Trust Based DoS Attack Detection in Wireless Sensor Networks for Reliable Data Transmission

Wireless Personal Communications - Wireless sensor network occupies an inevitable role in various applications that requires data collection and transmission. The tiny wireless sensor nodes are...     

A Centralized Mechanism for Preventing DDOS Attack in Wireless Sensor Networks

Wireless sensor networks face numerous limitations. Security and Privacy are the two most essential parameters that require consideration in wireless sensor networks for conveying responsive information amid basic applications. High density and limited communication range of sensor nodes, forwarding packets in sensor networks have caused the performance of during multi-hop data transmission. Hence communication with different devices these days are not secure, due to the absence of centralized monitoring and overprotective requirements. This paper is related to speak about Distributed Denial of Service which debilitates the ability of the network and the data being transmitted. The earlier system guarantees the WSN through a self arranged and confined procedure between the nodes in the sensor environment. Here, the authors present the Centralized Detect Eliminate and Control algorithm for authorization and centralized monitoring component to discover the node that has turned into a victim node and to get rid of the information communicated to the fatality node from the neighbour nodes. Overprotective of the communication between the nodes leads to dependability. The simulation results improve the malicious node detection rate and increase the various parameters like throughput and reduce the average delay. This leads to, the overall detection rate built, eventually enhancing the parameters of the network environment.

     

Detection of Replica Node Attack Based on Exponential Moving Average Model in Wireless Sensor Networks

Due to the broadcast nature of wireless communication, wireless sensor networks (WSNs) are susceptible to several attacks. Amongst them, replica attack is one of the predominates as it facilitates the attackers to perform some other attacks. So, it is of immense significance to design a competent security method for WSNs. Introducing a trust method is the primary concern for assisting well-organized use of the available energy in each node in the energy restricted environment. In order to tradeoff between energy usage and attack detection, energy-based prediction approach is deemed to be a suitable one. A statistical method, exponential moving average (EMA) model based replica detection is proposed to detect replica node attack based on energy consumption threshold in WSNs. The difference between actual and predicted energy consumption exceeding the threshold level is considered as malicious. In this paper, future energy drop of a sensor node is forecasted using statistical measure instead of probabilistic method. In EMA model, the transition from higher power consuming state (active state) to lower power consuming states (sleep and sense states) is controlled by a fixed schedule. The accumulated average time of the node was in any state in the past is used to estimate the time duration of a node that spends in that state. Unlike Markov Model, the estimations of energy are made periodically. By this, computational overhead on the microcontroller of the sensor is greatly reduced in EMA approach. The simulation results taken using TRM simulator shows that choosing the threshold value which is neither too large nor too small results in optimum level of detection accuracy and lifetime of the network.

     

无线传感器网络中的虫洞攻击和防御

无线传感器网络被誉为21世纪三大技术之一,其安全问题受到了越来越多的关注.文章首先介绍了无线传感器网络的特征,分析了安全问题的根源,然后详细介绍了无线传感器网络中虫洞攻击的原理和破坏性,提出引入简化的marsh信任模型,将邻居节点以往表现作为信任评估的经验来源,通过具体分析确定节点的位置关系,从而避免传感器网络中的虫洞攻击,最后指出了下一步研究的方向.     

基于动态布鲁姆过滤器的DDoS攻击检测方法

基于传统的布鲁姆过滤器在异常流量检测方面存在的不足,提出了动态布鲁姆过滤器的异常流量检测的结构,在检测率和误码率上都有所提高,从而更有效的预防了DDOS攻击.     

一种DDoS攻击的检测算法

对于骨干网中存在的DDoS攻击,由于背景流量巨大,且分布式指向受害者的多个攻击流尚未汇聚,因此难以进行有效的检测。为了解决该问题,本文提出一种基于全局流量异常相关分析的检测方法,根据攻击流引起流量之间相关性的变化,采用主成份分析提取多条流量中的潜在异常部分之间的相关性,并将相关性变化程度作为攻击检测测度。实验结果证明了测度的可用性,能够克服骨干网中DDoS攻击流幅值相对低且不易检测的困难,同现有的全局流量检测方法相比,该方法能够取得更高的检测率。     

