Secure data aggregation without persistent cryptographic operations in wireless sensor networks

In-network data aggregation is an essential operation to reduce energy consumption in large-scale wireless sensor networks. With data aggregation, however, raw data items are invisible to the base station and thus the authenticity of the aggregated data is hard to guarantee. A compromised sensor node may forge an aggregation value and mislead the base station into trusting a false reading. Due to the stringent constraints of energy supply and computing capability on sensor nodes, it is challenging to detect a compromised sensor node and keep it from cheating, since expensive cryptographic operations are unsuitable for tiny sensor devices. This paper proposes a secure aggregation tree (SAT) to detect and prevent cheating. Our method is essentially different from other existing solutions in that it does not require any cryptographic operations when all sensor nodes work honestly. The detection of cheating is based on the topological constraints in the aggregation tree. We also propose a weighted voting scheme to determine a misbehaving node and a secure local recovery scheme to avoid using the misbehaving node.     

Secure median computation in wireless sensor networks

Wireless sensor networks (WSNs) have proven to be useful in many applications, such as military surveillance and environment monitoring. To meet the severe energy constraints in WSNs, several researchers have proposed to use the in-network data aggregation technique (i.e., combining partial results at intermediate nodes during message routing), which significantly reduces the communication overhead. Given the lack of hardware support for tamper-resistance and the unattended nature of sensor nodes, sensor network protocols need to be designed with security in mind. Recently, researchers proposed algorithms for securely computing a few aggregates, such as Sum (the sum of the sensed values), Count (number of nodes) and Average. However, to the best of our knowledge, there is no prior work which securely computes the Median, although the Median is considered to be an important aggregate. The contribution of this paper is twofold. We first propose a protocol to compute an approximate Median and verify if it has been falsified by an adversary. Then, we design an attack-resilient algorithm to compute the Median even in the presence of a few compromised nodes. We evaluate the performance and cost of our approach via both analysis and simulation. Our results show that our approach is scalable and efficient.     

Non-intrusive aggregation in wireless sensor networks

Since energy is scarce in sensor nodes, wireless sensor networks aim to transmit as few packets as possible. To achieve this goal, sensor protocols often aggregate measured data from multiple sensor nodes into a single packet. In this paper, a survey of aggregation techniques and methods is given. Based on this survey, it is concluded that there are currently several dependencies between the aggregation method and the behavior of the other network layers. As a result, existing aggregation methods can often not be combined with different routing protocols. To remedy this shortcoming, the paper introduces a new ‘non-intrusive’ aggregation approach which is independent of the routing protocol. The proposed aggregation method is evaluated and compared to traditional aggregation approaches using a large-scale sensor testbed of 200 TMoteSky sensor nodes. Our experimental results indicate that existing aggregation approaches are only suited for a limited set of network scenarios. In addition, it is shown both mathematically and experimentally that our approach outperforms existing non-intrusive techniques in a wide range of scenarios.     

基于分簇的无线传感器网络安全路由协议研究

无线传感器网络（Wireless Sensor Networks,简称WSNs）作为一种新的获取信息的方式和处理模式,已成为通信领域的研究重点。而路由协议则是无线传感器网络当前的热点研究之一。目前,针对较为典型的分簇式路由协议LEACH路由协议的研究,是无线传感器网络目前研究的一个热点。介绍了无线传感器网络路由协议常见的攻击类型,并从路由安全的角度建议性的提出了一种对LEACH路由协议针对安全性的改进方案,并应用NS2仿真平台,对改进协议做了仿真并进行了性能分析。     

Efficient clustering-based data aggregation techniques for wireless sensor networks

In wireless sensor network applications for surveillance and reconnaissance, large amounts of redundant sensing data are frequently generated. It is important to control these data with efficient data aggregation techniques to reduce energy consumption in the network. Several clustering methods were utilized in previous works to aggregate large amounts of data produced from sensors in target tracking applications (Park in A dissertation for Doctoral in North Carolina State University, 2006). However, such data aggregation algorithms show effectiveness only in restricted environments, while posing great problems when adapting to other various situations. To alleviate these problems, we propose two hybrid clustering based data aggregation mechanisms. The combined clustering-based data aggregation mechanism can apply multiple clustering techniques simultaneously in a single network depending on the network environment. The adaptive clustering-based data aggregation mechanism can adaptively choose a suitable clustering technique, depending on the status of the network. The proposed mechanisms can increase the data aggregation efficiency as well as improve energy efficiency and other important issues compared to previous works. Performance evaluation via mathematical analysis and simulation has been made to show the effectiveness of the proposed mechanisms.     

