Final Year IEEE Project Titles 2015

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CODE PROJECT TITLE DESCRIPTION REFERENCE
TTA-DN-
C1501
Delay Analysis of
Multichannel
Opportunistic Spectrum
Access MAC Protocols
We provide a comprehensive delay and
queuing analysis for two baseline
medium access control protocols for multi-user
cognitive radio networks with homogeneous
users and channels and investigate the impact
of different network parameters on the system
performance. In addition to an accurate
Markov chain, which follows the queue status
of all users, several lower complexity queuing
theory approximations are provided. Accuracy
and performance of the proposed analytical
approximations are verified with extensive
simulations. It is observed that using an Aloha-
type access to the control channel, a
buffering MAC protocol, where in case of
interruption the CR user waits for the primary
user to vacate the channel before resuming the
transmission, outperforms a switching MAC
protocol, where the CR user vacates the
channel in case of appearance of primary users
and then compete again to gain access to a new
channel. The reason is that
the delay bottleneck for both protocols is the
time required to successfully access the control
channel, which occurs more frequently for the
switching MAC protocol. It is thus shown that
a clustering approach, where users are divided
into clusters with a separate control channel
per cluster, can significantly improve the
performance by reducing the competitions over
control channel.
IEEE 2015
TTA-DN-
C1502
LEISURE A Framework
for Load-Balanced
Network - Wide Traffic
Measurement
Network-wide traffic measurement is of
interest to network operators to uncover
global network behavior for the management
tasks of traffic accounting, debugging or
troubleshooting, security, and
traffic engineering. Increasingly,
sophisticated network measurement tasks such
as anomaly detection and security forensic
analysis are requiring in-depth fine-grained
IEEE 2015

flow-level measurements. However,
performing in-depth per-
flow measurements (e.g., detailed payload
analysis) is often an expensive process. Given
the fast-changing Internet traffic landscape and
large traffic volume, a single monitor is not
capable of accomplishing
the measurement tasks for all applications of
interest due to its resource constraint.
Moreover, uncovering global network behavior
requires network-wide traffic measurements at
multiple monitors across
the network since traffic measured at any
single monitor only provides a partial view and
may not be sufficient or accurate. These
factors call for coordinated measurements
among multiple distributed monitors. In this
paper, we present a centralized
optimization framework, LEISURE (Load-
Equalized measurement), for load-
balancing network measurement workloads
across distributed monitors. Specifically, we
consider various load-balancing problems
under different objectives and study their
extensions to support different deployment
scenarios. We evaluate LEISURE via detailed
simulations on Abilene and
GEANT network traces to show
that LEISURE can achieve much better load-
balanced performance (e.g., 4.75X smaller
peak workload and 70X smaller variance in
workloads) across all coordinated monitors in
comparison to naive solution (uniform
assignment) to accomplish network-
wide traffic measurement tasks.
TTA-DN-
C1503
Authenticated Key
Exchange Protocols for
Parallel Network File
Systems
We study the problem of key establishment for
secure many-to-many communications. The
problem is inspired by the proliferation of
large-scale
distributed file systems supporting parallel acc
ess to multiple storage devices. Our work
focuses on the current Internet standard for
such file systems, i.e., parallel
Network File System (pNFS), which makes
use of Kerberos to
IEEE 2015

establish parallel session keys between clients
and storage devices. Our review of the existing
Kerberos-based protocol shows that it has a
number of limitations: (i) a metadata server
facilitating key exchange between the clients
and the storage devices has heavy workload
that restricts the scalability of the protocol; (ii)
the protocol does not provide forward secrecy;
(iii) the metadata server generates itself all the
session keys that are used between the clients
and storage devices, and this inherently leads
to key escrow. In this paper, we propose a
variety
of authenticated key exchange protocols that
are designed to address the above issues. We
show that our protocols are capable of
reducing up to approximately 54% of the
workload of the metadata server and
concurrently supporting forward secrecy and
escrow-freeness. All this requires only a small
fraction of increased computation overhead at
the client.
TTA-DN-
C1504
Diversifying Web
Service
Recommendation
Results via Exploring
Service Usage History
The last decade has witnessed a tremendous
growth of Web services as a major technology
for sharing data, computing resources, and
programs on the Web. With the increasing
adoption and presence of Web services, design
of novel approaches for
effective Web service recommendation to
satisfy users’ potential requirements has
become of paramount importance.
Existing Web service
commendation approaches mainly focus on
predicting missing QoS values of Web service
candidates which are interesting to a user using
collaborative filtering approach, content-based
approach, or their hybrid.
These recommendation approaches assume
that recommended Web services are
independent to each other, which sometimes
may not be true. As a result, many similar or
redundant Web services may exist in
a recommendation list. In this paper, we
propose a novel Web
service recommendation approach
IEEE 2015

incorporating a user’s potential QoS
preferences and diversity feature of user
interests on Web services. User’s interests and
QoS preferences on Web services are first
mined
by exploring the Web service usage history.
Then we compute scores of Web service
candidates by measuring their relevance with
historical and potential user interests, and their
QoS utility. We also construct
a Web service graph based on the functional
similarity between Web services. Finally, we
present an innovative diversity-
aware Web service ranking algorithm to rank
the Web service candidates based on their
scores, and diversity degrees derived from
the Web service graph. Extensive experiments
are conducted based on a real
world Web service dataset, indicating that our
proposed Web service recommendation approa
ch significantly improves the quality of their
commendation results compared with existing
methods.
TTA-DN-
C1505
Virtual Servers Co-
Migration for Mobile
Accesses Online vs.
Offline
In this paper, we study the problem of co-
migrating a set of service replicas residing on
one or more redundant virtual servers in clouds
in order to satisfy a sequence of mobile batch-
request demands in a cost effective way. With
such a migration, we can not only reduce the
service access latency for end users but also
minimize the network costs for service
providers. The co-migration can be achieved at
the cost of bulk-data transfer and increases the
overall monetary costs for the service
providers. To gain the benefits of
service migration while minimizing the overall
costs, we propose a co-migration algorithm
Migk for multiple servers, each hosting a
service replica. Migk is a randomized
algorithm with a competitive cost of O(γ log
n/min{1/k, μ/λ+μ}) to migrate κ services in a
static n-node network where γ is the maximal
ratio of the migration costs between any pair of
neighbor nodes in the network, and where λ
and μ represent the maximum wired
IEEE 2015

transmission cost and the wireless link cost
respectively. For comparison, we also study
this problem in its static off-line form by
proposing a parallel dynamic programming
(hereafter DP) based algorithm that integrates
the branch & bound strategy with sampling
techniques in order to approximate the optimal
DP results. We validate the advantage of the
proposed algorithms via extensive simulation
studies using various requests patterns and
cloud network topologies. Our simulation
results show that the proposed algorithms can
effectively adapt to mobile access patterns to
satisfy the service request sequences in a cost-
effective way.
TTA-DN-
C1506
Anomaly-Based
Network Intrusion
Detection System
We present POSEIDON, a new anomaly-
based network intrusion detection system.
POSEIDON is payload-based, and has a two-
tier architecture: the first stage consists of a
self-organizing map, while the second one is a
modified PAYL system. Our benchmarks on
the 1999 DARPA data set show a
higher detection rate and lower number of false
positives than PAYL and PHAD
IEEE 2015
TTA-DN-
C1507
CEDAR A Low-Latency
and Distributed
Strategy for Packet
Recovery in Wireless
Networks
Underlying link-layer protocols of well-
established wireless networks that use the
conventional “store-and-forward” design
paradigm cannot provide highly sustainable
reliability and stability in wireless
communication, which introduce significant
barriers and setbacks in scalability and
deployments of wireless networks. In this
paper, we propose a Code
Embedded Distributed Adaptive and Reliable
(CEDAR) link-layer framework that
targets low latency and balancing en/decoding
load among nodes. CEDAR is the first
comprehensive theoretical framework for
analyzing and designing distributed and
adaptive error recovery for wireless networks.
It employs a theoretically sound framework for
embedding channel codes in each packet and
performs the error correcting process in
selected intermediate nodes in a packet's route.
To identify the intermediate nodes for the
IEEE 2015

decoding, we mathematically calculate the
average packet delay and formalize the
problem as a nonlinear integer programming
problem. By minimizing the delays, we derive
three propositions that: 1) can identify the
intermediate nodes that minimize the
propagation and transmission delay of
a packet; and 2) and 3) can identify the
intermediate nodes that simultaneously
minimize the queuing delay and maximize the
fairness of en/decoding load of all the nodes.
Guided by the propositions, we then propose a
scalable and distributed scheme in CEDAR to
choose the intermediate en/decoding nodes in a
route to achieve its objective. The results from
real-world test bed “NESTbed” and simulation
with MATLAB prove that CEDAR is superior
to schemes using hop-by-hop decoding and
destination decoding not only in packet delay
and throughput but also in energy-consumption
and load distribution balance.
TTA-DN-
C1508
CoCoWa A
Collaborative Contact-
Based Watchdog for
Detecting Selfish Nodes
Mobile ad-hoc networks (MANETs) assume
that mobile nodes voluntary cooperate in order
to work properly. This cooperation is a cost-
intensive activity and some nodes can refuse to
cooperate, leading to a selfish node behavior.
Thus, the overall network performance could
be seriously affected. The use of watchdogs is
a well-known mechanism
to detect selfish nodes. However, the detection
process performed by watchdogs can fail,
generating false positives and false negatives
that can induce to wrong operations.
Moreover, relying on local watchdogs alone
can lead to poor performance when
detecting selfish nodes, in term of precision
and speed. This is specially important on
networks with sporadic contacts, such as delay
tolerant networks (DTNs), where
sometimes watchdogs lack of enough time or
information to detect the selfish nodes. Thus,
we propose collaborative contact-based
watchdog (CoCoWa) as
a collaborative approach based on the diffusion
of local selfish nodes awareness when
IEEE 2015

a contact occurs, so that information
about selfish nodes is quickly propagated. As
shown in the paper, this collaborative approach
reduces the time and increases the precision
when detecting selfish nodes.
TTA-DN-
C1509
Distributed
Opportunistic
Scheduling for
EnergyHarvesting
Based Wireless
Networks A Two-
StageProbing Approach
This paper considers a heterogeneous ad
hoc network with multiple transmitter-receiver
pairs, in which all transmitters are capable of
harvesting renewable energy from the
environment and compete for one shared
channel by random access. In particular, we
focus on two different scenarios: the constant
energy harvesting (EH) rate model where the
EH rate remains constant within the time of
interest and the i.i.d. EH rate model where the
EH rates are independent and
identically distributed across different
contention slots. To quantify the roles of both
the energy state information (ESI) and the
channel state information (CSI),
a distributed opportunistic scheduling (DOS)
framework with two-stage probing and save-
then-transmit energy utilization is proposed.
Then, the optimal throughput and the optimal
scheduling strategy are obtained via one-
dimension search, i.e., an iterative algorithm
consisting of the following two steps in each
iteration: First, assuming that the stored energy
level at each transmitter is stationary with a
given distribution, the expected throughput
maximization problem is formulated as an
optimal stopping problem, whose solution is
proven to exist and then derived for both
models; second, for a fixed stopping rule, the
energy level at each transmitter is shown to be
stationary and an efficient iterative algorithm
is proposed to compute its steady-state
distribution. Finally, we validate our analysis
by numerical results and quantify the
throughput gain compared with the best-effort
delivery scheme.
IEEE 2015
TTA-DN-
C1510
Enabling Efficient Multi-
Keyword Ranked
Search Over Encrypted
Mobile Cloud Data
In mobile cloud computing, a fundamental
application is to outsource the mobile data to
external cloud servers for scalable data storage.
The outsourced data, however, need to
IEEE 2015

