Detection of Insider Selective Forwarding Attack Based on Monitor Node and Trust Mechanism in WSN

The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.

An Efficient Billing Scheme for Trusted Nodes Using Fuzzy Logic in Wireless Sensor Networks

Extending the lifetime of the wireless sensor networks (WSNs), where recharging sensors is not always possible, has been a major concern for researchers for the past decade. In this paper, we study the cooperation between nodes in wireless sensor networks in forwarding packets to others, and we propose a new collaboration technique which stimulates intermediate nodes to forward packets toward their destination. Some nodes show selfish behavior by denying the forwarding packets to other nodes in commercial networks in an effort to preserve their own energy. This paper applies a technique which is used to prolong the network lifetime, based on a node’s energy and trust value, and additionally incorporates fuzzy logic, which stimulates nodes to forward packets by rewarding cooperation. According to simulation results, the proposed approach surpasses the Nuglets (virtual currency) approach and the Reputation approach in network energy and thus prolongs the network lifetime. Additionally, our proposed approach demonstrates better results in the number of dropped packets, PDR and forwarded packets to neighboring nodes.

基于RTM信任模型的DPoS共识机制改进研究

为了解决传统DPoS共识算法中存在的恶意行为“摇摆节点”问题和因权益分配不均所造成的“财富集中”问题,提出了一种基于RTM信任模型改进的R-DPoS共识算法。首先,该算法根据节点间的信息传播方向与交易关系对网络节点进行集合分类,在考虑了时间衰减因子等影响因素的条件下分别计算了各节点的直接信任值、推荐信任值以及全局信任值;其次,引入了节点摇摆度值概念,根据计算得到摇摆值的大小,将相邻共识轮次前后该值的变化情况进行比较,再对摇摆节点做出不同程度下的共识轮次惩罚限制措施;最后,在见证人节点投票过程中,增加了平衡反对票环节,再利用前期得到的综合信誉值,构建了一套新的记账节点选举评估准则,根据每轮计算后得到的节点评估值大小来动态地选择见证人节点,并完成一轮共识过程。仿真实验结果表明:改进后的共识算法相较原始DPoS共识算法、基于奖励机制和信用机制的改进共识算法而言,节点选举成为见证人节点的积极性提高了24%、18%,公平性增加了15%、10%,节点作恶的概率降低了9%、15%。

多信源无线传感网络带宽时延感知数据汇聚方法

为提高多信源无线传感网络的传输效率,设计了一种多信源无线传感网络带宽时延感知数据汇聚方法。该方法构建三类虚拟队列,并根据带宽时延数据判断阈值进行端到端计算,以针对不同类型的数据流计算相应的带宽时延阈值。使用卡方拟合检验方法对当前时延感知数据的信任度进行判定,在此基础上排除异常或偏离分布模型的数据样本。对高卡方统计量的数据进行压缩或信息提取,并通过聚类权值实现感知数据汇聚。仿真结果显示,该方法在高斯噪声或莱斯噪声环境下,能将传输时延控制在50 ms以内,网络带宽数据汇聚结果较高,且网络数据传输耗能低于100 J。这表明多信源无线传感网络带宽时延感知数据汇聚可减少传输时间和资源浪费。

基于AMP模式多核处理器的可信节点构建方法

针对多核处理器的安全性进行研究,深入探讨了微处理器技术的发展背景以及多核处理器在非对称多处理(AMP)模式下所面临的安全挑战。通过运用可信计算技术和双体系架构,结合AMP模式的工作特点以及多核之间的控制机制,提出一种主动免疫防御系统的策略和可信节点的构建方法,分析了可信计算在全工作过程中的度量机制,有效解决了多核处理器在AMP模式下的安全问题,同时很好地保持了核内原有系统的实时性。该方法不仅可以增强多核处理器的安全性,还能确保系统的可信运行环境,为未来计算设备的安全提供了坚实的支撑。通过对实验验证结果的分析,构建方案完全可行,能够在实际应用中推广。