Q-learning based routing for in-network aggregation in wireless sensor networks

Wireless Networks - In-network data aggregation is an inherent paradigm that extends the lifetime of resource-constrained wireless sensor networks (WSNs). By aggregating sensor data at...     

In-network aggregation techniques for wireless sensor networks: a survey

In this article we provide a comprehensive review of the existing literature on techniques and protocols for in-network aggregation in wireless sensor networks. We first define suitable criteria to classify existing solutions, and then describe them by separately addressing the different layers of the protocol stack while highlighting the role of a cross-layer design approach, which is likely to be needed for optimal performance. Throughout the article we identify and discuss open issues, and propose directions for future research in the area     

Secure probabilistic location verification in randomly deployed wireless sensor networks

Security plays an important role in the ability to deploy and retrieve trustworthy data from a wireless sensor network. Location verification is an effective defense against attacks which take advantage of a lack, or compromise, of location information. In this work, a secure probabilistic location verification method for randomly deployed dense sensor networks is proposed. The proposed Probabilistic Location Verification (PLV) algorithm leverages the probabilistic dependence of the number of hops a broadcast packet traverses to reach a destination and the Euclidean distance between the source and the destination. A small number of verifier nodes are used to determine the plausibility of the claimed location, which is represented by a real number between zero and one. Using the calculated plausibility metric, it is possible to create arbitrary number of trust levels in the location claimed. Simulation studies verify that the proposed solution provides high performance in face of various types of attacks.     

Secure K-Nearest neighbor queries in two-tiered mobile wireless sensor networks

Tiered Mobile Wireless Sensor Network(TMWSN) is a new paradigm introduced by mobile edge computing. Now it has received wide attention because of its high scalability, robustness, deployment flexibility, and it has a wide range of application scenarios. In TMWSNs, the storage nodes are the key nodes of the network and are more easily captured and utilized by attackers. Once the storage nodes are captured by the attackers, the data stored on them will be exposed. Moreover, the query process and results will not be trusted any more. This paper mainly studies the secure KNN query technology in TMWSNs, and we propose a secure KNN query algorithm named the Basic Algorithm For Secure KNN Query(BAFSKQ) first, which can protect privacy and verify the integrity of query results. However, this algorithm has a large communication overhead in most cases. In order to solve this problem, we propose an improved algorithm named the Secure KNN Query Algorithm Based on MR-Tree(SEKQAM). The MR-Trees are used to find the K-nearest locations and help to generate a verification set to process the verification of query results. It can be proved that our algorithms can effectively guarantee the privacy of the data stored on the storage nodes and the integrity of the query results. Our experimental results also show that after introducing the MR-Trees in KNN queries on TMWSNs, the communication overhead has an effective reduction compared to BAFSKQ.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

Break-and-join tree construction for latency-aware data aggregation in wireless sensor networks

Wireless Networks - Emerging applications require processing a huge amount of environmental data from wireless sensor networks, and then triggering appropriate actions in response to the detected...     

Opportunistic routing with in-network aggregation for asynchronous duty-cycled wireless sensor networks

We propose an opportunistic routing protocol for wireless sensor networks designed to work on top of an asynchronous duty-cycled MAC. Opportunistic routing can be very effective when used with asynchronous duty-cycled MAC because expected waiting time of senders—when they stay on active mode and transmit packet streams—is significantly reduced. If there are multiple sources, energy consumption can be reduced further through in-network aggregation. The idea proposed in this paper is to temporarily increase duty cycle ratio of nodes holding packets, in order to increase chance of in-network aggregation and thus reduce energy consumption and extend network lifetime. In the proposed protocol called opportunistic routing with in-network aggregation (ORIA), whenever a node generates a packet or receives a packet to forward, it waits for a certain amount of time before transmitting the packet. Meanwhile, the node increases its duty cycle ratio, hoping that it receives packets from other nodes and aggregate them into a single packet. Simulation results show that ORIA saves considerable amount of energy compared to general opportunistic routing protocols, as well as tree-based protocols.     

