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Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Jiang J.,Hohai University | Jiang J.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 5 more authors.
Journal of Computer and System Sciences | Year: 2014

Wireless Sensors Networks (WSNs) are susceptible to many security threats, and because of communication, computation and delay constraints of WSNs, traditional security mechanisms cannot be used. Trust management models have been recently suggested as an effective security mechanism for WSNs. Considerable research has been done on modeling and managing trust. In this paper, we present a detailed survey on various trust models that are geared towards WSNs. Then, we analyze various applications of trust models. They are malicious attack detection, secure routing, secure data aggregation, secure localization and secure node selection. In addition, we categorize various types of malicious attacks against trust models and analyze whether the existing trust models can resist these attacks or not. Finally, based on all the analysis and comparisons, we list several trust best practices that are essential for developing a robust trust model for WSNs.


Zhou Y.,Hohai University | Zhou Y.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Li Q.-W.,Hohai University | Li Q.-W.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 2 more authors.
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | Year: 2014

As the image enhancement algorithm of NonSubsampled Contourlet Transform (NSCT) domain has to adjust its parameters manually and can not enhance images adaptively, this paper proposes an adaptive image enhancement algorithm by combining histogram equalization with NSCT domain enhancement. The algorithm firstly performs the histogram equalization to the original low-contrast and noisy image. Then, it conducts the NSCT decomposition on the original image and the histogram equalized image to obtain the low frequency subband coefficients and a series of the high frequency directional subband coefficients. In the low frequency subband, the transform coefficient histogram of the original image is mapped to that of the equalized image. In each high frequency subband, the transform coefficient histogram of the original image is mapped to that of the equalized image after threshold denoising. Finally, the enhanced image is obtained by reconstruction of the modified NSCT coefficients. Experimental results show that the enhancement of the proposed algorithm is superior to that of classical histogram equalization method. As contrasted with Contourlet transform enhancement in two group of images, its evuluation function EMEE (Measurement of Enhanement by Entropy) values increase by 24.05%, 16.97%, 13.29% and 20.63%, respectively, which corresponds to that of NSCT non-adaptive enhancement (selecting optimal parameters manually) well. Moreover, this algorithm does not need manual adjusting parameters, and is characterized by good adaptability and practicability.


Tang Y.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Shen Y.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Jiang A.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Xu N.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 2 more authors.
Proceedings - IEEE International Symposium on Circuits and Systems | Year: 2013

Sparse representation theory has been well developed in recent years. In this paper, we consider an image denoising problem which can be efficiently solved under the framework of the sparse representation theory. The traditional image denoising methods based on the sparse representation seldom take into account the special structure of the data. As an attempt to overcome such problem, the Graph regularized K-means singular value decomposition (Graph K-SVD) algorithm is proposed with the manifold learning. The local geometrical structure of the image is considered in the sparse optimization model with the graph Laplacian. This manifold-based optimization problem is well solved in the framework of the traditional K-SVD algorithm. Since the novel strategy adds a graph regularizer to the sparse representation model in order to emphasize the correlations among image blocks, the Graph K-SVD can achieve better denoising performance than the traditional K-SVD. © 2013 IEEE.


Yan S.,Hohai University | Shan M.,Hohai University | Shan M.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing
Proceedings - 2014 IEEE Workshop on Electronics, Computer and Applications, IWECA 2014 | Year: 2014

A dual-channel detection method based on the acoustic attenuation characteristics in gas for sulfur hexafluoride concentration is presented. The difference of classical attenuation coefficients of two channels as a function of sulfur hexafluoride concentration is derived and numerically simulated. A dual-channel detection device is designed using ultrasonic transducers with specific center frequency to build up the experimental platform to verify the effectiveness of the proposed scheme experimentally. Experiments demonstrated that the dual-channel acoustic detection method is nearly linear when sulfur hexafluoride concentration changes in the mixture. © 2014 IEEE.


Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Jiang J.,Hohai University | Jiang J.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 3 more authors.
IET Information Security | Year: 2013

Owing to wireless communication's broadcast nature, wireless sensor networks (WSNs) are vulnerable to denial-ofservice (DoS) attacks. It is of great importance to design an efficient intrusion detection scheme (IDS) for WSNs. In this study, the authors propose a novel IDS based on energy prediction (IDSEP) in cluster-based WSNs. The main idea of IDSEP is to detect malicious nodes based on energy consumption of sensor nodes. Sensor nodes with abnormal energy consumption are identified as malicious ones. Furthermore, IDSEP is designed to differentiate categories of ongoing DoS attacks based on energy consumption thresholds. The simulation results show that IDSEP detects and recognises malicious nodes effectively. © The Institution of Engineering and Technology 2013.


