Range-free 3D node localization in anisotropic wireless sensor networks

In this paper, we propose two computationally efficient ‘range-free’ 3D node localization schemes using the application of hybrid-particle swarm optimization (HPSO) and biogeography based optimization (BBO). It is considered that nodes are deployed with constraints over three layer boundaries, in an anisotropic environment. The anchor nodes are randomly distributed over the top layer only and target nodes distributed over the middle and bottom layers. Radio irregularity factor, i.e., an anisotropic property of propagation media and heterogenous properties of the devices are considered. To overcome the non-linearity between received signal strength (RSS) and distance, edge weights between each target node and neighboring anchor nodes have been considered to compute the location of the target node. These edge weights are modeled using fuzzy logic system (FLS) to reduce the computational complexity. The edge weights are further optimized by HPSO and BBO separately to minimize the location error. Both the proposed applications of the two algorithms are compared with the earlier proposed range-free algorithms in literature, i.e., the simple centroid method and weighted centroid method. The results of our proposed applications of the two algorithms are better as compared to centroid and weighted centroid methods in terms of error and scalability.     

Evaluation of Localization Attacks on Power-Modulated Challenge–Response Systems

Location information should be verifiable in order to support new computing and information services. In this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. Our scheme utilizes a collection of transmitters, and adapts the power allocations across these transmitters to verify a user's claimed location. This strategy, which we call a power-modulated challenge response, is able to be used with existing. wireless sensor networks. First, we propose a direct method, where some transmitters are selected to send ldquochallengesrdquo that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond to in order to prove its location. Second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. Then, we present a signal-strength-based method, where the node responds with its received signal strength and thereby provides improved location verification. To evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models. Further, we propose a new localization attack, where a set of nodes collaborates to pretend that there is a node at the claimed location. This collusion attack can do tremendous harm to localization and the performance of the aforementined methods under collusion attack are explained. Finally, we propose the use of a rotational directional power-modulated challenge response, where directional antennas are used to defend against collusion attacks.     

LAD: Localization anomaly detection for wireless sensor networks

In wireless sensor networks (WSNs), sensors’ locations play a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery (localization) schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the reference information provided by these beacon nodes. Most of the beacon-based localization schemes assume a benign environment, where all beacon nodes are supposed to provide correct reference information. However, when the sensor networks are deployed in a hostile environment, where beacon nodes can be compromised, such an assumption does not hold anymore. In this paper, we propose a general scheme to detect localization anomalies that are caused by adversaries. Our scheme is independent from the localization schemes. We formulate the problem as an anomaly intrusion detection problem, and we propose a number of ways to detect localization anomalies. We have conducted simulations to evaluate the performance of our scheme, including the false positive rates, the detection rates, and the resilience to node compromises.     

A soft computing approach to localization in wireless sensor networks

In this paper, we propose two intelligent localization schemes for wireless sensor networks (WSNs). The two schemes introduced in this paper exhibit range-free localization, which utilize the received signal strength (RSS) from the anchor nodes. Soft computing plays a crucial role in both schemes. In the first scheme, we consider the edge weight of each anchor node separately and combine them to compute the location of sensor nodes. The edge weights are modeled by the fuzzy logic system (FLS) and optimized by the genetic algorithm (GA). In the second scheme, we consider the localization as a single problem and approximate the entire sensor location mapping from the anchor node signals by a neural network (NN). The simulation and experimental results demonstrate the effectiveness of the proposed schemes by comparing them with the previous methods.     

Secure localization and location verification in wireless sensor networks: a survey

The locations of sensor nodes are very important to many wireless sensor networks (WSNs). When WSNs are deployed in hostile environments, two issues about sensors’ locations need to be considered. First, attackers may attack the localization process to make estimated locations incorrect. Second, since sensor nodes may be compromised, the base station (BS) may not trust the locations reported by sensor nodes. Researchers have proposed two techniques, secure localization and location verification, to solve these two issues, respectively. In this paper, we present a survey of current work on both secure localization and location verification. We first describe the attacks against localization and location verification, and then we classify and describe existing solutions. We also implement typical secure localization algorithms of one popular category and study their performance by simulations.     