Through Blind Storage be encrypted due to the privacy and
confidentiality concerns of their owner. This
results in the distinguished difficulties on the
accurate search over
the encrypted mobile cloud data. To tackle this
issue, in this paper, we develop the searchable
encryption for multi-
keyword ranked search over the storage data.
Specifically, by considering the large number
of outsourced documents (data) in the cloud,
we utilize the relevance score and k-nearest
neighbor techniques to develop
an efficient multi-keyword search scheme that
can return the ranked search results based on
the accuracy. Within this framework, we
leverage an efficient index to further improve
the search efficiency, and adopt
the blind storage system to conceal access
pattern of the search user. Security analysis
demonstrates that our scheme can achieve
confidentiality of documents and index,
trapdoor privacy, trapdoor unlinkability, and
concealing access pattern of the search user.
Finally, using extensive simulations, we show
that our proposal can achieve much improved
efficiency in terms of search functionality
and search time compared with the existing
proposals.
TTA-DN-
C1511
Energy-Efficient Group
Key Agreement for
Wireless Networks
Advances in lattice-based cryptography are
enabling the use of public key algorithms
(PKAs) in power-constrained ad hoc and
sensor network devices. Unfortunately, while
many wireless networks are dominated
by group communications, PKAs are
inherently unicast i.e., public/private key pairs
are generated by data destinations. To fully
realize public key cryptography in
these networks, lightweight PKAs should be
augmented with energy-efficient mechanisms
for group key agreement. We consider a
setting where master keys are loaded on clients
according to an arbitrary distribution. We
present a protocol that uses
session keys derived from those master keys to
establish a group key that is information-
IEEE 2015

theoretically secure. When master keys are
distributed randomly, our protocol requires
O(logb t) multicasts, where 1-1 is the
probability that a given client possesses a
given master key. The minimum number of
public multicast transmissions required for a
set of clients to agree on a secret key in our
setting was recently characterized. The
proposed protocol achieves the best possible
approximation to that optimum that is
computable in polynomial time. Moreover, the
computational requirements of our protocol
compare favorably to multi-party extensions of
Diffie-Hellman key exchange.
TTA-DN-
C1512
iPath Path Inference in
Wireless Sensor
Networks
Recent wireless sensor networks (WSNs) are
becoming increasingly complex with the
growing network scale and the dynamic nature
of wireless communications. Many
measurement and diagnostic approaches
depend on per-packet routing paths for
accurate and fine-grained analysis of the
complex network behaviors. In this paper, we
propose iPath, a novel path inference approach
to reconstructing the per-packet
routing paths in dynamic and large-
scale networks. The basic idea of iPath is to
exploit high path similarity to iteratively infer
long paths from short ones. iPath starts with an
initial known set ofpaths and
performs path inference iteratively. iPath inclu
des a novel design of a lightweight hash
function for verification of the inferred paths.
In order to further improve
the inference capability as well as the
execution efficiency, iPath includes a fast
bootstrapping algorithm to reconstruct the
initial set ofpaths. We also
implement iPath and evaluate its performance
using traces from large-scale WSN
deployments as well as extensive simulations.
Results show that iPath achieves much higher
reconstruction ratios under
different network settings compared to other
state-of-the-art approaches.
IEEE 2015

TTA-DN-
C1513
Joint Static and
Dynamic Traffic
Scheduling in Data
Center Networks
The advent and continued growth of
large data centers has led to much interest in
switch architectures that can economically
meet the high capacities needed for
interconnecting the thousands of servers in
these data centers. Various multilayer
architectures employing thousands of switches
have been proposed in the literature. We make
use of the observation that the traffic in
a data center is a mixture of
relatively static and rapidly fluctuating
components, and develop a combined
scheduler for both these components using a
generalization of the load-balanced scheduler.
The presence of the known static component
introduces asymmetries in the ingress-egress
capacities, which preclude the use of a load-
balanced scheduler as is. We generalize the
load-balanced scheduler and also incorporate
an opportunistic scheduler that sends traffic on
a direct path when feasible to enhance the
overall switch throughput. Our evaluations
show that this scheduler works very well
despite avoiding the use of a central scheduler
for making packet-by-
packet scheduling decisions.
IEEE 2015
TTA-DN-
C1514
On Downlink
Beamforming with
Small Cells inWireless
Heterogeneous
Systems
In this letter, we study downlink beam
forming for wireless heterogeneous networks
with two groups of users. The users in one
group (group 1) are supported by the small cell
base station (SBS) as well as the macro cell
base station (MBS), while the users in the
other group (group 2) are supported by the
MBS only. The MBS is equipped with an
antenna array for downlink beam forming. We
formulate a convex optimization problem,
which can be solved by semi definite
programming (SDP) relaxation, for
downlink beam forming that takes advantage
of the presence of the SBS for group 1, but
also takes into account the interfering signal
from the SBS for group 2.
IEEE 2015

TTA-DN-
C1515
On-Demand Discovery
of Software Service
Dependencies in
MANETs
The dependencies among the components
of service-oriented software applications
hosted in a mobile ad hoc network (MANET)
are difficult to determine due to the inherent
loose coupling of the services and the transient
communication topologies of the network. Yet
understanding these dependencies is critical to
making good management decisions, since
dependence data underlie important analyses
such as fault localization and impact analysis.
Current methods for discovering dependencies,
developed primarily for fixed networks,
assume that dependencies change only slowly
and require relatively long monitoring periods
as well as substantial memory and
communication resources, all of which are
impractical in the MANET environment. We
describe a new dynamic dependence discovery
method designed specifically for this
environment, yielding dynamic snapshots of
dependence relationships discovered through
observations of service interactions. We
evaluate the performance of our method in
terms of the accuracy of the
discovered dependencies, and draw insights on
the selection of critical parameters under
various operational conditions. Although
operated under more stringent conditions, our
method is shown to provide results comparable
to or better than existing methods.
IEEE 2015
TTA-DN-
C1516
PWDGR Pair-Wise
Directional
Geographical Routing
Based on Wireless
Sensor Network
Multipath routing in wireless multimedia senso
r network makes it possible to transfer data
simultaneously so as to reduce delay and
congestion and it is worth researching.
However, the current
multipath routing strategy may cause problem
that the node energy near sink becomes
obviously higher than other nodes which
makes the network invalid and dead. It also has
serious impact on the performance
of wireless multimedia sensor network (WMS
N). In this paper, we propose a pair-wise
directional geographical routing (PWDGR)
strategy to solve the energy bottleneck
problem. First, the source node can send the
IEEE 2015

data to the pair-wise node around the sink node
in accordance with certain algorithm and then
it will send the data to the sink node.
These pair-wise nodes are equally selected in
360° scope around sink according to a certain
algorithm. Therefore, it can effectively relieve
the serious energy burden around Sink and also
make a balance between energy consumption
and end-to-end delay. Theoretical analysis and
a lot of simulation experiments
on PWDGR have been done and the results
indicate that PWDGR is superior to the
proposed strategies of the similar strategies
both in the view of the theory and the results of
those simulation experiments. With respect to
the strategies of the same kind, PWDGR is
able to prolong 70% network life. The delay
time is also measured and it is only increased
by 8.1% compared with the similar strategies.
TTA-DN-
C1517
REAL A Reciprocal
Protocol for Location
Privacy in Wireless
Sensor Networks
K-anonymity has been used to
protect location privacy for location monitorin
g services in wireless
sensor networks (WSNs), where sensor nodes
work together to report k-anonymized
aggregate locations to a server. Each k-
anonymized aggregate location is a cloaked
area that contains at least k persons. However,
we identify an attack model to show that
overlapping aggregate locations still pose
privacy risks because an adversary can infer
some overlapping areas with less than k
persons that violates the k-
anonymity privacy requirement. In this paper,
we propose a reciprocal protocol for
location privacy (REAL) in WSNs.
In REAL, sensor nodes are required to
autonomously organize their sensing areas into
a set of non-overlapping and highly accurate k-
anonymized aggregate locations. To confront
the three key challenges in REAL, namely,
self-organization, reciprocity property and high
accuracy, we design a state transition process,
a locking mechanism and a time delay
mechanism, respectively. We compare the
performance of REAL with
IEEE 2015

