基于聚类的网络异常检测

探索一种基于聚类来识别异常的方法,这个方法不需要手动标示的训练数据集却可以探测到很多不同类型的入侵行为.实验结果表明该方法是可行的和有效的,使用它来进行异常检测可以得到探测率和误报率的一个平衡,从而为异常检测问题提供一个较好的解决办法.     

Double Cluster Head Heterogeneous Clustering for Optimization in Hybrid Wireless Sensor Network

Wireless Personal Communications - The growth of ubiquitous and pervasive computing is largely derived from the contribution of Wireless Sensor Network (WSN) in several fields such as medicine,...     

基于权值的无线传感器网络分簇算法

综述了无线传感器网络路由算法的主要成果,但重点分析更具有能量有效性的分簇路由算法,对各种算法的主要思想进行了性能评价,提出了一种新的算法.     

Jammed Node Detection and Routing in a Multihop Wireless Sensor Network Using Hybrid Techniques

Wireless Personal Communications - Wireless sensor networks are susceptible to various Denial-of-Service attacks due to their open deployment. Jamming attack at the physical layer is a type of...     

Improve Performance of Wireless Sensor Network Clustering Using Mobile Relay

Wireless Personal Communications - Wireless sensor networks sense events, collect data and forward it to the infrastructural node, called sink, for further processing and assessment. The...     

无线传感器网络中的分簇算法

分簇算法是无线传感器网络中实施分层路由所采用的重要方法,尤其是传感器节点受到能量和带宽的严重制约。如何合理、有效地利用分簇算法使得网络中节点的能量分布趋于一致,从而延长网络的生命周期,提高系统的整体性能指标,成为当前无线传感器网络研究领域内的热点问题之一。本文从能量有效性的角度出发,对最新的分簇算法进行研究与分析,指出如何根据无线传感器网络不同的分布区域、应用场景和多样的无线环境,生成性能优越的分簇算法。     

Rule‐Based Anomaly Detection Technique Using Roaming Honeypots for Wireless Sensor Networks

Because the nodes in a wireless sensor network (WSN) are mobile and the network is highly dynamic, monitoring every node at all times is impractical. As a result, an intruder can attack the network easily, thus impairing the system. Hence, detecting anomalies in the network is very essential for handling efficient and safe communication. To overcome these issues, in this paper, we propose a rule‐based anomaly detection technique using roaming honeypots. Initially, the honeypots are deployed in such a way that all nodes in the network are covered by at least one honeypot. Honeypots check every new connection by letting the centralized administrator collect the information regarding the new connection by slowing down the communication with the new node. Certain pre‐defined rules are applied on the new node to make a decision regarding the anomality of the node. When the timer value of each honeypot expires, other sensor nodes are appointed as honeypots. Owing to this honeypot rotation, the intruder will not be able to track a honeypot to impair the network. Simulation results show that this technique can efficiently handle the anomaly detection in a WSN.     

无线传感器网络能量均衡分簇路由协议

LEACH是无线传感器网络(Wireless Sensor Network,WSN)中一种经典的分层式路由协议,在此基础上通过对LEACH成簇算法及簇间路由的改进,提出了一种新的均衡能量消耗分簇路由协议。该协议在无线传感器网络成簇过程中充分考虑了传感器节点的能量状态,同时簇首向基站的通信采用基于能量的簇间路由。理论分析及仿真结果表明,改进的协议能够均衡传感器节点的能量消耗,有效地延长网络寿命。     

Fault-Tolerance Data Aggregation for Clustering Wireless Sensor Network

The hierarchical cluster-based topology is commonly accepted as an optimal structure for sensor network to increase communication scalability, prolong network lifetime, and reduce data redundancy. However, the data privacy and security are challenging the proliferation of clustering wireless sensor network (CWSN) due to its highly constrained resources and violably deployed environments, which make it infeasible to directly apply traditional cryptography and therefore vulnerable to various attacks. This article proposes a scheme that provides efficient privacy-preserving data fusion as well as malicious data tolerance by mining concealed data within groups. And the dynamically organized groups in each cluster improves resilience against large number of node compromise comparing with the existing data aggregation schemes. The simulation results and mathematical comparison show the effectiveness and fitness of our scheme for CWSN in terms of fault tolerance and process efficiency, which costs a little of additional overheads in memory and communication.     

面向目标跟踪的无线传感器网络动态分簇

在考虑节点剩余能量和节点探测信号强度的基础上,提出了一种面向目标跟踪的无线传感器网络动态分簇方法。由于在簇首选择时考虑了节点的剩余能量,因此可以有效地避免簇首节点能量不足导致的跟踪失败。方法既能保证各个节点均衡地担任簇首节点,又能避免簇首切换过于频繁,因此可以延长网络的使用寿命。计算机仿真结果表明,在满足簇首节点能量需求和簇内节点大部分能观测到目标的情况下,应该取尽量小的能量阈值和尽量大的距离阈值。     

考虑整体消耗代价的无线传感器网络分簇算法

在LEACH协议的基础上,研究一种无线传感器网络分簇算法,采用高级节点作为固定簇头替代LEACH中的随机簇头选择策略,推导出最优簇头节点数目即所需高级节点数的计算公式及各类节点所需能量的表达式,并从网络整体消耗代价的角度出发,通过仿真对网络性能进行分析评价。结果表明,采用一定量的高级节点作为固定簇头,当其节点硬件代价和电池能量代价之比a1/b超过一定值时,新算法的整体网络代价明显低于LEACH。     

Minimum Path Exposure and Detection Interval Setting for Target Detection Using Wireless Sensor Network

Sensor network generally detects target at a fixed frequency. Detection interval means time spacing between two adjacent detection attempts. While designing a sensor network for detection of target intrusion in a specific region, the interval should be carefully set with trade-off between power consumption and detection performance. This is because redundant power may be consumed if it is too short and the target may be missed if too long. In this paper, we study the determination of the maximum detection interval (MDI) with specified detection performance. Path exposure is adopted as a performance metric. For detection-oriented application, a novel method to evaluate the minimum path exposure (MPE) is developed. Then the MDI problem is formulated and its solution is presented. The factors influencing the MDI are extensively simulated.