基于格的可验证秘密共享方案

可验证秘密共享是密码学领域中的一项重要分支.以往可验证秘密共享方案的有效性通常是基于离散对数的数学难题,然而离散对数问题已经被证明在量子计算模型下是不安全的.因此,需要借助格难题去实现可以抵抗量子攻击的可验证秘密共享方案.本文分析现有的可验证秘密共享方案,针对现有方案计算效率低和无法抵御量子攻击的缺陷,利用格密码学中的数学难题,提出一种新的可验证秘密共享方案.该方案相对于以往的可验证秘密共享方案,具有更高的计算效率和抗量子攻击的特性.     

基于改进的DV-Hop算法的无线传感器网络的研究

针对基本的DV-Hop节点定位算法会产生不良的节点和多级跳带来的累积误差的缺点,提出的一种改进的DV-Hop算法,这种算能够节省附加节点的硬件开销进而能达到准确的定位。改进以后的算法的定位误差率明显比改进前的定位误差率小,表明了定位误差率随锚节点数量的增加而减小。通过MATLAB软件对节点定位误差方面进行仿真验证,仿真实验结果证明该改进后的算法稳定、可靠,易于实现,提高了定位精确度、改善了网络覆盖率,达到了预期的目标。     

基于多指纹联合匹配的混合定位算法

随着信息科技的迅猛发展,室内定位技术已经成为基于位置服务LBS的研究热点之一。基于接收信号强度RSS的位置指纹与步行者航位推算PDR相结合的定位算法能有效提高定位精度,但目前已有的算法难以同时满足较高的定位精度与较小的计算量,常见的卡尔曼滤波算法精度不够,而粒子滤波算法计算量较大。提出了一种基于多指纹联合匹配的混合定位算法,有效融合惯性信息与RSS指纹信息,在较低计算量的前提下实现了高精度定位。实验结果表明,该算法80%的定位精度低于1m,平均精度高达0.77m。     

ServLoc:无线传感反应网络的安全位置服务机制

为解决无线传感反应网络的安全位置服务问题,提出了一种距离无关的安全定位协议--ServLoc定位协议.在该协议中,反应器通过认证消息包、被动接收定位请求、过滤虚假信息等方法进行位置攻击防御,位置匿名和分布地确定传感器节点位置.另外也提出了一种基于表决的位置校验协议--ServLoc校验协议,并对反应器攻击的防御方法进行了初步探讨.分析说明,该协议能够有效地平衡位置欺骗攻击的成功率和定位失效率,并在网络遭受位置攻击时,仍能有效地完成安全位置服务.     

A robust localization algorithm in wireless sensor networks

Most of the state-of-the-art localization algorithms in wireless sensor networks (WSNs) are vulnerable to various kinds of location attacks, whereas secure localization schemes proposed so far are too complex to apply to power constrainedWSNs. This paper provides a distributed robust localization algorithm called Bilateration that employs a unified way to deal with all kinds of location attacks as well as other kinds of information distortion caused by node malfunction or abnormal environmental noise. Bilateration directly calculates two candidate positions for every two heard anchors, and then uses the average of a maximum set of close-by candidate positions as the location estimation. The basic idea behind Bilateration is that candidate positions calculated from reasonable (i.e., error bounded) anchor positions and distance measurements tend to be close to each other, whereas candidate positions calculated from false anchor positions or distance measurements are highly unlikely to be close to each other if false information are not collaborated. By using ilateration instead of classical multilateration to compute location estimation, Bilateration requires much lower computational complexity, yet still retains the same localization accuracy. This paper also evaluates and compares Bilateration with three multilateration-based localization algorithms, and the simulation results show that Bilateration achieves the best comprehensive performance and is more suitable to real wireless sensor networks.     

A robust localization algorithm in wireless sensor networks

Most of the state-of-the-art localization algorithms in wireless sensor networks (WSNs) are vulnerable to various kinds of location attacks, whereas secure localization schemes proposed so far are too complex to apply to power constrained WSNs. This paper provides a distributed robust localization algorithm called Bilateration that employs a unified way to deal with all kinds of location attacks as well as other kinds of information distortion caused by node malfunction or abnormal environmental noise. Bilateration directly calculates two candidate positions for every two heard anchors, and then uses the average of a maximum set of close-by candidate positions as the location estimation. The basic idea behind Bilateration is that candidate positions calculated from reasonable (i.e., error bounded) anchor positions and distance measurements tend to be close to each other, whereas candidate positions calculated from false anchor positions or distance measurements are highly unlikely to be close to each other if false information are not collaborated. By using ilateration instead of classical multilateration to compute location estimation, Bilateration requires much lower computational complexity, yet still retains the same localization accuracy. This paper also evaluates and compares Bilateration with three multilateration-based localization algorithms, and the simulation results show that Bilateration achieves the best comprehensive performance and is more suitable to real wireless sensor networks.     