current protocols through simulated
experiments. The results show
that REAL protects location privacy, provides
more accurate query answers, and reduces
communication and computational costs.
TTA-DN-
C1518
SanGA A Self-Adaptive
Network-Aware
Approach to Service
Composition
Service-Oriented Computing enables
the composition of loosely
coupled services provided with varying
Quality of Service (QoS) levels. Selecting a
near-optimal set of services for
a composition in terms of QoS is crucial when
many functionally equivalent services are
available. As the number of distributed
services, particularly in the cloud, is rising
rapidly, the impact of the network on the QoS
keeps increasing. Despite this,
current approaches do not differentiate
between the QoS of services themselves and
the network. Therefore, the computed latency
differs from the actual latency, resulting in
suboptimal QoS. Thus, we propose a network-
aware approach that handles the QoS
of services and the QoS of
the network independently. First, we build
a network model in order to estimate
the network latency between
arbitrary services and potential users. Our
selection algorithm then leverages this
model to find compositions with a low latency
for a given execution policy. We employ
a self-adaptive genetic algorithm which
balances the optimization of latency and other
QoS as needed and improves the convergence
speed. In our evaluation, we show that
our approach works under realistic network
conditions, efficiently
computing compositions with much lower
latency and otherwise equivalent QoS
compared to current approaches.
IEEE 2015
TTA-DN-
C1519
Secure Binary Image
Stegnograpghy Based
On Minimizing the
disortion on the texture
Most state-of-the-
art binary image steganographic techniques
only consider the flipping distortion according
to the human visual system, which will be
not secure when they are attacked by
IEEE 2015

steganalyzers. In this paper,
a binary image steganographic scheme that
aims to minimize the embedding distortion on
the texture is presented. We extract the
complement, rotation, and mirroring-invariant
local texture patterns (crmiLTPs) from
the binary image first. The weighted sum of
crmiLTP changes when flipping one pixel is
then employed to measure the flipping
distortion corresponding to that pixel. By
testing on both simple binary images and the
constructed image data set, we show that the
proposed measurement can well describe the
distortions on both visual quality and
statistics. Based on the proposed measurement,
a practical steganographic scheme is
developed. The steganographic scheme
generates the cover vector by dividing the
scrambled image into super pixels. Thereafter,
the syndrome-trellis code is employed
to minimize the designed embedding
distortion. Experimental results have
demonstrated that the proposed steganographic
scheme can achieve statistical security without
degrading the image quality or the embedding
capacity.
TTA-DN-
C1520
Software Puzzle A
Countermeasure to
Resource-Inflated
Denial-of- Service
Attacks
Denial-of-service (DoS) and distributed DoS
(DDoS) are among the major threats to cyber-
security, and client puzzle, which demands a
client to perform computationally expensive
operations before being granted services from
a server, is a well-
known countermeasure to them. However, an
attacker can inflate its capability of
DoS/DDoS attacks with fast puzzle-
solving software and/or built-in graphics
processing unit (GPU)
hardware to significantly weaken the
effectiveness of client puzzles. In this paper,
we study how to prevent DoS/DDoS attackers
from inflating their puzzle-solving
capabilities. To this end, we introduce a new
client puzzle referred to as software puzzle.
Unlike the existing client puzzle schemes,
which publish their puzzle algorithms in
IEEE 2015

advance, a puzzle algorithm in the present
software puzzle scheme is randomly generated
only after a client request is received at the
server side and the algorithm is generated such
that: 1) an attacker is unable to prepare an
implementation to solve the puzzle in advance
and 2) the attacker needs considerable effort in
translating a central processing
unit puzzle software to its functionally
equivalent GPU version such that the
translation cannot be done in real time.
Moreover, we show
how to implement software puzzle in the
generic server-browser model.
TTA-DN-
C1521
Task Allocation for
Wireless Sensor
Network Using Modified
Binary Particle Swarm
Optimization
Many applications
of wireless sensor network (WSN) require the
execution of several computationally intense
in-network processing tasks. Collaborative in-
network processing among multiple nodes is
essential when executing such a task due to the
strictly constrained energy and resources in
single node. Task allocation is essential to
allocate the workload of each task to proper
nodes in an efficient manner. In this paper,
a modified version
of binary particle swarm optimization (MBPS
O), which adopts a different transfer function
and a new position updating procedure with
mutation, is proposed for the
task allocation problem to obtain the best
solution. Each particle in MBPSO is encoded
to represent a complete potential solution
for task allocation. The task workload and
connectivity are ensured by taking them as
constraints for the problem. Multiple metrics,
including task execution time, energy
consumption, and network lifetime, are
considered a whole by designing a hybrid
fitness function to achieve the best overall
performance. Simulation results show the
feasibility of the proposed MBPSO-based
approach for task allocation problem in WSN.
The proposed MBPSO-based approach also
outperforms the approaches based on genetic
algorithm and BPSO in the comparative
IEEE 2015

analysis.
TTA-DN-
C1522
Towards Distributed
Optimal Movement
Strategy for Data
Gathering in Wireless
Sensor Network
In this paper, we address how to design
a distributed movement strategy for mobile
collectors, which can be either physical mobile
agents or query/collector packets periodically
launched by the sink, to achieve
successful data gathering in wireless sensor net
works. Formulating the problem as general
random walks on a graph composed
of sensor nodes, we analyze how
much data can be successfully gathered in time
under any Markovian random-
walk movement strategies for mobile
collectors moving over a graph (or network),
while each sensor node is equipped with
limited buffer space and data arrival rates are
heterogeneous over different sensor nodes. In
particular, from the analysis, we obtain the
optimal movement strategy among a class of
Markovian strategies so as to minimize
the data loss rate over all sensor nodes, and
explain how such
an optimal movement strategy can be made to
work in a distributed fashion. We demonstrate
that
our distributed optimal movement strategy can
lead to about 2 times smaller loss rate than a
standard random walk strategy under diverse
scenarios. In particular, our strategy results in
up to 70% cost savings for the deployment of
multiple collectors to achieve the target
data loss rate than the standard random
walk strategy.
IEEE 2015
TTA-DN-
C1523
Universal Network
Coding-Based
Opportunistic Routing
for Unicast
Network coding-
based opportunistic routing has emerged as an
elegant way to optimize the capacity of lossy
wireless multihop networks by reducing the
amount of required feedback messages. Most
of the works on network coding-
based opportunistic routing in the literature
assume that the links are independent. This
assumption has been invalidated by the recent
empirical studies that showed that the
IEEE 2015

correlation among the links can be arbitrary. In
this work, we show that the performance
of network coding-
based opportunistic routing is greatly impacted
by the correlation among the links. We
formulate the problem of maximizing the
throughput while achieving fairness under
arbitrary channel conditions, and we identify
the structure of its optimal solution. As is
typical in the literature, the optimal solution
requires a large amount of immediate feedback
messages, which is unrealistic. We propose the
idea of performing network coding on the
feedback messages and show that if the
intermediate node waits until receiving only
one feedback message from each next-hop
node, the optimal level of network coding
redundancy can be computed in a distributed
manner. The coded feedback messages require
a small amount of overhead, as they can be
integrated with the packets. Our approach is
also oblivious to losses and correlations among
the links, as it optimizes the performance
without the explicit knowledge of these two
factors.
TTA-JN-
C1524
VEGAS Visual influEnce
GrAph Summarization
on Citation Networks
Visually analyzing citation networks poses
challenges to many fields of the data mining
research. How can we summarize a
large citation graph according to the user's
interest? In particular, how can we illustrate
the impact of a highly influential paper through
the summarization? Can we maintain the
sensory node-link graph structure while
revealing the flow-based influence patterns and
preserving a fine readability? The state-of-the-
art influence maximization algorithms can
detect the most influential node in
a citation network, but fail to summarize
a graph structure to account for its influence.
On the other hand,
existing graph summarization methods fold
large graphs into clustered views, but can not
reveal the hidden influence patterns underneath
the citation network. In this paper, we first
formally define
IEEE 2015

the Influence Graph Summarization problem
on citation networks. Second, we propose a
matrix decomposition based algorithm pipeline
to solve the IGS problem. Our method can not
only highlight the flow-
based influence patterns, but also easily extend
to support the rich attribute information. A
prototype system called VEGAS implementing
this pipeline is also developed. Third, we
present a theoretical analysis on our main
algorithm, which is equivalent to the kernel k-
mean clustering. It can be proved that the
matrix decomposition based algorithm can
approximate the objective of the proposed IGS
problem. Last, we conduct comprehensive
experiments with real-
world citation networks to compare the
proposed algorithm with
classical graph summarization methods.
Evaluation results demonstrate that our method
significantly outperforms the previous ones in
optimizing both the quantitative IGS objective
and the quality of the visual summarizations.
TTA-JN-
C1525
Privacy Protection for
Wireless Medical
Sensor Data
In recent
years, wireless sensor networks have
been widely used in healthcare
applications, such as hospital and home
patient
monitoring. Wireless medical sensor net
works are more vulnerable to
eavesdropping, modification,
impersonation and replaying attacks
than the wired networks. A lot of work
has been done to
secure wireless medical sensor networks
. The existing solutions can protect the
patient data during transmission, but
cannot stop the inside attack where the
administrator of the patient database
reveals the sensitive patient data. In this
paper, we propose a practical approach
to prevent the inside attack by using
IEEE 2015

multiple data servers to store
patient data. The main contribution of
this paper is securely distributing the
patient data in multiple data servers and
employing the Paillier and ElGamal
cryptosystems to perform statistic
analysis on the patient data without
compromising the patients’ privacy.
TTA-JN-
C1526
A Decentralized Cloud
Firewall Framework
with Resources
Provisioning Cost
Optimization
Cloud computing is becoming popular as the
next infrastructure of computing platform.
Despite the promising model and hype
surrounding, security has become the major
concern that people hesitate to transfer their
applications to clouds.
Concretely, cloud platform is under numerous
attacks. As a result, it is definitely expected to
establish a firewall to protect cloud from these
attacks. However, setting up a
centralized firewall for a whole cloud data
center is infeasible from both performance and
financial aspects. In this paper, we propose
a decentralized cloud firewall framework for
individual cloud customers. We investigate
how to dynamically allocate resources to
optimize resources provisioning cost, while
satisfying QoS requirement specified by
individual customers simultaneously.
Moreover, we establish novel queuing theory
based model M/Geo/1 and M/Geo/m for
quantitative system analysis, where the service
times follow a geometric distribution. By
employing Z-transform and embedded Markov
chain techniques, we obtain a closed-form
expression of mean packet response time.
Through extensive simulations and
experiments, we conclude that an M/Geo/1
model reflects the cloud firewall real system
much better than a traditional M/M/1 model.
Our numerical results also indicate that we are
able to set up cloud firewall with
affordable cost to cloud customers.
IEEE 2015