面向异常检测的人体行为聚类

We presented a novel framework for automatic behavior clustering and unsupervised anomaly detection in a large video set. The framework consisted of the following key components: 1) Drawing from natural language processing, we introduced a compact and effective behavior representation method as a stochastic sequence of spatiotemporal events, where we analyzed the global structural information of behaviors using their local action statistics. 2) The natural grouping of behavior patterns was discovered through a novel clustering algorithm. 3) A run-time accumulative anomaly measure was introduced to detect abnormal behavior, whereas normal behavior patterns were recognized when sufficient visual evidence had become available based on an online Likelihood Ratio Test (LRT) method. This ensured robust and reliable anomaly detection and normal behavior recognition at the shortest possible time. Experimental results demonstrated the effectiveness and robustness of our approach using noisy and sparse data sets collected from a real surveillance scenario.     

Intrusion Detection System in Wireless Sensor Network Using Conditional Generative Adversarial Network

Wireless communication networks have much data to sense, process, and transmit. It tends to develop a security mechanism to care for these needs for such modern-day systems. An intrusion detection system (IDS) is a solution that has recently gained the researcher’s attention with the application of deep learning techniques in IDS. In this paper, we propose an IDS model that uses a deep learning algorithm, conditional generative adversarial network (CGAN), enabling unsupervised learning in the model and adding an eXtreme gradient boosting (XGBoost) classifier for faster comparison and visualization of results. The proposed method can reduce the need to deploy extra sensors to generate fake data to fool the intruder 1.2–2.6%, as the proposed system generates this fake data. The parameters were selected to give optimal results to our model without significant alterations and complications. The model learns from its dataset samples with the multiple-layer network for a refined training process. We aimed that the proposed model could improve the accuracy and thus, decrease the false detection rate and obtain good precision in the cases of both the datasets, NSL-KDD and the CICIDS2017, which can be used as a detector for cyber intrusions. The false alarm rate of the proposed model decreases by about 1.827%.

     

A Centralized Balance Clustering Routing Protocol for Wireless Sensor Network

Routing protocol plays a role of great importance in the performance of wireless sensor networks (WSNs). A centralized balance clustering routing protocol based on location is proposed for WSN with random distribution in this paper. In order to keep clustering balanced through the whole lifetime of the network and adapt to the non-uniform distribution of sensor nodes, we design a systemic algorithm for clustering. First, the algorithm determines the cluster number according to condition of the network, and adjusts the hexagonal clustering results to balance the number of nodes of each cluster. Second, it selects cluster heads in each cluster base on the energy and distribution of nodes, and optimizes the clustering results to minimize energy consumption. Finally, it allocates suitable time slots for transmission to avoid collision. Simulation results demonstrate that the proposed protocol can balance the energy consumption and improve the network throughput and lifetime significantly.     

一种基于WSN的能源有效的被动聚类模式

在分析无线传感器网络（WSN）的能量消耗模型的基础上，提出了一种新的层次型、分布式的能源有效的被动聚类模式EEPCS。采用“智能延迟策略”和“智能启发式选择”产生类首和网关结点，改变了传统被动聚类模式中通信结点能源消耗过快、网络不连通等缺点。理论分析和实验结果表明，EEPCS不仅能够节省通信结点的能量消耗，而且使能量在节点间均衡消耗，延长了网络的生存周期。     

Clustering Algorithm for Deployment of Independent Heterogeneous Wireless Sensor Network

Wireless Personal Communications - Wireless Sensor Network (WSN) is the main element of modern Industrial Internet of Things system in event monitoring. However, WSN is unable to respond for longer...     

An Improved Fuzzy Unequal Clustering Algorithm for Wireless Sensor Network

This paper introduces IFUC, which is an Improved Fuzzy Unequal Clustering scheme for large scale wireless sensor networks (WSNs).It aims to balance the energy consumption and prolong the network lifetime. Our approach focuses on energy efficient clustering scheme and inter-cluster routing protocol. On the one hand, considering each node’s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine each node’s chance of becoming cluster head and estimate the cluster head competence radius. On the other hand, we use Ant Colony Optimization (ACO) method to construct the energy-aware routing between cluster heads and base station. It reduces and balances the energy consumption of cluster heads and solves the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The validation experiment results have indicated that the proposed clustering scheme performs much better than many other methods such as LEACH, CHEF and EEUC.     

无线传感器网络分簇算法分析与性能比较

文中在介绍无线传感器网络路由协议的基础上,重点分析了几种有代表性的分簇路由协议算法。然后对各种分簇算法从10个评价参数上进行了一个综合对比,总结了无线传感器网络现有分簇路由协议的优点和存在的问题。最后从网络安全性和协议的实用性等方面,并对无线传感器网络分簇路由协议算法进行了展望。