物联网内节点信任传递能耗智能感知仿真

物联网由大量分布在不同位置的节点组成,通过能耗感知,可以优化信任传递路径的选择和节点之间的通信方式,从而提高整个物联网网络的性能和效率。因此,提出一种物联网节点信任传递能耗智能感知方法。通过对物联网体系架构展开分析,提取物联网节点信任传递能耗评估指标,建立对应的指标体系。利用T-S模糊神经网络获取各个指标对应的节点信任传递能耗智能感知结果,通过层次分析法将全部感知结果展开融合处理,最终实现物联网节点信任传递能耗智能感知。通过实验分析表明,所提方法可以精准感知物联网节点信任传递能耗变化情况且感知效率高,耗时短,可以为物联网节点信任传递能耗智能感知的进一步研究和应用提供重要的参考依据。

面向物联数据的改进分片方案设计

为提升区块链在物联数据处理中的吞吐量,减轻其存储压力,分片技术被广泛认为是一种有效解决方案。论文提出一种改进的节点分片方案,旨在考虑节点信任分片差异,通过节点处理不同类型物联数据计算其信任分数并划分信任等级,将不同信任等级的节点合理地分配至各个分片,以确保各分片拥有相近的信任值,并控制各分片内均存在不同信任等级的节点,减少区块链系统崩溃的概率。同时,考虑节点之间通信延迟以及分片内节点数,有效降低了分片间的通信延迟。仿真实验表明,相较于Monoxide和Rapidchain方案,论文提出的改进分片方案降低了区块链系统的通信延迟和崩溃概率,显著提高了区块链系统的吞吐量和安全性。

智慧管网中物联网传感器节点安全性研究

智慧管网不断发展,应用规模不断扩大,智慧管网的安全对于石化企业的安全运营愈发重要。其中,基础数据采集和传输作为智慧管网的数据基石,安全性至关重要。由于存在负责收集数据的传感器设备资源较少、部署环境恶劣等原因,这些设备容易受到攻击,导致数据异常,最终影响上层应用在传感器设备安全方面的接入问题,基于此,提出一种智慧管网中物联网传感器节点安全接入方案,将节点进行信任度量化判断是否可信,并在数据集上进行实验表明该方法能够有效抵御对感知层传感器设备的攻击。应用该方法可以提高智慧管网的感知层节点安全性,保障底层数据源的安全。

基于综合交互信任的工业安全路由性能仿真优化

工业网络安全直接影响到工业的效益。使用经过改进处理信任评估模型,与两跳实时可靠路由协议THTP相结合,设计出一种建立在工业无线传感器网络节点上的安全路由协议NCS。通过更新直接信任值交互次数的方式来抵御由恶意节点发起的暴力攻击,利用推荐节点提供的推荐信任可靠度可以去除不可靠推荐节点,促进网络安全性的显著提升。研究结果表明:通过实时更新NCS的节点交互次数可以快速减小网络受到恶意节点影响时信任值,使丢包率明显降低。

基于内生安全的高压直流输电控制保护系统研究

面对日益突出的网络安全问题,高压直流输电控制保护系统的安全防护面临着严重威胁。结合高压直流输电控制保护系统整体架构,提出了一种内生安全高压直流输电控制保护系统设计方法,按照可信主动防御体系框架建立可信安全管理中心,分别对运行人员控制层、控制保护层、现场层进行可信节点设计。该系统有助于提高高压直流输电的整体防护水平。

面向跨级可信协作服务的大规模节点组网共识算法

为有效提升业务数据跨级可信协作服务的可扩展性、高鲁棒性、高并发能力与处理效能,提出一种面向多层级大规模节点组网场景的高效共识算法——高效拜占庭容错(Efficient Byzantine Fault Tolerance, EBFT)。在现有共识算法的基础上,把轮换主节点作为常规共识流程的一部分,实现所有节点轮流担任主节点进行提案,以减轻单一主节点带来的压力并保证节点间的公平性。通过合并视图切换流程和正常流程实现了快速共识,进一步提升算法灵活性、可靠性和数字签名性能。仿真实验表明,所提算法满足了跨级大规模业务数据流转对业务系统处理能力和响应速度的实际需求。

