
consist of place are to be identified with in a short period of
time. Moreover, the protocol by announcing unknown
locations, that follow a realistic pattern mobility. Among all
nodes NPV protocol is:
1. Any node can be executed reactively at any instant with a
short span period of time.
2. Mobility patterns announces by opposite nodes consist of
strong fake information over time.
Our protocol is to provide a lightweight solution, fully
distributed to the NPV problem that does not require any
structure or a fixed priority based nodes and it is strong
against several attacks, including all nodes are together.
Indeed, non-RF communication, e.g., infrared or ultrasound, is
used in mobile networks, where non-line-of-sight conditions
are frequent and distance can be calculated between deviceto- device in terms of tens or hundreds of meters. An version
of early of this work, some of the verification tests are used to
detect adversaries are to be sketched in NPV protocol.
III.
SYSTEM MODEL
A mobile network and define as a node of communication
neighbors of all other nodes that reach directly its
transmissions [7].Each node its own location with some
maximum error €p, and its share a reference of common time
with the nodes of other: both requirements can be used by
communication nodes with GPS receivers. In addition, nodes
perform Time-of-Flight-based RF ranging with a maximum
error equal to €r. This is a reasonable assumption, it
requirements modifications to off-the-shelf radio interfaces
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Nodes are correct with the NPV protocol, and adversarial if
they delete from it. As secure essentially external information,
we focus on the more powerful internal ones, i.e., nodes can
possess to participate in the NPV and try to advertising own
locations or misleading information. Internal adversaries
cannot messages of other nodes they do not have keys. Thus
attacks occurred the cryptosystem are not considered, as
correct implementation of cryptographic primitives makes
them infeasible.
We classify adversaries into: knowledgeable, if at
each time instant positions are to be know and temporary
identities of all their neighbors, and unknowledgeable,
otherwise; independent, if they act individual, and colluding, if
they actions are to be coordinated.
IV.
NPV OVERVIEW
The presented a distributed solution for NPV, which
allows any node in wireless ad hoc networks is to verify the
location of its communication neighbor without relying on
priority based nodes. The analysis shows that a set of rules
protocol is very strong to attacks by independent as well as
together nodes, even when they have perfect knowledge of the
neighbor of the verifier. Simulation results confirm that the
solutions is effective in identifying nodes announcing false
positions. Only an overwhelming presence of colluding nodes
in the neighbor of the verifier, or the unlikely presence of
distributed network topologies, can degrade the effectiveness
of our NPV.
Future work will aimed at integrating the set of rules, as well
as useful in presence of applications that location of the
neighbors.
In methodology, a complete distributed cooperative
scheme for NPV, which enables a source node, to discover
and verify the location of its neighbors. For clarity, here it
describes the principles of route discovery and location
verification process.
Figure 1: Neighbor discovery in adversarial environment
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
A source node, S can initiate the protocol at any time
instant, by triggering the 4- step message exchange process
[POLL, REPLY, REVEAL and REPORT], after completion
of message exchange process, source node S has derives
distance range of neighbor nodes to find the shortest path to
reach destination, after discovery of route S runs verification
tests of several places in order to classify each neighbor node
as either VERIFIED, FAULTY, UNVERFIABLE.
Clearly, the verification tests aim at adversaries
announcing fake positions that are already verified and the
correct nodes whose positions are deemed faulty as well as at
minimizes the number of unverifiable nodes. we remark that
our NPV scheme does not target the creation of a consistent
“map” of neighbor node relations through out an network:
rather, it allows the verifier to classify its neighbors.
V.