Outlier Detection in Wireless Sensor Networks Based on Neighbourhood

Wireless sensor networks contain millions of nodes deployed in a spatially dispersed manner. These sensors are low battery powered devices having limited storage and computation power. The data collected by these sensors may be subjected to error due to environmental fluctuations, interference in wireless communication or wearing of sensors with time. These erroneous data deviate significantly from the rest of the data. To solve this issue, we present a new technique named Outlierness Factor based on Neighbourhood to detect and analyse the outliers in sensor network. Proposed detection approach is time efficient and scalable. Further, outlier data are classified as errors due to sensor malfunctioning or actual detected events such as fire detection, weather changes, earthquakes, landslide etc. The capabilities of the proposed approach have been evaluated on real dataset obtained from Intel Berkeley research lab and synthetic datasets. The results show the effectiveness of the proposed approach in contrast to the previously dealt approaches.

     

DDoS Attack Detection and Wavelets

This paper presents a systematic method for DDoS attack detection. DDoS attack can be considered a system anomaly or misuse from which abnormal behavior is imposed on network traffic. Attack detection can be performed via abnormal behavior identification. Network traffic characterization with behavior modeling could be a good indication of attack detection. Aggregated traffic has been found to be strong bursty across a wide range of time scales. Wavelet analysis is able to capture complex temporal correlation across multiple time scales with very low computational complexity. We utilize energy distribution based on wavelet analysis to detect DDoS attack traffic. Energy distribution over time will have limited variation if the traffic keeps its behavior over time (i.e. attack-free situation) while an introduction of attack traffic in the network will elicit significant energy distribution deviation in a short time period. Our experimental results with typical Internet traffic trace show that energy distribution variance markedly changes, causing a spike when traffic behaviors are affected by DDoS attack. In contrast, normal traffic exhibits a remarkably stationary energy distribution. In addition, this spike in energy distribution variance can be captured in the early stages of an attack, far ahead of congestion build-up, making it an effective detection of the attack.     

带有黑洞节点探测的间断连接无线网络数据转发机制

间断连接无线网络利用节点移动产生的通信机会完成数据传输,但网络中的恶意节点通过伪造节点的相遇信息等方法,吸引并丢弃数据,影响网络的运行。该文提出带有黑洞攻击探测的间断连接无线网络数据转发机制,通过节点诚信度、信用度、间接信任度及数据转发能力4维信任属性的评估,获知攻击节点的行为规律,并采用粗糙集理论降低网络运行过程中产生的不确定状态信息引发的误判率,更加准确地对节点的可信性进行判断,进而,合理地为数据选择中继节点。结果表明,所提出的方法能有效提升黑洞节点的辨识率,对网络中其它非协作行为也有一定探测和防御能力,能显著改善网络性能。     

基于VTP方法的DDoS攻击实时检测技术研究

为了能及时准确检测DDoS攻击的发生,在对方差－时间图(VTP,Variance－Time Plots)方法分析的基础上,对基于VTP的实时在线计算Hurst参数技术进行了性能分析,得出了其具有高效性的结论,并利用这种技术,对MIT的林肯实验室数据进行了分析,总结出了DDoS攻击过程中,网络流量的自相似模型的Hurst参数变化规律,即DDoS攻击刚开始时,Hurst参数具有较快的上升趋势,然后在参数值很高水平的基础上具有缓慢下降趋势,直到计算Hurst参数的网络流量全部是DDoS攻击流量时,有一个突然下降的现象(从0.95以上降至0.45左右),并由此总结出一种基于Hurst参数实时检测DDoS攻击发生的技术.     

一种三角形网格空洞修复算法

无线传感器网络由大量传感器节点组成,在网络初始化时节点随机部署在目标区域中,导致某一区域未被覆盖而形成覆盖空洞.针对目标区域中存在覆盖空洞问题,设计了一种基于三角形网格的无需地理信息的空洞探测算法ATN和空洞修复算法TNR.利用ATN算法检测节点与其邻居形成的三角形网格是否被完全覆盖,TNR算法以ATN算法理论为基础,向三角形网格中添加节点使目标区域完全覆盖.理论与仿真实验分析表明,ANR算法能够探测出目标区域中所有空洞,TNR算法在部署密集的传感网络中能够快速完成空洞修复.     