TTA-JN-
C1527
A Privacy-Aware
Authentication Scheme
for Distributed Mobile
Cloud Computing
Services
In modern societies, the number
of mobile users has dramatically risen in recent
years. In this paper, an
efficient authentication scheme for distributed
mobile cloud computing services is proposed.
The proposed scheme provides security and
convenience for mobile users to access
multiple mobile cloud
computing services from
multiple service providers using only a single
private key. The security strength of the
proposed scheme is based on bilinear pairing
cryptosystem and dynamic nonce generation.
In addition, the scheme supports
mutual authentication, key exchange, user
anonymity, and user untraceability. From
system implementation point of view,
verification tables are not required for the
trusted smart card generator
(SCG) service and cloud computing service pr
oviders when adopting the proposed scheme.
In consequence, this scheme reduces the usage
of memory spaces on these
corresponding service providers. In
one mobile user authentication session, only
the targeted cloud service provider needs to
interact with the service requestor (user). The
trusted SCG serves as the secure key
distributor
for distributed cloud service providers
and mobile clients. In the proposed scheme,
the trusted SCG service is not involved in
individual user authentication process. With
this design,
our scheme reduces authentication processing
time required by communication and
computation between cloud service providers
and traditional trusted third party service.
Formal security proof and performance
analyses are conducted to show that
the scheme is both secure and efficient.
IEEE 2015
TTA-JN-
C1528
CPCDN Content
Delivery Powered by
Context and User
Intelligence
There is an unprecedented trend
that content providers (CPs) are building their
own content delivery networks (CDNs) to
provide a variety of content services to
IEEE 2015

their users. By exploiting powerful CP-level
information in content distribution, these CP-
built CDNs open up a whole new design space
and are changing
the content delivery landscape. In this paper,
we adopt a measurement-based approach to
understanding why, how, and how much CP-
level intelligences can help content delivery.
We first present a measurement study of the
CDN built by Tencent, a
largest content provider based in China. We
observe new characteristics and trends
in content delivery which pose great
challenges to the
conventional content delivery paradigm and
motivate the proposal of CPCDN, a
CDN powered by CP-aware information. We
then reveal the benefits obtained by exploiting
two indispensable CP-level intelligences,
namely context intelligence and user intelligen
ce, in content delivery. Inspired by the insights
learnt from the measurement studies, we
systematically explore the design space
of CPCDNand present the novel architecture
and algorithms to address the
new content delivery challenges that have
arisen. Our results not only demonstrate the
potential of CPCDN in
pushing content delivery performance to the
next level, but also identify new research
problems calling for further investigation.
TTA-JN-
C1529
QoS Evaluation for Web
Service
Recommendation
Web service recommendation is one of the
most important fields of research in the area
of service computing. The two core problems
of Web service recommendation are the
prediction of unknown QoSproperty values
and the evaluation of overall QoS according to
user preferences. Aiming to address these two
problems and their current challenges, we
propose two efficient approaches to solve these
problems. First, unknown QoS property values
were predicted by modeling the high-
dimensional QoSdata as tensors, by utilizing
an important tensor operation, i.e., tensor
composition, to predict these QoSvalues. Our
IEEE 2015

method, which considers all QoS dimensions
integrally and uniformly, allows us to predict
multi-dimensional QoS values accurately and
easily. Second, the overall QoS was evaluated
by proposing an efficient user preference
learning method, which learns user preferences
based on users' ratings history data, allowing
us to obtain user preferences quantifiably and
accurately. By solving these two core
problems, it became possible to compute a
realistic value for the overall QoS. The
experimental results showed our proposed
methods to be more efficient than existing
methods.
TTA-JN-
C1530
Towards Information
Diffusion in Mobile
Social Networks
The emerging of mobile social networks opens
opportunities for viral marketing. However,
before fully utilizing mobile social networks as
a platform for viral marketing, many
challenges have to be addressed. In this paper,
we address the problem of identifying a small
number of individuals through whom
the information can be diffused to
the network as soon as possible, referred to as
the diffusion minimization
problem. Diffusion minimization under the
probabilistic diffusion model can be
formulated as an asymmetric k- center problem
which is NP-hard, and the best known
approximation algorithm for the asymmetric k-
center problem has approximation ratio of log
n and time complexity O(n5). Clearly, the
performance and the time complexity of the
approximation algorithm are not satisfiable in
large-scale mobile social networks. To deal
with this problem, we propose a community
based algorithm and a distributed set-cover
algorithm. The performance of the proposed
algorithms is evaluated by extensive
experiments on both synthetic networks and a
real trace. The results show that the
community based algorithm has the best
performance in both synthetic networks and
the real trace compared to existing algorithms,
and the distributed set-cover algorithm
outperforms the approximation algorithm in
IEEE 2015

the real trace in terms of diffusion time.
TTA-JN-
C1531
Location-Sharing
Systems With
Enhanced Privacy in
Mobile Online Social
Networks
Location sharing is one of the critical
components
in mobile online social networks (mOSNs),
which has attracted much attention recently.
With the advent of mOSNs, more and more
users' location information will be collected by
the service providers in mOSN. However, the
users' privacy, including
location privacy and social network privacy,
cannot be guaranteed in the previous work
without the trust assumption on the service
providers. In this paper, aiming at
achieving enhanced privacy against the insider
attack launched by the service providers in
mOSNs, we introduce a new architecture with
multiple location servers for the first time and
propose a secure solution
supporting location sharing among friends and
strangers in location-based applications. In our
construction, the user's friend set in each
friend’s query submitted to the location servers
is divided into multiple subsets by the social
network server randomly. Each location server
can only get a subset of friends, instead of the
whole friends' set of the user as the previous
work. In addition, for the first time, we
propose a location-sharing construction which
provides check ability of the searching results
returned from location servers in an efficient
way. We also prove that the new construction
is secure under the stronger security model
with enhanced privacy. Finally, we provide
extensive experimental results to demonstrate
the efficiency of our proposed construction.
IEEE 2015
TTA-JN-
C1532
Mobile Based
Healthcare
Management Using
Artificial Intelligence
In this growing age of technology it is
necessary to have a proper health
care management system which should be cent
percent accurate but also should be portable so
that every person carry with it as personalized
health care system. The health
care management system which will consist
of mobile based Heart Rate Measurement so
IEEE 2015

that the data can be transferred and
diagnosis based on heart rate can be provided
quickly with a click of button. The system will
consist of video conferencing to connect
remotely with the Doctor. The Doc-Bot which
was developed earlier is now being transferred
to mobile platform and will be further
advanced for diagnosis of common diseases.
The system will also consist of Online Blood
Bank which will provide up-to-date details
about availability of blood in different
hospitals.
TTA-JN-
C1533
PSMPA Patient Self-
Controllable and Multi-
Level Privacy-
Preserving Cooperative
Authentication in
Distributed m-
Healthcare Cloud
Computing System
Distributed m-
healthcare cloud computing system significantl
y facilitates efficient patient treatment for
medical consultation by sharing personal
health information
among healthcare providers. However, it
brings about the challenge of keeping both the
data confidentiality and patients'
identity privacy simultaneously. Many existing
access control and
anonymous authentication schemes cannot be
straightforwardly exploited. To solve the
problem, in this paper, a novel authorized
accessible privacy model (AAPM) is
established. Patients can authorize physicians
by setting an access tree supporting flexible
threshold predicates. Then, based on it, by
devising a new technique of attribute-based
designated verifier signature, a patient self-
controllable multi-level privacy-
preserving cooperativeauthentication scheme
(PSMPA) realizing three levels of security
and privacy requirement in distribute dm-
healthcare cloud computing system is
proposed. The directly authorized physicians,
the indirectly authorized physicians and the
unauthorized persons in medical consultation
can respectively decipher the personal health
information and/or verify patients' identities by
satisfying the access tree with their own
attribute sets. Finally, the formal security proof
and simulation results illustrate our scheme
can resist various kinds of attacks and far
IEEE 2015

outperforms the previous ones in terms of
computational, communication and storage
overhead.
TTA-JN-
C1534
Secure and Distributed
Data Discovery and
Dissemination in
Wireless Sensor
Networks
A data discovery and dissemination protocol
for wireless sensor networks (WSNs) is
responsible for updating configuration
parameters of, and distributing management
commands to, the sensor nodes. All
existing data discovery and dissemination prot
ocols suffer from two drawbacks. First, they
are based on the centralized approach; only the
base station can distribute data items. Such an
approach is not suitable for emergent multi-
owner-multi-user WSNs. Second, those
protocols were not designed with security in
mind and hence adversaries can easily launch
attacks to harm the network. This paper
proposes the
first secure and distributed data discovery and
dissemination protocol named DiDrip. It
allows the network owners to authorize
multiple network users with different
privileges to simultaneously and directly
disseminate data items to the sensor nodes.
Moreover, as demonstrated by our theoretical
analysis, it addresses a number of possible
security vulnerabilities that we have identified.
Extensive security analysis show DiDrip is
provably secure. We also implement DiDrip in
an experimental network of resource-
limited sensor nodes to show its high
efficiency in practice.
IEEE 2015
TTA-JN-
C1535
DDSGA A Data-Driven
Semi-Global Alignment
Approach for Detecting
Masquerade Attacks
A masquerade attacker impersonates a legal
user to utilize the user services and privileges.
The semi-global alignment algorithm (SGA) is
one of the most effective and efficient
techniques to detect these attacks but it has not
reached yet the accuracy and performance
required by large scale, multiuser systems. To
improve both the effectiveness and the
performances of this algorithm, we propose the
Data-Driven Semi-
Global Alignment, DDSGA approach. From
the security effectiveness view point,
IEEE 2015