NPV PROTOCOL
generated MAC address is used here. A public key K’S carries
chosen from a pool of onetime use keys of S’.
b) REPLY message:
A communication neighbor X receiving the POLL message
will broadcast REPLY message with a time interval MAC
address are generated. This also internally saves the
transmission time. It contains some encrypted message with S
public key (K’S). This message is called as commitment of
XCX.
c)
REVEAL message:
The REVEAL message is broadcasted using verifier’s MAC
address. It contains A map MS, as a proof that S is the verifier
of the original POLL and the identity of verifier ,i.e., it
certifies public key and signature.
d) REPORT message:
NPV protocol is used to message exchange between the
verifier and its neighbors communication, followed it
describes at tests run by the verifier. In NPV protocol it
consists of steps mentioned below:
1.Protocol Message Exchange
2.Position Verification
The REPORT carries X’s position, the time of transmission
X’s REPLY, and the list of pairs of times and temporary
identifiers refers to REPLY broadcasts X received. The
identifiers are obtained from the map MS included in the
REVEAL message. Also, X has its own value by including in
the message its digital signature and it certifies public key.
B. Position Verification:
A. Protocol Message Exchange:
In Protocol Message Exchange, follow the steps
mentioned below:
1. POLL message
2. REPLY message
The node location verification is not suitable for
dynamic environment, since wireless nodes are in change in
nature, so each and every schedule the wireless nodes
undergoes location verification test, thus results in delay time
of delivery packet ratio.
VI PERFORMANCE EVALUATION
3. REVEAL message
We evaluate the presentation of our NPV protocol in a
vehicular situation. Results obtained in a ordinary scenario are
available as supplemental material, which can be found on the
Computer
Society
Digital
Library
at
http://
doi.ieeecomputersociety.org/10.1109/TMC. 2011.258.
4. REPORT message
We focus on well-informed adversary whose goal is
to make the verifier believe their fake positions, and we
describe the best attack approach they can adopt in Section A.
Such a strategy, which depends on the area of the adversary
and builds on a combination of the attacks described and will
be assumed while deriving the results in section B.
Figure 2: Message Exchange Process
a) POLL message:
A verifier S initiates this message. This message is
unidentified. The verifier of identity is kept hidden. Software
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The results, which therefore imply a worst case study
of the planned NPV, are shown in terms of the chance that the
tests return false positives and false negatives as well as of
the probability that a (correct or adversary) node is tagged
as unverifiable. In addition, we plot the average differentiation
between the true position of a successful adversary and the
fake position it advertises, as well as the overhead introduced
by our NPV scheme. The outcome on attacks aimed at
discredit the position of other nodes are absent, since they are
very close to those we present later in this part.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
A. Adversaries Attack Strategy:
The opponent choice on the kind of attack to open is driven by
the tradeoff among the probability of success and the freedom
of choice on its fake position. The basic attack allows the
adversary to choose any false position, but it requires a high
percentage of colluders in the neighborhood in order to be
successful. The colluding attackers agree not only on the
position of the verifier (either guessed or multilaterated), but
also pick a non-collinear common neighbor, X, that they share
with S: each colluder then computes the hyperbola with foci S,
X, and passing through its own real position, and announces a
fake location on such a curve. The hyperbola-based attack
imply less freedom of choice but has higher probability of
success and combining a hyperbola-based attack with a
REPLY- disregard attack yields no chance of success. The
collinear attack pins the opponent into a particular angle with
the verifier, and strictly bounds its distance from the verifier
itself. The presence of two or more correct common
neighbors, which can be used to perform the cross-checks in
the Cross-Symmetry Test, is a condition that foils all the
attack strategies introduced so far. There exists however a last
type of attack, which we name collinear attack, However, if
the network topology features a enough quantity of collinear
nodes, this attack has the highest achievement probability.
The best plan that an opponent can adopt depends on
its neighborhood. First, if it collude with other adversary
outnumbering the noncolluding neighbors, a basic attack is
launched. Otherwise, if the ratio between colluding and
noncolluding neighbors is not greater than (but close enough
to) 1, a hyperbola-based attack is attempt. As a third option, if
noncolluding neighbors greatly outnumber the colluding ones,
but some of the former are collinear with the verifier and
among themselves, the adversary launch a collinear attack.