A hierarchical energy-efficient framework for data aggregation in wireless sensor networks

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called "aggregators." Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments.     

A time efficient aggregation convergecast scheduling algorithm for wireless sensor networks

Wireless Networks - We investigated the aggregation convergecast scheduling problem in wireless sensor networks. In order to reduce the time needed for data collection through aggregation...     

An adaptive-weighted two-dimensional data aggregation algorithm for clustered wireless sensor networks

In this paper, an Adaptive-Weighted Time-Dimensional and Space-Dimensional （AWTDSD） data aggregation algorithm for a clustered sensor network is proposed for prolonging the lifetime of the network as well as improving the accuracy of the data gathered in the network. AWTDSD contains three phases： （1） the time-dimensional aggregation phase for eliminating the data redundancy; （2） the adaptive-weighted aggregation phase for further aggregating the data as well as improving the accuracy of the aggregated data; and （3） the space-dimensional aggregation phase for reducing the size and the amount of the data transmission to the base station. AWTDSD utilizes the correlations between the sensed data for reducing the data transmission and increasing the data accuracy as well. Experimental result shows that AWTDSD can not only save almost a half of the total energy consumption but also greatly increase the accuracy of the data monitored by the sensors in the clustered network.     

无线传感器网络中的安全GEAR路由协议

GEAR路由是无线传感器网络中一种高效的位置和能量感知的地理路由协议，在抵御路由攻击方面有较好的特性，但是GEAR路由不能抵御虚假路由、女巫、选择性转发等攻击。针对该问题，提出了一种适合无线传感器网络特征的、基于位置密钥对引导模型的安全GEAR路由协议SGEAR，并对该协议进行了性能分析，分析显示在较小的系统开销下，SGEAR能有效抑制上述攻击及DoS攻击。     

低能耗和低时延的无线传感器网络数据融合算法

针对无线传感器网络的节点能量有限,且在进行信息传输时存在数据冲突、传输延时等问题,提出并设计了基于最大生存周期的无线传感器网络数据融合算法。该算法将整个网络中的节点分成多个簇,并根据节点的传输范围,将每个簇中的节点均匀分布,每个节点根据自己的本地信息和剩余能量选择通信方式向簇头节点传输数据,从而形成传输数据的最短路径;并根据集中式TDMA(时分多址)调度模型,运用基于微粒群的Pareto优化方法,使得网络在完成规定的信息传输时每个节点耗费的平均时隙和平均能耗最优。仿真结果表明,上述算法不但可以最大化网络的生存时间,还可以有效的降低数据融合时间,减少网络延时。     

Design guidelines for wireless sensor networks: communication, clustering and aggregation

When sensor nodes are organized in clusters, they could use either single hop or multi-hop mode of communication to send their data to their respective cluster heads. We present a systematic cost-based analysis of both the modes, and provide results that could serve as guidelines to decide which mode should be used for given settings. We determine closed form expressions for the required number of cluster heads and the required battery energy of nodes for both the modes. We also propose a hybrid communication mode which is a combination of single hop and multi-hop modes, and which is more cost-effective than either of the two modes. Our problem formulation also allows for the application to be taken into account in the overall design problem through a data aggregation model.     

Near optimal scheduling of data aggregation in wireless sensor networks

Due to the large-scale ad hoc deployments and wireless interference, data aggregation is a fundamental but time consuming task in wireless sensor networks. This paper focuses on the latency of data aggregation. Previously, it has been proved that the problem of minimizing the latency of data aggregation is NP-hard [1]. Many approximate algorithms have been proposed to address this issue. Using maximum independent set and first-fit algorithms, in this study we design a scheduling algorithm, Peony-tree-based Data Aggregation (PDA), which has a latency bound of 15R + Δ ? 15, where R is the network radius (measured in hops) and Δ is the maximum node degree. We theoretically analyze the performance of PDA based on different network models, and further evaluate it through extensive simulations. Both the analytical and simulation results demonstrate the advantages of PDA over the state-of-art algorithm in [2], which has a latency bound of 23R + Δ ? 18.