DDSGA improves the scoring systems by
adopting distinct alignment parameters for
each user. Furthermore, it tolerates small
mutations in user command sequences by
allowing small changes in the low-level
representation of the commands functionality.
It also adapts to changes in the user behavior
by updating the signature of a user according
to its current behavior. To optimize the
runtime overhead, DDSGA minimizes
the alignment overhead and parallelizes the
detection and the update. After describing
the DDSGA phases, we present the
experimental results that show that DDSGA
achieves a high hit ratio of 88.4 percent with a
low false positive rate of 1.7 percent. It
improves the hit ratio of the enhanced SGA by
about 21.9 percent and reduces Maxion-
Townsend cost by 22.5 percent.
Hence, DDSGA results in improving both the
hit ratio and false positive rates with an
acceptable computational overhead.
TTA-JN-
C1536
Revisiting Attribute-
Based Encryption with
Verifiable Outsourced
Decryption
Attribute-based encryption (ABE) is a
promising technique for fine-grained access
control of encrypted data in a cloud storage,
however, decryption involved in the ABEs is
usually too expensive for resource-constrained
front-end users, which greatly hinders its
practical popularity. In order to reduce
the decryption overhead for a user to recover
the plaintext, Green et al. suggested
to outsource the majority of
the decryption work without revealing actually
data or private keys. To ensure the third-party
service honestly computes
the outsourced work, Lai et al. provided a
requirement of verifiability to the
decryption of ABE, but their scheme doubled
the size of the underlying ABE ciphertext and
the computation costs. Roughly speaking, their
main idea is to use a
parallel encryption technique, while one of
the encryption components is used for the
verification purpose. Hence, the bandwidth and
the computation cost are doubled. In this
IEEE 2015

paper, we investigate the same problem. In
particular, we propose a more efficient and
generic construction of ABE
with verifiable outsourced decryption based on
an attribute-based key encapsulation
mechanism, a symmetric-
key encryption scheme and a commitment
scheme. Then, we prove the security and the
verification soundness of our constructed ABE
scheme in the standard model. Finally, we
instantiate our scheme with concrete building
blocks. Compared with Lai et al.'s scheme, our
scheme reduces the bandwidth and the
computation costs almost by half.
TTA-JN-
C1537
A Strategy of
Clustering Modification
Directions in Spatial
Image Steganography
Most of the recently proposed
steganographic schemes are based on
minimizing an additive distortion
function defined as the sum of
embedding costs for individual pixels.
In such an approach, mutual embedding
impacts are often ignored. In this paper,
we present an approach that can exploit
the interactions among embedding
changes in order to reduce the risk of
detection by steganalysis. It employs a
novel strategy,
called clustering modification directions
(CMDs), based on the assumption that
when embedding modifications in
heavily textured regions are locally
heading toward the same direction, the
steganographic security might be
improved. To implement the strategy, a
cover image is decomposed into several
sub images, in which message segments
are embedded with well-known
schemes using additive distortion
functions. The costs of pixels are
updated dynamically to take mutual
embedding impacts into account.
Specifically, when neighboring pixels
IEEE 2015

are changed toward a
positive/negative direction, the cost of
the considered pixel is biased toward
the same direction. Experimental results
show that our proposed CMD strategy,
incorporated into existing
steganographic schemes, can effectively
overcome the challenges posed by the
modern steganalyzers with high-
dimensional features.
TTA-JN-
C1538
An Access Control
Model for Online Social
Networks Using User-
to-User Relationships
Users and resources
in online social networks (OSNs) are
interconnected via various types of
relationships. In particular, user-to-
user relationships form the basis of the OSN
structure, and play a significant role in
specifying and enforcing access control.
Individual users and the OSN provider should
be enabled to specify which access can be
granted in terms of existing relationships. In
this paper, we propose a novel user-to-
user relationship-
based access control (UURAC) model for
OSN systems that utilizes regular expression
notation for such policy
specification. Access control policies on users
and resources are composed in terms of
requested action, multiple relationship types,
the starting point of the evaluation, and the
number of hops on the path. We present two
path checking algorithms to determine whether
the required relationship path between users
for a given access request exists. We validate
the feasibility of our approach by
implementing a prototype system and
evaluating the performance of these two
algorithms.
IEEE 2015
TTA-JN-
C1539
An Authenticated Trust
and Reputation
Calculation and
Management System
for Cloud and Sensor
Networks Integration
Induced by incorporating the powerful data
storage and data processing abilities
of cloud computing (CC) as well as ubiquitous
data gathering capability of
wireless sensor networks (WSNs), CC-WSN
integration received a lot of attention from
IEEE 2015

both academia and industry. However,
authentication as well
as trust and reputation calculation and manage
ment of cloud service providers (CSPs)
and sensor network providers (SNPs) are two
very critical and barely explored issues for this
new paradigm. To fill the gap, this paper
proposes a
novel authenticated trust and reputation calcula
tion and management (ATRCM) system for
CC-WSN integration. Considering the
authenticity of CSP and SNP, the attribute
requirement of cloud service user (CSU) and
CSP, the cost, trust, and reputation of the
service of CSP and SNP, the proposed
ATRCM system achieves the following three
functions: 1) authenticating CSP and SNP to
avoid malicious impersonation attacks; 2)
calculating and managing trust and reputation
regarding the service of CSP and SNP; and 3)
helping CSU choose desirable CSP and
assisting CSP in selecting appropriate SNP.
Detailed analysis and design as well as further
functionality evaluation results are presented to
demonstrate the effectiveness of ATRCM,
followed with system security analysis.
TTA-JN-
C1540
An Efficient Privacy-
Preserving Ranked
Keyword Search
Method
Cloud data owners prefer to outsource
documents in an encrypted form for the
purpose of privacy preserving. Therefore it is
essential to develop efficient and reliable
ciphertext search techniques. One challenge is
that the relationship between documents will
be normally concealed in the process of
encryption, which will lead to
significant search accuracy performance
degradation. Also the volume of data in data
centers has experienced a dramatic growth.
This will make it even more challenging to
design ciphertext search schemes that can
provide efficient and reliable online
information retrieval on large volume of
encrypted data. In this paper, a hierarchical
clustering method is proposed to support
more search semantics and also to meet the
demand for fast ciphertext search within a big
IEEE 2015

data environment. The proposed hierarchical
approach clusters the documents based on the
minimum relevance threshold, and then
partitions the resulting clusters into sub-
clusters until the constraint on the maximum
size of cluster is reached. In the search phase,
this approach can reach a linear computational
complexity against an exponential size
increase of document collection. In order to
verify the authenticity of search results, a
structure called minimum hash sub-tree is
designed in this paper. Experiments have been
conducted using the collection set built from
the IEEE Xplore. The results show that with a
sharp increase of documents in the dataset
the search time of the proposed method
increases linearly whereas the search time of
the traditional method increases exponentially.
Furthermore, the proposed method has an
advantage over the traditional method in
the rank privacy and relevance of retrieved
documents.
TTA-JN-
C1541
An Internal Intrusion
Detection and
Protection System by
Using Data Mining and
Forensic Techniques
Currently, most computer systems use user IDs
and passwords as the login patterns to
authenticate users. However, many people
share their login patterns with coworkers and
request these coworkers to assist co-tasks,
thereby making the pattern as one of the
weakest points of computer security. Insider
attackers, the valid users of a system who
attack the system internally, are hard to detect
since most intrusion detection systems and
firewalls identify and isolate malicious
behaviors launched from the outside world of
the system only. In addition, some studies
claimed that analyzing system calls (SCs)
generated by commands can identify these
commands, with which to accurately detect
attacks, and attack patterns are the features of
an attack. Therefore, in this paper, a
security system, named the
Internal Intrusion Detection and Protection Sys
tem (IIDPS), is proposed to detect insider
attacks at SC
level by using data mining and forensic techniq
IEEE 2015

ues. The IIDPS creates users' personal profiles
to keep track of users' usage habits as
their forensic features and determines whether
a valid login user is the account holder or
not by comparing his/her current computer
usage behaviors with the patterns collected in
the account holder's personal profile. The
experimental results demonstrate that the
IIDPS's user identification accuracy is 94.29%,
whereas the response time is less than 0.45 s,
implying that it can prevent a
protected system from insider attacks
effectively and efficiently.
TTA-JN-
C1542
Cloud-Assisted Safety
Message Dissemination
in VANET–Cellular
Heterogeneous
Wireless Network
In vehicular ad hoc networks (VANETs),
efficient message dissemination is critical to
road safety and traffic efficiency. Since many
VANET-based schemes suffer from high
transmission delay and data redundancy, the
integrated VANET–
cellular heterogeneous network has been
proposed recently and attracted significant
attention. However, most existing studies focus
on selecting suitable gateways to
deliver safety message from the source vehicle
to a remote server, whereas
rapid safety message dissemination from the
remote server to a targeted area has not been
well studied. In this paper, we propose a
framework for
rapid message dissemination that combines the
advantages of diverse communication
and cloud computing technologies.
Specifically, we propose a novel Cloud-
assisted
Message Downlink dissemination Scheme
(CMDS), with which the safety messages in
the cloud server are first delivered to the
suitable mobile gateways on relevant roads
with the help of cloud computing (where
gateways are buses with both cellular and
VANET interfaces), and then being
disseminated among neighboring vehicles via
vehicle-to-vehicle (V2V) communication. To
evaluate the proposed scheme, we
mathematically analyze its performance and
IEEE 2015

conduct extensive simulation experiments.
Numerical results confirm the efficiency of
CMDS in various urban scenarios.
TTA-JN-
C1543
Collaborative Task
Execution in Mobile
Cloud Computing
Under a Stochastic
Wireless Channel
This paper
investigates collaborative task execution betwe
en a mobile device and a cloud clone for
mobile applications under
a stochastic wireless channel.
A mobile application is modeled as a sequence
of tasks that can be executed on
the mobile device or on the cloud clone. We
aim to minimize the energy consumption on
the mobile device while meeting a time
deadline, by strategically offloading tasks to
the cloud. We formulate
the collaborative task execution as a
constrained shortest path problem. We derive a
one-climb policy by characterizing the optimal
solution and then propose an enumeration
algorithm for
the collaborative task execution in polynomial
time. Further, we apply the LARAC algorithm
to solving the optimization problem
approximately, which has lower complexity
than the enumeration algorithm. Simulation
results show that the approximate solution of
the LARAC algorithm is close to the optimal
solution of the enumeration algorithm. In
addition, we consider a probabilistic time
deadline, which is transformed to hard
deadline by Markov inequality. Moreover,
compared to the local execution and the
remote execution,
the collaborative task execution can
significantly save the energy consumption on
the mobile device, prolonging its battery life.
IEEE 2015
TTA-JN-
C1544
Contact-Aware Data
Replication in Roadside
Unit Aided Vehicular
Delay Tolerant
Networks
Roadside units (RSUs), which enable vehicles-
to infrastructure communications, are deployed
along roadsides to handle the ever-growing
communication demands caused by explosive
increase of vehicular traffics. How to
efficiently utilize them to enhance
the vehicular delay tolerant network (VDTN)
performance are the important problems in
IEEE 2015