During it, the adversary can have the noncolluding, collinear
neighbors thrown out of the cross-checks in the Cross Symmetry Test. If none of the above conditions are met, the
adversary picks a hyperbola based attack, i.e., the one with the
highest chances of achievement in absence of noncolluding,
Figure 3: Road layout of the 7x 3 km2 vehicular scenario.
collinear neighbors. Also, an opponent always runs a REPLYdisregard on one noncolluding fellow citizen, avoiding a
variance with it. Recall that disregard just one REPLY does
not trigger the Multilateration Test on the opposition.
B. Results:
We engaged
group traces in place of means of
transportation transfer over a real-world road topology. More
precisely, we considered car movements within a 20 km2
portion of the Karlsruhe urban area depicted in Fig. 8,
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extracting 3 hours of vehicular mobility that reproduce mild to
heavy traffic density conditions. These artificial traces were
generated using the IDM-LC model of the VanetMobiSim
simulator, which takes into explanation car-to-car connections,
traffic lights, stop signs, and lane changes, and has been
proven to realistically copy vehicular group patter in urban
scenario [24].
In our simulation, we set Tmax =200 ms, Tjitter = 50
ms, ∆= 1 ms and assume that CSMA/CA is used to contact the
wireless medium, hence messages can be lost due to
collisions. Unless otherwise specified, we fix the nearness
range, R, which is equal to the most nominal show range, to
250 m (resulting in an average region size of 73.4 nodes),
while €r = 6:8 m, €p = 10 m, and the acceptance value €m = 5
m(roughly corresponding to the case of two vehicles moving
at 50 km/h in opposite directions).
To evaluate the presentation of our NPV, at every
simulation second we at random select 1 percent of the nodes
as verifiers. Then, for each verifier, we compare the outcome
of the verification tests with the actual nature of the neighbors.
We consider colluding adversary acting in groups, referred to
as clusters. Note that a colluding cluster size equal to 1
corresponds to independent attacks. Also, adversaries are
knowledgeable, i.e., they completely know the self and place
of all colluding and noncolluding neighbors, and always adopt
the best attack strategy as described in Section A. In the
following, unless otherwise particular, opponent amount to 5
percent of the overall nodes and are divided into clusters of
five colluders each.
In the celebrity of the plots, C stands for accurate
node (e.g.,the label “Cfaulty” refers to the probability of false
positives),while M/Bas, M/Hyp, and M/Col stand for
adversaries introduction, respectively, the basic, hyperbolabased and collinear attack (e.g., the label “M/Bas verified”
refers to the probability of false negatives due to basic
attacks). We first examine the NPV protocol performance for
different values of colluding cluster sizes and R = 250 m
(Figs. 4a and 4b).
The false negative/positive probability in Fig. 4a
clearly shows that 1) chance of wrong classification reaches
0.01 only for a very large adversarial cluster size, namely 10,
2) the hyperbola-based and the collinear attacks are the most
threatening and 3) an attack by the colluders is most effective
in passing themselves off as verified when there are at least
three of them. The cluster size also affects the colluders ability
to disrupt the positioning of correct nodes, which exhibit as
high as a 0.4 percent chance to be tagged as faulty.
Equally, as shown in Fig. 4b, the group amount does
not cause more correct nodes to be unverifiable, since the
main reason for correct nodes to be tag as unverifiable is the
lack of noncollinear neighbors that can prove them. The
chance for an adversary to be unverifiable increases with the
cluster size, even though it is significant only in case of
collinear attacks. This is in agreement with the fact that the
outcome of the collinear attack is the avoidance of a
considerable number of cross-checks between the opponent
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
and correct nodes, thus likely leading the adversary to be tag
as unverifiable.