On the use of limited autonomous mobility for dynamic coverage maintenance in sensor networks

Sensor networks consist of small wireless sensor nodes deployed randomly over an area to monitor the environment or detect intrusion. The coverage provided by sensor networks is very crucial to their effectiveness. Many of the important applications of sensor networks demand autonomous mobility for the sensor nodes. Early failure of sensor nodes can lead to coverage loss that requires coverage maintenance schemes. In this paper, we propose Dynamic Coverage Maintenance (DCM) schemes that exploit the limited mobility of the sensor nodes. The main objective of coverage maintenance is to compensate the loss of coverage with minimum expenditure of energy. Existing autonomous sensor deployment schemes such as the “potential field approach” are not useful for DCM because the nodes initially distribute themselves such that there is no redundancy in coverage. We propose a set of DCM schemes which can be executed on individual sensor nodes having a knowledge of only their local neighborhood topology. The process of moving a node to a new location for maintenance of coverage is termed “migration”. We propose four algorithms to decide which neighbors to migrate, and to what distance, such that the energy expended is minimized and the coverage obtained for a given number of live nodes is maximized. The decision and movement are completely autonomous in the network, and involves movement of one-hop neighbors of a dead sensor node. We also propose an extension to these algorithms, called Cascaded DCM, which extends the migrations to multiple hops. We have developed a graphical simulator Java Sensor Simulator (JSS) to visually inspect the working of the algorithms. We have also compared the performance of the different algorithms in terms of the improvement in coverage, average migration distance of the nodes, and the lifetime of the network. Cascaded DCM was seen to offer the maximum network lifetime and coverage.     

基于改进的RSSI无线传感器网络节点定位算法研究

研究无线传感器网络节点定位问题。接收信号强度值(RSSI)直接影响无线传感器网络节点定位准确度,而现有定位算法没有考虑锚节点的RSSI消息,造成节点定位精度低。为了提高无线传感器网络节点的定位精度,提出了一种基于RSSI的质心定位算法。首先通过无线信号强度计算出节点间RSSI值,然后把RSSI值转换成质心算法权值,最后采用质心定位算法对待测节点位置进行估计,获得节点的准确位置。仿真实验结果表明,与现有质心定位算法相比,基于RSSI的质心定位算法在不增加成本、通信功耗的情况下,提高了节点定位精度,降低了定位误差,适合各种规模的无线传感器网络的节点定位。     

无需测距的综合节点定位算法

针对基本的DV-Hop节点定位算法会产生不良的节点和多级跳带来的累积误差、定位精度不高以及能量消耗方面等缺点,提出一种改进的综合定位算法,即基于一种无需测距的综合节点定位算法,这种算法能够节省附加节点的硬件开销进而能达到准确的定位。改进以后的算法的定位误差率明显比改进前的定位误差率小,表明了定位误差率随锚节点数量的增加而减小。通过MATLAB软件对节点定位误差方面进行仿真验证,仿真实验结果证明该改进后的算法稳定、可靠,易于实现,提高了定位精确度、降低了能量消耗水平,达到了预期的目标。     

NLOS环境下无线传感器网络TOA定位算法

针对现有定位算法定位精度低、适用场景少的问题,提出一种非视距传播（NLOS）环境下的无线传感器网络电波到达时间（TOA）定位算法。对未知节点位置进行初步估计,将该估计值作为初始迭代参考点,利用泰勒级数展开法进行迭代计算,得到未知节点位置的二次估计值。使用二次估计值反推得到未知节点与各传感器锚节点的近似距离,将原始TOA测量距离与该近似距离之差作为非视距传播误差值,从而剔除NLOS误差较大的TOA测量组,利用误差修正后的TOA测量组再次进行泰勒级数迭代处理,实现未知节点的精确定位。仿真结果表明,该算法可有效抑制NLOS误差,相比传统定位算法,其定位误差小、定位精度高。     