Zhu C.,Hohai University | Zhu C.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Zheng C.,Hohai University | Shu L.,Osaka University | And 2 more authors.
Journal of Network and Computer Applications | Year: 2012

A wireless sensor network (WSN) is composed of a group of small power-constrained nodes with functions of sensing and communication, which can be scattered over a vast region for the purpose of detecting or monitoring some special events. The first challenge encountered in WSNs is how to cover a monitoring region perfectly. Coverage and connectivity are two of the most fundamental issues in WSNs, which have a great impact on the performance of WSNs. Optimized deployment strategy, sleep scheduling mechanism, and coverage radius cannot only reduce cost, but also extend the network lifetime. In this paper, we classify the coverage problem from different angles, describe the evaluation metrics of coverage control algorithms, analyze the relationship between coverage and connectivity, compare typical simulation tools, and discuss research challenges and existing problems in this area. © 2011 Elsevier Ltd. All rights reserved.


Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Jiang J.,Hohai University | Jiang J.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 3 more authors.
Sensors | Year: 2012

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes' mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs. © 2012 by the authors.


Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Xu H.,Hohai University | Xu H.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 5 more authors.
Wireless Communications and Mobile Computing | Year: 2013

In wireless sensor networks (WSNs), many applications require sensor nodes to obtain their locations. Now, the main idea in most existing localization algorithms has been that a mobile anchor node (e.g., global positioning system-equipped nodes) broadcasts its coordinates to help other unknown nodes to localize themselves while moving according to a specified trajectory. This method not only reduces the cost of WSNs but also gets high localization accuracy. In this case, a basic problem is that the path planning of the mobile anchor node should move along the trajectory to minimize the localization error and to localize the unknown nodes. In this paper, we propose a Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) in WSNs. LMAT algorithm uses a mobile anchor node to move according to trilateration trajectory in deployment area and broadcasts its current position periodically. Simulation results show that the performance of our LMAT algorithm is better than that of other similar algorithms. © 2011 John Wiley & Sons, Ltd.


Shen W.,Hohai University | Shen W.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | And 3 more authors.
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering | Year: 2012

Wireless Sensor Networks (WSNs) require an efficient intrusion detection scheme to identify malicious attackers. Traditional detection schemes are not well suited for WSNs due to their higher false detection rate. In this paper, we propose a novel intrusion detection scheme based on the energy prediction in cluster-based WSNs (EPIDS). The main contribution of EPIDS is to detect attackers by comparing the energy consumptions of sensor nodes. The sensor nodes with abnormal energy consumptions are identified as malicious attackers. Furthermore, EPIDS is designed to distinguish the types of denial of service (DoS) attack according to the energy consumption rate of the malicious nodes. The primary simulation experiments prove that EPIDS can detect and recognize malicious attacks effectively. © 2012 Springer-Verlag Berlin Heidelberg.


Han G.,Hohai University | Han G.,Changzhou Key Laboratory of Sensor Networks and Environmental Sensing | Jiang J.,Hohai University | Shu L.,Osaka University | And 2 more authors.
Computer Journal | Year: 2013

Accurately locating unknown nodes is a critical issue in the study of wireless sensor networks (WSNs). Many localization approaches have been proposed based on anchor nodes, which are assumed to know their locations by manual placement or additional equipments such as global positioning system. However, none of these approaches can work properly under the adversarial scenario. In this paper, we propose a novel scheme called two-step secure localization (TSSL) stand against many typical malicious attacks, e.g. wormhole attack and location spoofing attack. TSSL detects malicious nodes step by step. First, anchor nodes collaborate with each other to identify suspicious nodes by checking their coordinates, identities and time of sending information. Then, by using a modified mesh generation scheme, malicious nodes are isolated and the WSN is divided into areas with different trust grades. Finally, a novel localization algorithm based on the arrival time difference of localization information is adopted to calculate locations of unknown nodes. Simulation results show that the TSSL detects malicious nodes effectively and the localization algorithm accomplishes localization with high localization accuracy. © 2012 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

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