基于SNMP和神经网络的DDoS攻击检测

DDoS（Distributed Denial of Service）已经严重威胁计算机网络安全。对DDoS攻击检测的关键是找到能反映攻击流和正常流区别的特征,设计简单高效的算法,实时检测。通过对攻击特点的分析,总结出15个基于SNMP（Simple Network Management Protocol）的检测特征。利用BP神经网络高效的计算性能,设计了基于SNMP和神经网络的DDoS攻击检测模型,提高了检测实时性和准确性。实验表明：该检测模型对多种DDoS攻击都具有很好的检测效果。     

基于分区的无线传感网节点复制攻击检测方法

 无线传感器网络部署在敌方区域时,节点可能被俘获,其信息被复制并散布到网络中进行破坏活动.这种攻击隐蔽,破坏力较强.本文提出了基于分区的节点复制攻击检测方法,通过将部署区域分区,并建立基于跳数的坐标,可有效检测节点复制攻击.仿真实验表明:本方法耗能少,效率高且无需辅助节点.     

无线传感器网络分布式多传感器目标检测

目标检测是无线传感器网络中的一种重要应用,文中提出了一种能量有效分布式多传感器目标检测方法,该方法区别于以往的单目标方法,通过多个节点相互协作对目标进行检测,算法1给出了时间序列离散法,求得目标被测距离,且多节点将检测到的信息在聚合节点进行聚合,并通过算法2找到一条最优传输路径将聚合数据包传送至sink节点。此外通过仿真比较了单节点检测目标和多节点协同检测目标的概率、权系数α对检测节点平均能量消耗的影响,并给出了目标检测数据的最佳采样周期。     

一种适用于无线传感器网络的 高效节能广播机制

 针对无线传感器网络结点体积小、内存与计算能力小、靠电池供电、结点密度高以及网络规模大的特点,提出了高效广播协议(EBP,Effective Broadcast Protocol).通过对广播过程中一个结点转播之后其邻域内其它结点的转播,即引发新转播的讨论,完成了对最佳引发新转播的分析.EBP广播协议以此为依据选择转播结点,不需要任何邻结点信息就可以高效完成广播,算法的控制开销和存储开销大大降低.EBP广播机制简单有效,在无线传感器网络中具有良好的扩展性.     

一种无线传感器网络中的簇头变化机制

针对无线传感器网络节点密集和节点能量有限等特点,提出了一种簇头变化机制,数据业务节点使用指数退避算法来竞争本簇的簇头,而原簇头转入休眠状态。网络仿真结果表明该机制可提高能量效率和降低传输时延。     

Energy-Efficient Routing for Signal Detection in Wireless Sensor Networks

For many envisioned applications of wireless sensor networks (WSNs), the information processing involves dealing with distributed data in the context of accurate signal detection and energy-efficient routing, which have been active research topics for many years, respectively. In this paper, we relate these two aspects via joint optimization. Considering the scenario of using distributed radar-like sensors to detect the presence of an object through active sensing, we formulate the problem of energy- efficient routing for signal detection under the Neyman–Pearson criterion, apparently for the first time. The joint optimization of detection and routing is carried out in a fusion center which precomputes the routes as a function of the geographic location to be monitored. Accordingly, we propose three different routing metrics that aim at an appropriate tradeoff between the detection performance and the energy expenditure. In particular, each metric relates the detection performance explicitly in terms of probabilities of detection and false alarm, with the energy consumed in sensing and routing. The routing problems are formulated as combinatorial optimization programs, and we provide solutions drawing on operations research. We present extensive simulation results that demonstrate the energy and detection performance tradeoffs for each proposed routing metric.      

无线传感器网络拥塞控制机制研究

本论文在分析无线传感器网络不同于普通有线网络的特征后,提出了一种适用于无线传感器网络的TCP 拥塞控制机制DW-TCP,此机制将TCP拥塞窗口分为拥塞丢包窗口和误码丢包窗口,在链路误码率较高时通过降低发送速率提高数据发送的可靠性,节约无线节点的能源消耗和系统不必要的开销,该机制不但考虑到拥塞丢包对数据发送速率的影响,而且考虑到无线链路中的误码丢包对数据发送速率的影响.     

无线传感器网络中定向扩散协议的改进算法

定向扩散算法周期性地扩散探测分组时,会给网络带来很大负载,严重影响了数据分组的传输性能。该文提出了一种基于梯度的受限扩散算法。通过分析邻居梯度,计算扩散的广度和深度,进而选取最优的转发节点集进行扩散。仿真结果表明受限扩散算法在保证较低能量消耗的前提下,大大缩短了扩散持续的时间和数据分组端到端时延。