基于入侵杂草优化算法的无线传感网节点定位

在基于测距的无线传感器网络节点定位中,最小二乘法由于定位误差的累积,定位精度不高。针对该问题,提出了一种基于入侵杂草优化算法的定位方法。该算法以定位误差为适应度函数,将定位问题转换为求解非线性方程组最优化问题。在求解的过程中,利用未知节点到锚节点的距离和锚节点可信度对适应度函数进行修正,以实现更高精度的定位。仿真实验表明:改进的定位算法,在不同测距误差、不同通信半径、不同锚节点数和不同节点数下,都能得到更高的定位精度。     

一种基于加权多尺度分析技术的鲁棒节点定位算法

研究了多种网络拓扑结构及稀疏网络下节点定位的鲁棒性问题. 联合考虑 1 跳邻居数目、邻居节点自身定位精度与测距误差, 引入节点相对定位误差和相对可信度概念, 提出了一种分布式基于加权多尺度分析技术的鲁棒节点定位算法. 该算法根据节点2跳局部网络连通度信息及邻居节点相对定位误差大小, 自适应选择综合性能好的邻居节点参与迭代优化, 并采用与节点相对可信度成正比的加权机制, 增加高可信度节点在定位计算中的贡献度. 实验数据显示, 该定位算法能够有效地抑制较大定位误差在网络内的扩散, 同基于高斯核加权的 dwMDS(G) 算法相比, 不仅迭代次数减半, 而且在网络连通度较低或拓扑不规则时, 可提高 5% 左右的定位精度.     

一种高效安全的无证书数字签名方案

无证书签名体制容易遭受公钥替换攻击,在很多已有的方案中,密钥生成中心(KGC)可假冒合法用户生成"有效"的公私钥对。在Gap Diffie-Hellman(GDH)群中,利用用户公钥和部分私钥"绑定"技术,提出了一种可追踪KGC假冒的无证书签名方案,在随机谕示模型下,给出了该方案的安全性分析。与同类方案相比,该方案具有较高的效率。     

基于RSSI权值的环境适应型室内定位算法研究

定位节点接收的信号强度指示（Received Signal Strength Indication,RSSI）值是室内指纹定位技术重要的元素之一。通过对定位节点接收到的信号强度值特性分析,提出了基于RSSI权值的室内定位算法。改进型RSSI权值计算公式以及权值指数[α]的提出,使得定位算法具有一定的环境适应性,能更灵活地运用于实际定位场景。经过一般实验场景验证,算法在定位精度上有较大的提升。     

A secure and robust temporal credential-based three-factor user authentication scheme for wireless sensor networks

User authentication is one of the most important security services required for the resource-constrained wireless sensor networks (WSNs). In user authentication, for critical applications of WSNs, a legitimate user is allowed to query and collect the real-time data at any time from a sensor node of the network as and when he/she demands for it. In order to get the real-time information from the nodes, the user needs to be first authenticated by the nodes as well as the gateway node (GWN) of WSN so that illegal access to nodes do not happen in the network. Recently, Jiang et al. proposed an efficient two-factor user authentication scheme with unlinkability property in WSNs Jiang (2014). In this paper, we analyze Jiang et al.’s scheme. Unfortunately, we point out that Jiang et al.’s scheme has still several drawbacks such as (1) it fails to protect privileged insider attack, (2) inefficient registration phase for the sensor nodes, (3) it fails to provide proper authentication in login and authentication phase, (4) it fails to update properly the new changed password of a user in the password update phase, (5) it lacks of supporting dynamic sensor node addition after initial deployment of nodes in the network, and (6) it lacks the formal security verification. In order to withstand these pitfalls found in Jiang et al.’s scheme, we aim to propose a three-factor user authentication scheme for WSNs. Our scheme preserves the original merits of Jiang et al.’s scheme. Our scheme is efficient as compared to Jiang et al.’s scheme and other schemes. Furthermore, our scheme provides better security features and higher security level than other schemes. In addition, we simulate our scheme for the formal security analysis using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool. The simulation results clearly demonstrate that our scheme is also secure.