The region size proves to play an significant role, as
evident in Figs. 4c and 4d where we believe a 5-colluder
cluster and vary the transmission range. A small R (hence few
neighbors) affects the NPV means to properly tag a node.
widen the transmission range with a fixed colluding bunch
size extensively favors the verifier, allow it to reach a certain
and exact decision on either correct or opponent nodes: the
larger the R, the higher the number of cross-checks involving
correct nodes in the Cross -Symmetry Test. We note that, for
show ranges larger than 300 m, we obtain false
positive/negative probability that are smaller than 0.001.
Below 150-m ranges (identical to an standard region size of 12
nodes), such chance are still 0.01.
unverifiable tag being slapped onto more correct nodes. A
final observation can be made looking at the false
positive/negative probability as the positioning error varies
(Figs. 5c and 5d). Fascinatingly, for any positioning error
different from 0, the metrics are only slightly affected.
Finally, we further increase the level of feature of our
analysis and study the advantage obtained by adversaries that
perform a successful attack against the NPV protocol. Such an
adversarial gain is expressed in terms of spatial dislocation,
i.e., difference of position between the real and fraudulently
advertised locations of the successful attacker: clearly, a larger
displacement range implies a superior freedom of group,
which, in turn, enables potentially more dangerous actions
against the system. Attacks where the adversaries aim at
disrupting the verification of correct node positions and
verifier and validate their own fake position. The results in
Fig. 6a are broken down based on the type of attack launched
by the successful opponent, and are limited to the impact of
the show range, since the other parameter did not show major
influence on the displacement of successful attackers.
Figure 4: Probability that a neighbor is tagged incorrectly or as
R(c,d).C:correct; M/Bas, M/Hyp, and M/Col: adversaries
combined with the REPLY-disregard attack.
unverifiable,versus the colluder cluster size (a,b), and versus
launching the basic,hyperbola-based and collinear attack, each
Figure 5: Probability that a neighbor is tagged incorrectly or
Position error (c,d). C:correct; M/Bas, M/Hyp, and M/Col:
Collinear attack, each combined with the REPLY-disregard
Beside the impact of the group size and of the
message range, it is important to understand the effect of the
percentage of adversary in the vehicular network. Thus, in Fig.
5a we fix R to 250 m and the cluster size to 5, and we show
the robustness of our NPV to the density of adversaries: the
probability that adversaries are verified increases ever so
slightly with their density. The highest effect is on the
probability of correct nodes being tagged as faulty, which
however reaches its highest value (0.1) only for 30 percent of
adversaries in the network. A further effect of the growing
presence of adversaries, as shown in Fig. 5b, is the
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as unverifiable, versus the ratio of adversaries (a,b), and
adversaries launching the basic, hyperbola-based, and
attack.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
VII. CONCLUSION
Techniques for finding neighbors efficiently in a non priority
based nodes are identified. The proposed techniques will
eventually provided authentication from attacked nodes. A set
of rules is strong to adversarial attacks. This protocol will also
update the location of the nodes in an active environment. The
performance of the proposed scheme will be effective in
identifying nodes announcing false locations. Future work will
aim at integrating the NPV protocol in a set of rules, as well as
at extending it to a information, useful in presence of
implementation that need each node to continuous verify the
location of its neighbors.
Figure 6: Displacement gain of adversaries running a
successful attack against the NPV (a) and traffic load induced
by one instance of the Protocol (b).
REFERENCES
[1]
We can observe that successful collinear attacks yield
small advantage for adversaries, who are forced to announce
positions quite close to their real locations. Moreover, we
recall that these attacks confine adversaries to advertise fake
positions along a accurate axis, thus further limiting their
choice of movement. We can end that collinear attacks,
typically those with the highest chances of success as
previously discussed, are also those resulting in the smallest
gain for the adversary. Equally, basic attacks allow the largest
average displacements, but we showed that they have
extremely low success chance. The hyperbola-based attacks
appear then to be the most dangerous ones, if the displacement
gain is taken into consideration. However, such a gain
becomes important only for large communication ranges, in
presence of which we already observed that the actual success
possibility of the attacks becomes insignificant.