designing RSU-aided VDTNs. In this work,
we implement an extensive experiment
involving tens of thousands of operational
vehicles in Beijing city. Based on this newly
collected Beijing trace and the existing
Shanghai trace, we obtain some invariant
properties for communication contacts of large
scale RSU-aided VDTNs. Specifically, we find
that the contact time between RSUs and
vehicles obeys an exponential distribution,
while the contact rate between them follows a
Poisson distribution. According to these
observations, we investigate the problem of
communication contact-
aware mobile data replication for RSU-
aided VDTNs by considering the mobile
data dissemination system that
transmits data from the Internet to vehicles via
RSUs through opportunistic communications.
In particular, we formulate the
communication contact-aware RSU-
aidedvehicular mobile data dissemination
problem as an optimization problem with
realistic VDTN settings, and we provide an
efficient heuristic solution for this NP-hard
problem. By carrying out extensive simulation
using realistic vehicular traces, we demonstrate
the effectiveness of our proposed heuristic
contact-aware data replication scheme, in
comparison with the optimal solution and other
existing schemes.
TTA-JN-
C1545
Cost-Aware SEcure
Routing (CASER)
Protocol Design for
Wireless Sensor
Networks
Lifetime optimization and security are two
conflicting design issues for multi-
hop wireless sensor networks (WSNs) with
non-replenishable energy resources. In this
paper, we first propose a novel secure and
efficient Cost-
Aware Secure Routing (CASER) protocol to
address these two conflicting issues through
two adjustable parameters: energy balance
control (EBC) and probabilistic-based random
walking. We then discover that the energy
consumption is severely disproportional to the
uniform energy deployment for the
given network topology, which greatly reduces
IEEE 2015

the lifetime of the sensor networks. To solve
this problem, we propose an efficient non-
uniform energy deployment strategy to
optimize the lifetime and message delivery
ratio under the same energy resource and
security requirement. We also provide a
quantitative security analysis on the
proposed routing protocol. Our theoretical
analysis and OPNET simulation results
demonstrate that the
proposed CASER protocol can provide an
excellent tradeoff between routing efficiency
and energy balance, and can significantly
extend the lifetime of the sensor networks in
all scenarios. For the non-uniform energy
deployment, our analysis shows that we can
increase the lifetime and the total number of
messages that can be delivered by more than
four times under the same assumption. We also
demonstrate that the proposed
CASER protocol can achieve a high message
delivery ratio while preventing routing trace
back attacks.
TTA-JN-
C1546
Deleting Secret Data
with Public Verifiability
Existing software-based data erasure programs
can be summarized as following the same one-
bit-return protocol: the deletion program
performs data erasure and returns either
success or failure. However, such a onebit-
return protocol turns the data deletion system
into a black box – the user has to trust the
outcome but cannot easily verify it. This is
especially problematic when the deletion
program is encapsulated within a Trusted
Platform Module (TPM), and the user has no
access to the code inside. In this paper, we
present a cryptographic solution that aims to
make the data deletion process more
transparent and verifiable. In contrast to the
conventional black/white assumptions about
TPM (i.e., either completely trust or distrust),
we introduce a third assumption that sits in
between: namely, “trust-but-verify”. Our
solution enables a user to verify the correct
implementation of two important operations
IEEE 2015

inside a TPM without accessing its source
code: i.e., the correct encryption of data and
the faithful deletion of the key. Finally, we
present a proof-of-concept implementation of
the SSE system on a resource-constrained Java
card to demonstrate its practical feasibility. To
our knowledge, this is the first systematic
solution to the secure data deletion problem
based on a “trust-but-verify” paradigm,
together with a concrete prototype
implementation.
TTA-JN-
C1547
Design and Evaluation
of the Optimal Cache
Allocation for Content-
Centric Networking
Content-Centric Networking (CCN) is a
promising framework to rebuild the Internet’s
forwarding substrate around the concept
of content. CCN advocates ubiquitous in-
network caching to enhance content delivery
and thus each router has storage space
to cache frequently requested content. In this
work, we focus on
the cache allocation problem, namely, how to
distribute the cache capacity across routers
under a constrained total storage budget for
the network. We first formulate this problem
as a content placement problem and obtain
the optimal solution by a two-step method. We
then propose a suboptimal heuristic method
based on node centrality, which is more
practical in dynamic networks with
frequent content publishing. We investigate
through simulations the factors that affect
the optimal cache allocation, and perhaps more
importantly we use a real-life Internet topology
and video access logs from a large scale
Internet video provider to evaluate the
performance of various cache allocation
methods. We observe that network topology
and content popularity are two important
factors that affect where exactly
should cache capacity be placed. Further, the
heuristic method comes with only a very
limited performance penalty compared to
the optimal allocation. Finally, using our
findings, we provide recommendations
for network operators on the best deployment
IEEE 2015

of CCN caches capacity over routers.
TTA-JN-
C1548
Designing High
Performance Web-
Based Computing
Services to Promote
Telemedicine Database
Management System
Many web computing systems are running real
time database services where their information
change continuously and expand
incrementally. In this
context, web data services have a major role
and draw significant improvements in
monitoring and controlling the information
truthfulness and data propagation.
Currently, web telemedicine database services
are of central
importance to distributed systems. However,
the increasing complexity and the rapid growth
of the real world healthcare challenging
applications make it hard to induce
the database administrative staff. In this paper,
we build an integrated web data services that
satisfy fast response time for large scale Tele-
health database management systems. Our
focus will be on database management with
application scenarios in
dynamic telemedicine systems to increase care
admissions and decrease care difficulties such
as distance, travel, and time limitations. We
propose three-fold approach based on data
fragmentation, database websites clustering
and intelligent data distribution. This approach
reduces the amount of data migrated between
websites during applications' execution;
achieves cost-effective communications during
applications' processing and improves
applications' response time and throughput.
The proposed approach is validated internally
by measuring the impact of using
our computing services' techniques on
various performance features like
communications cost, response time, and
throughput. The external validation is achieved
by comparing the performance of our
approach to that of other techniques in the
literature. The results show that our integrated
approach significantly improves the
performance of web database systems and
outperforms its counterparts.
IEEE 2015

TTA-JN-
C1549
Distributed Database
Management
Techniques for Wireless
Sensor Networks
In sensor networks, the large amount of data
generated by sensors greatly influences the
lifetime of the network. To manage this
amount of sensed data in an energy-efficient
way, new methods of storage and data query
are needed. In this way,
the distributed database approach
for sensor networks is proved as one of the
most energy-efficient data storage and
query techniques. This paper surveys the state
of the art of the techniques used to manage
data and queries
in wireless sensor networks based on
the distributed paradigm. A classification of
these techniques is also proposed. The goal of
this work is not only to present how data and
query management techniques have advanced
nowadays, but also show their benefits and
drawbacks, and to identify open issues
providing guidelines for further contributions
in this type of distributed architectures.
IEEE 2015
TTA-JN-
C1550
Diversifying Web
Service
Recommendation
Results via Exploring
Service Usage History
The last decade has witnessed a tremendous
growth of Web services as a major technology
for sharing data, computing resources, and
programs on the Web. With the increasing
adoption and presence of Web services, design
of novel approaches for
effective Web service recommendation to
satisfy users’ potential requirements has
become of paramount importance.
Existing Web service
recommendation approaches mainly focus on
predicting missing QoS values of Web service
candidates which are interesting to a user using
collaborative filtering approach, content-based
approach, or their hybrid.
These recommendation approaches assume
that recommended Web services are
independent to each other, which sometimes
may not be true. As a result, many similar or
redundant Web services may exist in
a recommendation list. In this paper, we
IEEE 2015

propose a novel Web
service recommendation approach
incorporating a user’s potential QoS
preferences and diversity feature of user
interests on Web services. User’s interests and
QoS preferences on Web services are first
mined
by exploring the Web service usage history.
Then we compute scores of Web service
candidates by measuring their relevance with
historical and potential user interests, and their
QoS utility. We also construct
a Web service graph based on the functional
similarity between Web services. Finally, we
present an innovative diversity-
aware Web service ranking algorithm to rank
the Web service candidates based on their
scores, and diversity degrees derived from
the Web service graph. Extensive experiments
are conducted based on a real
world Web service dataset, indicating that our
proposed Web service recommendation approa
ch significantly improves the quality of their
commendation results compared with existing
methods.
TTA-JN-
C1551
DROPS Division and
Replication of Data in
Cloud for Optimal
Performance and
Security
Outsourcing data to a third-party
administrative control, as is done
in cloud computing, gives rise to
security concerns. The data compromise may
occur due to attacks by other users and nodes
within the cloud. Therefore,
high security measures are required to
protect data within the cloud. However, the
employed security strategy must also take into
account the optimization of the data retrieval
time. In this paper, we
propose Division and Replication of Data in
the Cloud for Optimal Performance and Securi
ty (DROPS) that collectively approaches
the security and performance issues. In
the DROPS methodology, we divide a file into
fragments, and replicate the
fragmented data over the cloud nodes. Each of
the nodes stores only a single fragment of a
particular data file that ensures that even in
IEEE 2015

