http://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/SecureDataAggreg.pdf

Secure data aggregation in wireless sensor networks: A comprehensive overview

https://www.nics.uma.es/pub/papers/JavierLopezMunoz2010.pdf

Trust management systems for wireless sensor networks: Best practices

Much of the existing work on wireless sensor networks (WSNs) has focused on addressing the power and computational resource constraints of WSNs by the design of specific routing, MAC, and cross-layer protocols. Recently, there have been heightened privacy concerns over the data collected by and transmitted through WSNs. The wireless transmission required by a WSN, and the self-organizing nature of its architecture, makes privacy protection for WSNs an especially challenging problem. This paper provides a state-of-the-art survey of privacy-preserving techniques for WSNs. In particular, we review two main categories of privacy-preserving techniques for protecting two types of private information, data-oriented and context-oriented privacy, respectively. We also discuss a number of important open challenges for future research. Our hope is that this paper sheds some light on a fruitful direction of future research for privacy preservation in WSNs.

Privacy preservation in wireless sensor networks: A state-of-the-art survey

SUMMARY The range of applications of wireless sensor networks is so wide that it tends to invade our every day life. In the future, a sensor network will survey our health, our home, the roads we follow, the office or the industry we work in or even the aircrafts we use, in an attempt to enhance our safety. However, the wireless sensor networks themselves are prone to security attacks. The list of security attacks, although already very long, continues to augment impeding the expansion of these networks. The trust management schemes consist of a powerful tool for the detection of unexpected node behaviours (either faulty or malicious). Once misbehaving nodes are detected, their neighbours can use this information to avoid cooperating with them, either for data forwarding, data aggregation or any other cooperative function. A variety of trust models which follow different directions regarding the distribution of measurement functionality, the monitored behaviours and the way measurements are used to calculate/define the node’s trustworthiness has been presented in the literature. In this paper, we survey trust models in an attempt to explore the interplay among the implementation requirements, the resource consumption and the achieved security. Our goal is to draw guidelines for the design of deployable trust model designs with respect to the available node and network capabilities and application peculiarities. Copyright © 2010 John Wiley & Sons, Ltd.

Trust management in wireless sensor networks

http://www.agentgroup.ing.unimo.it/Zambonelli/PDF/PMC12.pdf

Fast track article: Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence

In unattended and hostile environments, node compromise can become a disastrous threat to wireless sensor networks and introduce uncertainty in the aggregation results. A compromised node often tends to completely reveal its secrets to the adversary which in turn renders purely cryptography-based approaches vulnerable. How to secure the information aggregation process against compromised-node attacks and quantify the uncertainty existing in the aggregation results has become an important research issue. In this paper, we address this problem by proposing a trust based framework, which is rooted in sound statistics and some other distinct and yet closely coupled techniques. The trustworthiness (reputation) of each individual sensor node is evaluated by using an information theoretic concept, Kullback-Leibler (KL) distance, to identify the compromised nodes through an unsupervised learning algorithm. Upon aggregating, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As the result is being disseminated and assembled through the routes to the sink, this opinion will be propagated and regulated by Josang's belief model. Following this model, the uncertainty within the data and aggregation results can be effectively quantified throughout the network. Simulation results demonstrate that our trust based framework provides a powerful mechanism for detecting compromised nodes and reasoning about the uncertainty in the network. It further can purge false data to accomplish robust aggregation in the presence of multiple compromised nodes

A Trust Based Framework for Secure Data Aggregation in Wireless Sensor Networks

Fast track article: Secure data aggregation in wireless sensor networks: A watermark based authentication supportive approach

Security in Wireless Sensor Networks: A Survey

In-network processing presents a critical challenge for data authentication in wireless sensor networks (WSNs). Current schemes relying on message authentication code (MAC) cannot provide natural support for this operation since even a slight modification to the data invalidates the MAC. In this paper, based on digital watermarking, we propose an end-to-end approach for data authentication in WSNs that provides inherent support for in-network processing. In this scheme, authentication information is modulated as watermark and superposed to the sensory data at the sensor nodes. The watermarked data can be aggregated by the intermediate nodes without incurring any en-route checking. Upon reception of the sensory data, possibly distorted by the operations along the route, the data sink is able to authenticate the data by validating the watermark, detecting whether the data has been altered and where it has occurred. In this way, the aggregation-survivable authentication information is only added at the sources and checked by the data sink, without any involvement of intermediate nodes. Furthermore, the simple operation of watermark embedding and complex operation of watermark detection provide a natural solution of function partitioning between the resource limited sensor nodes and resource abundant data sink. The simulation results show that the proposed scheme can successfully authenticate the sensory data with high confidence.

Aggregation Supportive Authentication in Wireless Sensor Networks: A Watermark Based Approach

Reducing delay has an important position in the data collection of wireless sensor networks. Current mobile sink may use single antenna to collect data, but necessarily use two antennas if the data amount is large. The purpose of the research is to reduce the delay of data collection. Unlike many traditional methods, our approach has not parking positions of mobile sink in the process of data collection. We propose an algorithm based on speed control of mobile sink that reduces the delay of data collection. The algorithm combines speed control and two antennas of mobile sink. Our algorithm ensures reducing the delay of data collection.

Wei Zhang

Papers

A Trust Based Framework for Secure Data Aggregation in Wireless Sensor Networks

Fast track article: Secure data aggregation in wireless sensor networks: A watermark based authentication supportive approach

Security in Wireless Sensor Networks: A Survey

Aggregation Supportive Authentication in Wireless Sensor Networks: A Watermark Based Approach

Mobile data collection of wireless sensor networks with speed control