Density-based rough set model for hesitant node clustering in overlapping community detection

Overlapping community detection in a network is a challenging issue which attracts lots of attention in recent years.A notion of hesitant node（HN） is proposed. An HN contacts with multiple communities while the communications are not strong or even accidental, thus the HN holds an implicit community structure.However, HNs are not rare in the real world network. It is important to identify them because they can be efficient hubs which form the overlapping portions of communities or simple attached nodes to some communities. Current approaches have difficulties in identifying and clustering HNs. A density-based rough set model（DBRSM） is proposed by combining the virtue of densitybased algorithms and rough set models. It incorporates the macro perspective of the community structure of the whole network and the micro perspective of the local information held by HNs, which would facilitate the further ＂growth＂ of HNs in community. We offer a theoretical support for this model from the point of strength of the trust path. The experiments on the real-world and synthetic datasets show the practical significance of analyzing and clustering the HNs based on DBRSM. Besides, the clustering based on DBRSM promotes the modularity optimization.

A Secure Microgrid Data Storage Strategy with Directed Acyclic Graph Consensus Mechanism

The wide application of intelligent terminals in microgrids has fueled the surge of data amount in recent years.In real-world scenarios,microgrids must store large amounts of data efficiently while also being able to withstand malicious cyberattacks.To meet the high hardware resource requirements,address the vulnerability to network attacks and poor reliability in the tradi-tional centralized data storage schemes,this paper proposes a secure storage management method for microgrid data that considers node trust and directed acyclic graph(DAG)consensus mechanism.Firstly,the microgrid data storage model is designed based on the edge computing technology.The blockchain,deployed on the edge computing server and combined with cloud storage,ensures reliable data storage in the microgrid.Secondly,a blockchain consen-sus algorithm based on directed acyclic graph data structure is then proposed to effectively improve the data storage timeliness and avoid disadvantages in traditional blockchain topology such as long chain construction time and low consensus efficiency.Finally,considering the tolerance differences among the candidate chain-building nodes to network attacks,a hash value update mechanism of blockchain header with node trust identification to ensure data storage security is proposed.Experimental results from the microgrid data storage platform show that the proposed method can achieve a private key update time of less than 5 milliseconds.When the number of blockchain nodes is less than 25,the blockchain construction takes no more than 80 mins,and the data throughput is close to 300 kbps.Compared with the traditional chain-topology-based consensus methods that do not consider node trust,the proposed method has higher efficiency in data storage and better resistance to network attacks.

物联网环境中可信移动节点接入认证技术研究

针对物联网数据节点因缺少可信性验证导致传输安全性较差的问题,研究一种可信移动节点接入认证技术。首先,在设计技术架构的基础上,拼接并生成身份标识;其次,完成初始化操作后,提取密钥,完成移动节点与终端节点的双向认证与接入;最后,进行实验分析。测试结果表明:针对50组可信移动节点,利用本文方法安全接入认证的延迟时间较短,接入认证的成功率较高;针对50组非可信移动节点,利用本文方法验证并完成阻拦的成功率也较高,说明本文方法能够为物联网通信网络的稳定运行提供技术支持。

基于能耗信任值的无线传感网络克隆攻击检测方法

为避免无线传感网络信息传输时被黑客克隆攻击,导致数据传输质量下降,在能耗信任值的基础上,提出一种无线传感网络克隆攻击检测方法。根据无线传感网络节点拓扑图,建立无线传感网络节点能耗模型,计算接收端和发送端在信息传输时所消耗的能耗。以簇内成员节点信息路由表为依据,利用簇头节点对每个成员节点的ID、Postion和剩余能量值展开初期检测、能耗信任值计算和数据融合。基站端通过对簇头节点路由信息和融合后的信息进行检测的方式,完成对整个无线传感网络的克隆攻击检测。仿真分析结果表明,所提方法具有较高的检出率、数据包投递率以及较低的时延和能耗,取得了较理想的攻击检测结果。