case of a successful attack, no meaningful
information is revealed to the attacker.
Moreover, the nodes storing the fragments, are
separated with certain distance by means of
graph T-coloring to prohibit an attacker of
guessing the locations of the fragments.
Furthermore, the DROPS methodology does
not rely on the traditional cryptographic
techniques for the data security; thereby
relieving the system of computationally
expensive methodologies. We show that the
probability to locate and compromise all of the
nodes storing the fragments of a single file is
extremely low. We also compare
the performance of the DROPS methodology
with ten other schemes. The higher level
of security with slight performance overhead
was observed.
TTA-JN-
C1552
Dynamic Bin Packing
for On-Demand Cloud
Resource Allocation
Dynamic Bin Packing (DBP) is a variant of
classical bin packing, which assumes that
items may arrive and depart at arbitrary times.
Existing works on DBP generally aim to
minimize the maximum number of bins ever
used in the packing. In this paper, we consider
a new version of the DBP problem, namely,
the MinTotal DBP problem which targets at
minimizing the total cost of the bins used over
time. It is motivated by the request dispatching
problem arising from cloud gaming systems.
We analyze the competitive ratios of the
modified versions of the commonly used First
Fit, Best Fit, and Any Fit packing(the family
of packing algorithms that open a new bin only
when no currently open bin can accommodate
the item to be packed) algorithms for the
MinTotal DBP problem. We show that the
competitive ratio of Any Fit packing cannot be
better than + 1, where is the ratio of the
maximum item duration to the minimum item
duration. The competitive ratio of Best
Fit packing is not bounded for any given. For
First Fit packing, if all the item sizes are
smaller than 1 of the bin capacity (> 1 is a
constant), the competitive ratio has an upper
bound of �1 + 3 �1 + 1. For the general case,
IEEE 2015

the competitive ratio of First Fit packing has
an upper bound of 2 + 7. We also propose a
Hybrid First Fit packing algorithm that can
achieve a competitive ratio no larger than 5 4 +
19 4 when is not known and can achieve a
competitive ratio no larger than + 5 when is
known.
TTA-JN-
C1553
Location-Aware and
Personalized
Collaborative Filtering
for Web Service
Recommendation
Collaborative Filtering (CF) is widely
employed for
making Web service recommendation. CF-
based Web service recommendation aims to
predict missing QoS (Quality-of-Service)
values of Webservices. Although several CF-
based Web service QoS prediction methods
have been proposed in recent years, the
performance still needs significant
improvement. Firstly, existing QoS prediction
methods seldom
consider personalized influence of users
and services when measuring the similarity
between users and between services.
Secondly, Web service QoS factors, such as
response time and throughput, usually depends
on the locations of Web services and users.
However, existing Webservice QoS prediction
methods seldom took this observation into
consideration. In this paper, we propose
a location-aware personalized CF method
for Web service recommendation. The
proposed method leverages both locations of
users and Web services when selecting similar
neighbors for the target user or service. The
method also includes an enhanced similarity
measurement for users andWeb services, by
taking into account the personalized influence
of them. To evaluate the performance of our
proposed method, we conduct a set of
comprehensive experiments using a real-
world Webservice dataset. The experimental
results indicate that our approach improves the
QoS prediction accuracy and computational
efficiency significantly, compared to previous
CF-based methods.
IEEE 2015

TTA-JN-
C1554
Location-Based Key
Management Strong
Against Insider Threats
in Wireless Sensor
Networks
To achieve secure communications
in wireless sensor networks (WSNs), sensor no
des (SNs) must establish secret
shared keys with neighboring nodes.
Moreover, those keys must be updated by
defeating the insider threats of corrupted
nodes. In this paper, we propose a location-
based key management scheme for WSNs,
with special considerations of insider threats.
After reviewing existing location-
based key management schemes and studying
their advantages and disadvantages, we
selected location-
dependent key management (LDK) as a
suitable scheme for our study. To solve a
communication interference problem in LDK
and similar methods, we have devised a
new key revision process that incorporates
grid-based location information. We also
propose a key establishment process using grid
information. Furthermore, we
construct key update and revocation processes
to effectively resist inside attackers. For
analysis, we conducted a rigorous simulation
and confirmed that our method can increase
connectivity while decreasing the compromise
ratio when the minimum number of
common keys required for key establishment is
high. When there was a corrupted node
leveraging insider threats, it was also possible
to effectively rekey every SN except for the
corrupted node using our method. Finally, the
hexagonal deployment of anchor nodes could
reduce network costs.
IEEE 2015
TTA-JN-
C1555
Malware Propagation in
Large-Scale Networks
Malware is pervasive in networks, and poses a
critical threat to network security. However,
we have very limited understanding
of malware behavior in networks to date. In
this paper, we investigate how
malware propagates in networks from a global
perspective. We formulate the problem, and
establish a rigorous two layer epidemic model
for malware propagation from network to netw
ork. Based on the proposed model, our analysis
indicates that the distribution of a
IEEE 2015

given malware follows exponential
distribution, power law distribution with a
short exponential tail, and power law
distribution at its early, late and final stages,
respectively. Extensive experiments have been
performed through two real-world
global scale malware data sets, and the results
confirm our theoretical findings.
TTA-JN-
C1556
Optimal Cloudlet
Placement and User to
Cloudlet Allocation in
Wireless Metropolitan
Area Networks
Mobile applications are becoming increasingly
computation-intensive, while the computing
capability of portable mobile devices is
limited. A powerful way to reduce the
completion time of an application in a mobile
device is to offload its tasks to nearby
cloudlets, which consist of clusters of
computers. Although there is a significant
body of research in mobile cloudlet offloading
technology, there has been very little attention
paid to how cloudlets should be placed in a
given network to optimize mobile application
performance. In this paper we
study cloudlet placement and
mobile user allocation to the cloudlets in
a wireless metropolitan area network (WMAN)
. We devise an algorithm for the problem,
which enables the placement of the cloudlets
at user dense regions of the WMAN, and
assigns mobile users to the placed cloudlets
while balancing their workload. We also
conduct experiments through simulation. The
simulation results indicate that the
performance of the proposed algorithm is very
promising.
IEEE 2015
TTA-JN-
C1557
Predistribution Scheme
for Establishing Group
Keys in Wireless
Sensor Networks
Wireless sensor networks (WSNs). This is
because sensor nodes are limited in memory
storage and computational power. In 1992,
Blundo et al. proposed a non
interactive group key establishment scheme
using a multivariate polynomial.
Their scheme can establish a group key of
m sensors. Since each share is a polynomial
involving m - 1 variables and having degree k,
each sensor needs to store (k + 1)m-
1 coefficients from GF(p), which is
IEEE 2015

exponentially proportional to the size of group.
This makes their scheme only practical when
m = 2 for peer-to-peer communication. So far,
most existing predistribution schemes in
WSNs establish pair
wise keys for sensor nodes. In this paper, we
propose a novel design to propose
a predistribution scheme for establishing group
keys in WSNs. Our design uses a special-type
multivariate polynomial in ZN, where N is a
RSA modulus. The advantage of using this
type of multivariate polynomial can limit the
storage space of each sensor to be m(k + 1),
which is linearly proportional to the size
of group communication. In addition, we prove
the security of the proposed scheme and show
that the computational complexity of the
proposed scheme is efficient.
TTA-JN-
C1558
Privacy-Preserving
Detection of Sensitive
Data Exposure
Statistics from security firms, research
institutions and government organizations
show that the number of data-leak instances
have grown rapidly in recent years. Among
various data-leak cases, human mistakes are
one of the main causes of data loss. There exist
solutions detecting inadvertent sensitive
data leaks caused by human mistakes and to
provide alerts for organizations. A common
approach is to screen content in storage and
transmission for exposed sensitive information.
Such an approach usually requires
the detection operation to be conducted in
secrecy. However, this secrecy requirement is
challenging to satisfy in practice,
as detection servers may be compromised or
outsourced. In this paper, we present a privacy-
preserving data-leak detection (DLD) solution
to solve the issue where a special set
of sensitive data digests is used in detection.
The advantage of our method is that it enables
the data owner to safely delegate
the detection operation to a semi honest
provider without revealing the sensitive data to
the provider. We describe how Internet service
providers can offer their customers DLD as an
add-on service with strong privacy guarantees.
IEEE 2015

The evaluation results show that our method
can support accurate detection with very small
number of false alarms under various data-leak
scenarios.
TTA-JN-
C1559
Providing Privacy-
Aware Incentives in
Mobile Sensing
Systems
Mobile sensing relies on data contributed by
users through their mobile device (e.g., smart
phone) to obtain useful information about
people and their surroundings. However, users
may not want to contribute due to lack
of incentives and concerns on
possible privacy leakage. To effectively
promote user participation,
both incentive and privacy issues should be
addressed. Although incentive and
privacy have been addressed separately
in mobile sensing, it is still an open problem to
address them simultaneously. In this paper, we
propose two credit-based privacy-
aware incentive schemes for
mobile sensing systems, where the focus is
on privacy protection instead of on the design
of incentive mechanisms. Our schemes
enable mobile users to earn credits by
contributing data without leaking which data
they have contributed, and ensure that
malicious users cannot abuse the system to
earn unlimited credits. Specifically, the first
scheme considers scenarios where an online
trusted third party (TTP) is available, and
relies on the TTP to protect user privacy and
prevent abuse attacks. The second scheme
considers scenarios where no online TTP is
available. It applies blind signature, partially
blind signature, and a novel extended Merkle
tree technique to protect user privacy and
prevent abuse attacks. Security analysis and
cost evaluations show that our schemes are
secure and efficient.
IEEE 2015
TTA-JN-
C1560
Response Time Based
Optimal Web Service
Selection
Selecting an optimal web service among a list
of functionally equivalent web services still
remains a challenging issue. For
Internet services, the presence of low-
performance servers, high latency or overall
poor service quality can translate into lost
IEEE 2015

sales, user frustration, and customers lost. In
this paper, we propose a novel method for QoS
metrification based on Hidden Markov Models
(HMM), which further suggests
an optimal path for the execution of user
requests. The technique we show can be used
to measure and predict the behavior
of Web Services in terms of response time, and
can thus be used to rank services quantitatively
rather than just qualitatively. We demonstrate
the feasibility and usefulness of our
methodology by drawing experiments on real
world data. The results have shown how our
proposed method can help the user to
automatically select the most
reliable Web Servicetaking into account
several metrics, among them, system
predictability and response time variability.
Later ROC curve shows a 12 percent
improvement in prediction accuracy using
HMM.
TTA-JN-
C1561
Robust cloud
management of MANET
checkpoint sessions
In a traditional mobile ad-hoc network
(MANET), if two nodes are engaged in
a session and one of them departs suddenly,
their communication is aborted. The session is
not active any more, work is lost and,
consequently, the energy of the batteries has
been wasted. This paper proposes a model that
uses a cloud service to register, save, pause
and
resume sessions between MANET member
nodes so that both work in progress and energy
are saved. A checkpoint technique is
introduced to capture the progress of
a session and allow it to be resumed. This is an
additional service to our cloud management of
the MANET. The model proposed in this paper
was tested on Android-based devices and an
Amazon cloud instance. Experimental results
show that the model is feasible, robust, saves
time and, more importantly, energy
if session breaks occur frequently.
IEEE 2015

