11,828 research outputs found
A Survey on Wireless Sensor Network Security
Wireless sensor networks (WSNs) have recently attracted a lot of interest in
the research community due their wide range of applications. Due to distributed
nature of these networks and their deployment in remote areas, these networks
are vulnerable to numerous security threats that can adversely affect their
proper functioning. This problem is more critical if the network is deployed
for some mission-critical applications such as in a tactical battlefield.
Random failure of nodes is also very likely in real-life deployment scenarios.
Due to resource constraints in the sensor nodes, traditional security
mechanisms with large overhead of computation and communication are infeasible
in WSNs. Security in sensor networks is, therefore, a particularly challenging
task. This paper discusses the current state of the art in security mechanisms
for WSNs. Various types of attacks are discussed and their countermeasures
presented. A brief discussion on the future direction of research in WSN
security is also included.Comment: 24 pages, 4 figures, 2 table
Decentralized sequential change detection using physical layer fusion
The problem of decentralized sequential detection with conditionally
independent observations is studied. The sensors form a star topology with a
central node called fusion center as the hub. The sensors make noisy
observations of a parameter that changes from an initial state to a final state
at a random time where the random change time has a geometric distribution. The
sensors amplify and forward the observations over a wireless Gaussian multiple
access channel and operate under either a power constraint or an energy
constraint. The optimal transmission strategy at each stage is shown to be the
one that maximizes a certain Ali-Silvey distance between the distributions for
the hypotheses before and after the change. Simulations demonstrate that the
proposed analog technique has lower detection delays when compared with
existing schemes. Simulations further demonstrate that the energy-constrained
formulation enables better use of the total available energy than the
power-constrained formulation in the change detection problem.Comment: 10 pages, two-column, 10 figures, revised based on feedback from
reviewers, accepted for publication in IEEE Trans. on Wireless Communication
Data Transmission with Reduced Delay for Distributed Acoustic Sensors
This paper proposes a channel access control scheme fit to dense acoustic
sensor nodes in a sensor network. In the considered scenario, multiple acoustic
sensor nodes within communication range of a cluster head are grouped into
clusters. Acoustic sensor nodes in a cluster detect acoustic signals and
convert them into electric signals (packets). Detection by acoustic sensors can
be executed periodically or randomly and random detection by acoustic sensors
is event driven. As a result, each acoustic sensor generates their packets
(50bytes each) periodically or randomly over short time intervals
(400ms~4seconds) and transmits directly to a cluster head (coordinator node).
Our approach proposes to use a slotted carrier sense multiple access. All
acoustic sensor nodes in a cluster are allocated to time slots and the number
of allocated sensor nodes to each time slot is uniform. All sensor nodes
allocated to a time slot listen for packet transmission from the beginning of
the time slot for a duration proportional to their priority. The first node
that detect the channel to be free for its whole window is allowed to transmit.
The order of packet transmissions with the acoustic sensor nodes in the time
slot is autonomously adjusted according to the history of packet transmissions
in the time slot. In simulations, performances of the proposed scheme are
demonstrated by the comparisons with other low rate wireless channel access
schemes.Comment: Accepted to IJDSN, final preprinted versio
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
Resilient networking in wireless sensor networks
This report deals with security in wireless sensor networks (WSNs),
especially in network layer. Multiple secure routing protocols have been
proposed in the literature. However, they often use the cryptography to secure
routing functionalities. The cryptography alone is not enough to defend against
multiple attacks due to the node compromise. Therefore, we need more
algorithmic solutions. In this report, we focus on the behavior of routing
protocols to determine which properties make them more resilient to attacks.
Our aim is to find some answers to the following questions. Are there any
existing protocols, not designed initially for security, but which already
contain some inherently resilient properties against attacks under which some
portion of the network nodes is compromised? If yes, which specific behaviors
are making these protocols more resilient? We propose in this report an
overview of security strategies for WSNs in general, including existing attacks
and defensive measures. In this report we focus at the network layer in
particular, and an analysis of the behavior of four particular routing
protocols is provided to determine their inherent resiliency to insider
attacks. The protocols considered are: Dynamic Source Routing (DSR),
Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing
(RWR)
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