1,537 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
Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks
This chapter discusses the need of security and privacy protection mechanisms
in aggregation protocols used in wireless sensor networks (WSN). It presents a
comprehensive state of the art discussion on the various privacy protection
mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed
by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA
protocol and proposes a mechanism to plug that vulnerability. To demonstrate
the need of security in aggregation process, the chapter further presents
various threats in WSN aggregation mechanisms. A large number of existing
protocols for secure aggregation in WSN are discussed briefly and a protocol is
proposed for secure aggregation which can detect false data injected by
malicious nodes in a WSN. The performance of the protocol is also presented.
The chapter concludes while highlighting some future directions of research in
secure data aggregation in WSNs.Comment: 32 pages, 7 figures, 3 table
Energy efficient privacy preserved data gathering in wireless sensor networks having multiple sinks
Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-tomany structures are evolved due to need for conveying collected event information to multiple sinks at the same time. This study proposes an anonymity method bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify of an event owner, are generalized or encrypted in order to
meet the different anonymity requirements of sinks. Privacy guaranteed event information can be multicasted to all sinks instead of sending to each sink one by one. Since minimization of energy consumption is an important design criteria for WSNs, our method enables us to multicast the same event information
to multiple sinks and reduce energy consumption
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
An Enhanced Source Location Privacy based on Data Dissemination in Wireless Sensor Networks (DeLP)
open access articleWireless Sensor Network is a network of large number of nodes with limited power and computational capabilities. It has the potential of event monitoring in unattended locations where there is a chance of unauthorized access. The work that is presented here identifies and addresses the problem of eavesdropping in the exposed environment of the sensor network, which makes it easy for the adversary to trace the packets to find the originator source node, hence compromising the contextual privacy. Our scheme provides an enhanced three-level security system for source location privacy. The base station is at the center of square grid of four quadrants and it is surrounded by a ring of flooding nodes, which act as a first step in confusing the adversary. The fake node is deployed in the opposite quadrant of actual source and start reporting base station. The selection of phantom node using our algorithm in another quadrant provides the third level of confusion. The results show that Dissemination in Wireless Sensor Networks (DeLP) has reduced the energy utilization by 50% percent, increased the safety period by 26%, while providing a six times more packet delivery ratio along with a further 15% decrease in the packet delivery delay as compared to the tree-based scheme. It also provides 334% more safety period than the phantom routing, while it lags behind in other parameters due to the simplicity of phantom scheme. This work illustrates the privacy protection of the source node and the designed procedure may be useful in designing more robust algorithms for location privac
Privacy models in wireless sensor networks: a survey
Wireless Sensor Networks (WSNs) are attracting attention from the research community. One of the key issues is to provide them with privacy protection. In recent years, a huge amount of contributions has been focused on this area. Surveys and literature reviews have also been produced to give a systematic view of the different approaches taken. However, no previous work has focused on privacy models, that is, the set of assumptions made to build the approach. In particular, this paper focuses on this matter by studying 41 papers of the last 5 years. We highlight the great differences appearing among related papers that could make them incompatible to be applied simultaneously. We propose a set of guidelines to build comprehensive privacy models so as to foster their comparability and suitability analysis for different scenarios.This work was supported by the MINECO Grant TIN2013-46469-R (Security and Privacy in the Internet of You (SPINY)) and the CAM Grant S2013/ICE-3095 (Cybersecurity,Data, and Risks (CIBERDINE)), which is cofunded by EuropeanFunds (FEDER). Furthermore, J.M. de Fuentes and L. González-Manzano were also partially supported by the Programa de Ayudas a la Movilidad of Carlos III University of Madrid
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