Finally, we comment on the overhead introduced by
our scheme. The NPV protocol generates at most 2n+2
messages for one execution initiate by a verifier with n
communication neighbors. Also, NPV messages are relatively
small in size: with SHA-1 hashing and ECDSA-160
encryption [25], the length of signature is 21 bytes (with
coordinates compression). Assuming that messages contain
headers with 4-byte source and destination identifiers and 1byte message type field, POLL, REPLY, and REVEAL are 26,
71, and 67 bytes in size, respectively. The REPORT length
depends on the quantity of common neighbor data it carries,
amounting to 4 bytes per shared neighbor: information on
more than 360 neighbors can thus fit in a single IP packet.
Fig. 6b describe the traffic induced on the network by
one instance of the NPV protocol. The plot only accounts for
transmission range variations since, once more, the other
parameters do not have an impact on the overhead. We can
observe that security comes at a cost, since the traffic load of
the NPV protocol is higher than that of a basic nonsecure
neighbor position discovery, consisting of only one poll and
associated position replies from neighbors. More accurately,
the NPV protocol overhead is equal to that of the nonsecure
discovery for smaller transmission ranges, while the variation
tends to increase for better ranges. However, the cost of the
NPV protocol is reasonable in complete terms, since one run
requires just a few tens of kbytes to be substitute among
nodes, even in presence of dense networks and large
communication ranges.
ISSN: 2231-5381
[2]
1609.2-2006: IEEE Trial-Use Standard for Wireless
Access in
Vehicular Environments - Security Services for Applications and
Management Messages, IEEE, 2006.
P. Papadimitratos, L. Buttyan, T. Holczer, E. Schoch, J. Freudiger, M.
Raya, Z. Ma, F. Kargl, A. Kung, and J.-P. Hubaux, “Secure Vehicular
Communications: Design and Architecture,” IEEE Comm. Magazine,
vol. 46, no. 11, pp. 100-109, Nov. 2008.
[3] P. Papadimitratos and A. Jovanovic,“GNSS-Based Positioning: Attacks
and Countermeasures,” Proc. IEEE Military Comm. Conf. (MILCOM),
Nov. 2008.
[4]
L. Lazos and R. Poovendran, “HiRLoc: High-Resolution Robust
Localization for Wireless Sensor Networks,” IEEE J. Selected Areas in
Comm., vol. 24, no. 2, pp. 233-246, Feb. 2006.
[5] R. Poovendran and L. Lazos, “A Graph Theoretic Framework for
Preventing the Wormhole Attack,” Wireless Networks, vol. 13, pp. 2759, 2007.
[6] S. Zhong, M. Jadliwala, S. Upadhyaya, and C. Qiao, “Towards a Theory
of Robust Localization against Malicious Beacon Nodes,” Proc. IEEE
INFOCOM, Apr. 2008.
[7]
P.Papadimitratos,M. Poturalski, P. Schaller, P. Lafourcade, D. Basin, S.
Capkun,
and
J.-P.
Hubaux,
“Secure
Neighborhood
Discovery:AFundamental Element for Mobile Ad Hoc Networks,” IEEE
Comm. Magazine, vol. 46, no. 2, pp. 132-139, Feb. 2008.
[8]
Y.-C. Hu, A. Perrig, and D.B. Johnson, “Packet Leashes: A Defense
against Wormhole Attacks in Wireless Networks,” Proc. IEEE
INFOCOM, Apr. 2003.
[9]
J.Eriksson, S. Krishnamurthy, and M. Faloutsos,“TrueLink: A Practical
Countermeasure to the Wormhole Attack in Wireless Networks,” Proc.
IEEE 14th Int’l Conf. Network Protocols (ICNP), Nov. 2006.