车联网络车辆结点路由算法研究

设计一种基于地理位置和结点信任值的车联网络路由算法。路由算法在传输数据时,首先通过信标广播获得目的地结点的地理位置信息和邻居结点的地理位置信息,然后结点根据收集到的地理位置信息调用转发算法进行数据包转发。路由算法使用两种转发策略,贪婪转发策略和修正转发策略,通过实验仿真获得特定情境下路由算法的平均端到端时延和丢包率,分析车辆结点数目和车辆结点最大速度对路由算法性能的影响。

基于信任行为感知的WSN主动识别安全算法

在无线传感器网络中,为了解决恶意节点通过伪装窃取数据,造成WSN中敏感信息丢失问题,提出了一种基于可信连接架构的安全访问模型。通过引入调节因子和挥发因子可以自适应调整节点历史信任值对综合信任度的影响,阻止恶意节点通过群体欺诈获取信任值,同时设置节点最低信任阈值,以防止节点受到虚假转发数据、拒绝转发数据的影响。利用主动识别策略识别网络中可能存在的信任攻击,进一步提高模型的安全性。结果表明:该方法可以对网络中的信任攻击行为进行有效地识别,从而提升了对恶意结果的检测率和恶意节点的识别速度;能有效降低节点时延,减少网络丢包,延长生命周期。

A Direct Trust dependent Link State Routing Protocol Using Route Trusts for WSNs (DTLSRP)

The traditional cryptographic security techniques are not sufficient for secure routing of message from source to destination in Wireless Sensor Networks (WSNs), because it requires sophisticated software, hardware, large memory, high processing speed and communication bandwidth. It is not economic and feasible because, depending on the application, WSN nodes are high-volume in number (hence, limited resources at each node), deployment area may be hazardous, unattended and/or hostile and sometimes dangerous. As WSNs are characterized by severely constrained resources and requirement to operate in an ad-hoc manner, security functionality implementation to protect nodes from adversary forces and secure routing of message from source node to base station has become a challenging task. In this paper, we present a direct trust dependent link state routing using route trusts which protects WSNs against routing attacks by eliminating the un-trusted nodes before making routes and finding best trustworthy route among them. We compare our work with the most prevalent routing protocols and show its benefits over them.

区块链DPoS共识机制改进研究

区块链共识算法可用于增强物联网安全性,提高网络节点之间的协作效率。委托权益证明(Delegated Proof of Stake,DPoS)可以同时满足低成本和高效率的要求,提高节点协作的服务质量。然而,协作节点的恶意攻击、自私行为和投票积极性不高都会影响DPoS的共识过程。针对这些挑战,该文对DPoS共识机制进行了改进,为了提高节点的投票积极性,提出了一种信任值模型,根据节点行为将信用评价指标分为“交易情况”“性能”“信用级别”三个一级指标以及对应的二级指标,并采用动态分配二级指标权重的方法对节点信任值进行计算,从而使选出的节点更加可信。同时,针对恶意节点以及自私行为,提出了一种基于高斯混合模型的异常节点剔除算法,对投票数据进行划分,计算其混合高斯概率密度值,并设定阈值,将低于阈值的节点剔除,从而识别并剔除异常数据。相对于传统的DPoS,改进后的DPoS节点出块速率以及异常节点剔除率都有显著提升。

基于信任机制的电力无线传感网络安全簇头选举算法

无线传感网络(wireless sensor network,WSN)越来越多地应用于生产生活中的感知和监测场景中,但所处环境中大量的传感器节点通常面临着被攻击的安全风险。传感器节点资源受限,安全防护脆弱,在采集数据时容易遭受选择性转发、伪造篡改数据等恶意攻击,使系统遭受不必要的损失。提出了一种基于信任机制的无线传感网络安全簇头选举算法,综合考虑节点的历史通信记录、数据一致性、簇内节点距离以及和基站之间的距离,将通信质量和能耗考虑在内,通过时间周期轮替保证簇头节点的能耗公平性,选举安全可靠的簇头作为簇群的汇聚节点。仿真结果表明,该算法能有效避免恶意节点当选簇头,提高无线传感网络的安全性。