TTA-JN-
C1562
Secure Anonymous Key
Distribution Scheme for
Smart Grid
To fully support information management
among various stakeholders
in smart grid domains, how to
establish secure communication sessions has
become an important issue
for smart grid environments. In order to
support secure communications
between smart meters and service
providers, key management for authentication
becomes a crucial security topic. Recently,
several key distribution schemes have been
proposed to provide secure communications
for smart grid. However, these schemes do not
support smart meter anonymity and possess
security weaknesses. This paper utilizes an
identity-based signature scheme and an
identity-based encryption scheme to propose a
newanonymous key distribution scheme for sm
art grid environments. In the proposed scheme,
a smart meter can anonymously access
services provided by service providers using
one private key without the help of the trusted
anchor during authentication. In addition, the
proposed scheme requires only a few of
computation operations at the smart meter side.
Security analysis is conducted to prove the
proposed scheme is secure under random
oracle model.
IEEE 2015
TTA-JN-
C1563
Secure Data
Aggregation Technique
for Wireless Sensor
Networks in the
Presence of Collusion
Attacks
Due to limited computational power and
energy resources, aggregation of data from
multiple sensor nodes done at the aggregating
node is usually accomplished by simple
methods such as averaging. However
such aggregation is known to be highly
vulnerable to node compromising attacks.
Since WSN are usually unattended and without
tamper resistant hardware, they are highly
susceptible to such attacks. Thus, ascertaining
trustworthiness of data and reputation
of sensor nodes is crucial for WSN. As the
performance of very low power processors
dramatically improves, future aggregator nodes
will be capable of performing more
sophisticated data aggregation algorithms, thus
making WSN less vulnerable. Iterative
IEEE 2015

filtering algorithms hold great promise for
such a purpose. Such algorithms
simultaneously aggregate data from multiple
sources and provide trust assessment of these
sources, usually in a form of corresponding
weight factors assigned to data provided by
each source. In this paper we demonstrate that
several existing iterative filtering algorithms,
while significantly more robust
against collusion attacks than the simple
averaging methods, are nevertheless susceptive
to a novel sophisticated collusion attack we
introduce. To address this security issue, we
propose an improvement for iterative
filtering techniques by providing an initial
approximation for such algorithms which
makes them not only collusion robust, but also
more accurate and faster converging.
TTA-JN-
C1564
Secure Distributed
Deduplication Systems
with Improved
Reliability
Data deduplication is a technique for
eliminating duplicate copies of data, and has
been widely used in cloud storage to reduce
storage space and upload bandwidth. However,
there is only one copy for each file stored in
cloud even if such a file is owned by a huge
number of users. As a result, deduplication
system improves storage utilization while
reducing reliability. Furthermore, the challenge
of privacy for sensitive data also arises when
they are outsourced by users to cloud. Aiming
to address the above security challenges, this
paper makes the first attempt to formalize the
notion of distributed reliable
deduplication system. We propose
new distributed deduplication systems with
higher reliability in which the data chunks
are distributed across multiple cloud servers.
The security requirements of data
confidentiality and tag consistency are also
achieved by introducing a deterministic secret
sharing scheme in distributed storage systems,
instead of using convergent encryption as in
previous deduplication systems. Security
analysis demonstrates that
our deduplication systems are secure in terms
IEEE 2015

of the definitions specified in the proposed
security model. As a proof of concept, we
implement the proposed systems and
demonstrate that the incurred overhead is very
limited in realistic environments.
TTA-JN-
C1565
TEES An Efficient
Search Scheme over
Encrypted Data on
Mobile Cloud
Cloud storage provides a convenient, massive,
and scalable storage at low cost,
but data privacy is a major concern that
prevents users from storing files on
the cloud trustingly. One way of enhancing
privacy from data owner point of view is
to encrypt the files before outsourcing them
onto the cloud and decrypt the files after
downloading them. However, data encryption
is a heavy overhead for the mobile devices,
and data retrieval process incurs a complicated
communication between the data user and
cloud. Normally with limited bandwidth
capacity and limited battery life, these issues
introduce heavy overhead to computing and
communication as well as a higher power
consumption for mobile device users, which
makes
the encrypted search over mobile cloud very
challenging. In this paper, we
propose TEES (Traffic and Energy
saving Encrypted Search), a bandwidth and
energy efficient encrypted search architecture
over mobile cloud. The proposed architecture
offloads the computation from mobile devices
to the cloud, and we further optimize the
communication between the mobile clients and
the cloud. It is demonstrated that
the data privacy does not degrade when the
performance enhancement methods are
applied. Our experiments show
that TEES reduces the computation time by
23% to 46% and save the energy consumption
by 35% to 55% per file retrieval, meanwhile
the network traffics during the file retrievals
are also significantly reduced.
IEEE 2015
TTA-JN-
C1566
Transparent Real-Time
Task Scheduling on
Temporal Resource
Partitions
The Hierarchical Real-
Time Scheduling (HiRTS) technique helps
improve overall resource utilization in real-
IEEE 2015

time embedded systems. With HiRTS, a
computation resource is divided into a group
of temporal resource partitions, each of which
accommodates multiple real-time tasks.
Besides the
computationresource partitioning problem, real
-time task scheduling on resource partitions is
also a major problem of HiRTS. The
existing scheduling techniques for
dedicated resources, like schedulability tests
and utilization bounds, are unable to work
without changes
on temporal resource partitions in most cases.
In this paper, we show how to achieve
maximal transparency for task scheduling on
Regular Partitions, a type
of resource partition introduced by the
Regularity-based Resource Partition (RRP)
Model. We show that several classes of real-
time scheduling problems on a
regular partition can be transformed into
equivalent problems on a dedicated
single resource, such that comprehensive
single-resource scheduling techniques provide
optimal solutions. Furthermore, this
transformation method could be applied to
different types of real-time tasks such as
periodic tasks, sporadic tasks and a
periodic tasks.
TTA-JN-
C1567
User-Defined Privacy
Grid System for
Continuous Location-
Based Services
Location-based services (LBS) require users to
continuously report their location to a
potentially untrusted server to
obtain services based on their location, which
can expose them to privacy risks.
Unfortunately, existing privacy-preserving
techniques for LBS have several limitations,
such as requiring a fully-trusted third party,
offering limited privacy guarantees and
incurring high communication overhead. In
this paper, we propose a user-
defined privacy grid system called
dynamic grid system (DGS); the first
holistic system that fulfills four essential
requirements for privacy-preserving snapshot
and continuous LBS. (1) The system only
IEEE 2015

requires a semi-trusted third party, responsible
for carrying out simple matching operations
correctly. This semi-trusted third party does
not have any information about
a user's location. (2) Secure snapshot
and continuous location privacy is guaranteed
under our defined adversary models. (3) The
communication cost for the user does not
depend on the user's desired privacy level; it
only depends on the number of relevant points
of interest in the vicinity of the user. (4)
Although we only focus on range and k-
nearest-neighbor queries in this work,
our system can be easily extended to support
other spatial queries without changing the
algorithms run by the semi-trusted third party
and the database server, provided the required
search area of a spatial query can be abstracted
into spatial regions. Experimental results show
that our DGS is more efficient than the state-
of-the-art privacy-preserving technique
for continuous LBS.
TTA-JN-
C1568
VoteTrust Leveraging
Friend Invitation Graph
to Defend against
Social Network Sybils
Online social networks (OSNs) suffer from the
creation of fake accounts that introduce fake
product reviews, malware and spam. Existing
defenses focus on using
the social graph structure to isolate fakes.
However, our work shows that Sybils could
befriend a large number of real users,
invalidating the assumption behind social-
graph-based detection. In this paper, we
present VoteTrust, a scalable defense system
that further leverages user-level
activities. VoteTrust models
the friend invitation interactions among users
as a directed, signed graph, and uses two key
mechanisms to detect Sybilsover the graph: a
voting-based Sybil detection to find Sybils that
users vote to reject, and a Sybil community
detection to find other colluding Sybils around
identified Sybils. Through evaluating on
Renren social network, we show
that VoteTrust is able to prevent Sybils from
generating many unsolicited friend requests.
We also deploy VoteTrust in Renen, and our
IEEE 2015

real experience demonstrates
that VoteTrust can detect large-scale collusion
among Sybils.
DOMAIN : DATA MINING
TTA-DD-
C1501
CrowdOp Query
Optimization for
Declarative
Crowdsourcing
Systems
We study the query optimization problem
in declarative crowdsourcing systems. Declarat
ivecrowdsourcing is designed to hide the
complexities and relieve the user of the burden
of dealing with the crowd. The user is only
required to submit an SQL-like query and
the system takes the responsibility of
compiling the query, generating the execution
plan and evaluating in the crowd sourcing
marketplace. A given query can have many
alternative execution plans and the difference
in crowd sourcing cost between the best and
the worst plans may be several orders of
magnitude. Therefore, as in relational
database systems, query optimization is
important to crowd sourcing systems that
provide declarative query interfaces. In this
paper, we propose CROWDOP, a cost-
based query optimization approach
for declarative crowd
sourcing systems. CROWDOP considers both
cost and latency
in query optimization objectives and
generates query plans that provide a good
balance between the cost and latency. We
develop efficient algorithms in
the CROWDOP for optimizing three types
of queries: selection queries, join queries, and
complex selection-join queries. We validate
our approach via extensive experiments by
simulation as well as with the real crowd on
Amazon Mechanical Turk.
IEEE 2015
TTA-DD-
C1502
Time-Series
Classification with
COTE The Collective of
Transformation-Based
Ensembles
Recently, two ideas have been explored that
lead to more accurate algorithms for time-
series classification (TSC). First, it has been
shown that the simplest way to gain
improvement on TSC problems is to transform
into an alternative data space where
discriminatory features are more easily
IEEE 2015

Final Year IEEE Project Titles 2015

Final Year IEEE Project Titles 2015

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