[10] R.Maheshwari, J.Gao, and S. Das,“Detecting
Wormhole Attacks
in Wireless Networks Using Connectivity Information,” Proc. IEEE
INFOCOM, Apr. 2007.
[11] R. Shokri, M. Poturalski, G. Ravot, P. Papadimitratos,
and J.-P
Hubaux, “A Practical Secure Neighbor Verification Protocol for
Wireless Sensor Networks,”Proc. Second ACM Conf. Wireless
Network Security (WiSec), Mar. 2009.
[12] M.Poturalski, P.Papadimitratos, and J.-P.Hubaux, “Secure Neighbor
Discovery in Wireless Networks: Wireless Networks,” IEEE J.
Selected Areas in Comm., vol. 24, no. 2, pp. 221-232, Feb. 2006.
[13] M. Poturalksi, P. Papadimitratos, and J.-P. Hubaux,
“Towards Provable Secure Neighbor Discovery in Wireless
Networks,” Proc .Workshop Formal Methods. in Security Eng., Oct.
2008.
[14] E. Ekici, S. Vural, J. McNair, and D.Al-Abri, “Secure Probabilistic
Location Verification in
Randomly Deployed Wireless Sensor
Networks,” Elsevier Ad Hoc Networks, vol. 6, no. 2, pp. 195-209, 2008.
[15] J. Chiang,
J. Haas, and
Y. Hu, “Secure and Precise Location
Verification
Using
Distance
Bounding and Simultaneous
Multilateration,” Proc. Second ACM Conf. Wireless Network Security
(WiSec), Mar. 2009.
[16] S. Capkun, K. Rasmussen, M. Cagalj, and M.
Srivastava, “Secure
Location Verification with Hidden and Mobile Base Stations,” IEEE
Trans. Mobile Computing, vol. 7, no. 4, pp. 470-483, Apr. 2008.
http://www.ijettjournal.org
Page 177
International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 4 – Aug 2014
[17] S.Capkun and J.-P. Hubaux, “Secure Positioning in Wireless Networks,”
IEEE J. Selected Areas in Comm., vol. 24, no. 2, pp. 221-232, Feb.
2006.
[18] A. Vora and M. Nesterenko, “Secure Location
Verification Using
Radio Broadcast,” IEEE Trans. Dependable and Secure Computing, vol.
3, no. 4, pp. 377-385, Oct.-Dec. 2006.
[19] J. Hwang, T. He, and Y. Kim, “Detecting Phantom
Nodes in Wireless
Sensor Networks,” Proc. IEEE INFOCOM, May 2007.
[20] T. Leinmu¨ ller, C. Maiho¨ fer, E. Schoch, and F. Kargl, “Improved
Security in Geographic Ad Hoc Routing through Autonomous Position
Verification,” Proc. ACM Third Int’l Workshop Vehicular Ad Hoc
Networks (VANET), Sept. 2006.
[21] PRECIOSA: Privacy Enabled Capability in Co-Operative Systems and
Safety Applications, http://www.preciosa-project.org, 2012.
[22] G. Calandriello, P. Papadimitratos, A. Lioy, and J.-P. Hubaux, “On the
Performance of Secure Vehicular Communication Systems,” IEEE
Trans. Dependable and Secure Computing, vol. 8, no. 6, pp. 898- 912,
Nov./Dec. 2011.
[23]IEEE Standard Specifications for Public-Key Cryptography Amendment
1: Additional Techniques, IEEE 1363a 2004, 2004.
[24] J. Ha¨rri, M. Fiore, F. Filali, and C. Bonnet, “Vehicular Mobility
Simulation with VanetMobiSim,” Trans. Soc. Modeling & Simulation,
2009.
[25] IEEE Standard Specifications for Public-Key Cryptography –
Amendment 1: Additional Techniques, IEEE 1363a 2004, 2004.
ISSN: 2231-5381
http://www.ijettjournal.org
Page 178