基于CPN的车载网络无证书匿名认证和密钥协商方案研究

为了解决现有车载网络的认证方案中普遍存在密钥托管带来的缺陷,以及没有考虑计算受限电子控制单元(ECU)轻量级部署和安全快速认证的问题,首先,针对计算不受限的ECU网络,提出了一种无双线性配对的轻量级无证书匿名认证和密钥协商方案,该方案通过椭圆曲线密码体制安全构建认证密钥对,通过哈希函数和异或等轻量级方法实现匿名认证和密钥协商。然后,针对计算受限的ECU网络,提出了一种无证书批量验证方案来降低认证成本。最后,提出了一种基于有色Petri网(CPN)和Dolev-Yao攻击者模型的安全验证方法,对整体方案进行形式化安全性评估。安全评估和性能分析表明,所提方案能有效抵抗重放、伪装、篡改、已知密钥、已知特定会话临时信息攻击等多种不同类型的攻击,在保证多重安全属性的同时有较小的计算与通信成本。

MARL-GPN:一种基于多智能体强化学习的博弈Petri网

作为过程挖掘中的一个重要研究分支,变化挖掘可运用在系统安全分析、IPS安全建设等场景下,从变化域的生成情况判断可能存在的未知漏洞。而传统变化挖掘算法更注重业务流程的安全性,无法满足在动态博弈场景下挖掘需要考虑多方安全效益所形成有效变化域的情况。针对此问题,提出一种基于多智能体强化学习的博弈Petri网(MARL-GPN),以专用于动态安全模型的有效变化域研究。该新型的博弈Petri网会首先根据攻防事件构建效益矩阵,然后各智能体间会根据对方当前状态与下一步走势生成最优应对策略,其次在指定学习周期下达成纳什平衡得到双方最优活动迹,与传统变化挖掘进行比对即可得到有效变化域。最后以典型信息安全事件为例验证了该模型的可行性。

基于改进FPPN的飞控系统故障传播路径分析方法

针对飞控系统多冗余、多闭环的结构特性,结合有向图模型和模糊Petri网(FPN)模型,构建飞控系统故障传播模糊概率Petri网(FPPN)模型,以解决飞控系统特定结构下的故障传播路径问题。改进的FPPN模型包含飞控系统有向图模型、故障传播特性量化计算模型和故障传播FPPN模型3个部分。采用面向对象技术分析飞控系统的功能行为和物理结构,综合复杂网络理论,构建系统故障传播有向图模型;引入Floyd算法,开展系统耦合关联分析,基于节点的度和边介数定义系统故障传播特性;在有向图模型的基础上,提出相应的结构映射规则,构建飞控系统故障传播FPPN模型,融合改进后的参数量化方法,设定2种推理算法对系统多冗余、闭环结构特性下的故障传播路径进行有效分析。通过数值分析与实例验证,获取飞控系统典型故障传播路径及路径上相关节点的状态值,验证所提方法的有效性。

基于Petri网的全自动无人驾驶列车停站场景形式化建模与验证

为进一步提高全自动无人驾驶系统的安全性,采用Petri网理论在全生命周期早期对系统运营场景的实现流程进行形式化建模与验证。选取正线运营中的列车停站这一典型运营场景,进行对象提取与状态分析,结合各对象与库所、变迁的对应关系,建立Petri网模型,并利用仿真软件PIPE对其有效性和正确性进行形式化验证。针对可能出现的异常情况对模型进行优化,设置车门与站台门开关时序,避免乘客拥挤时出现安全隐患。试验结果表明:建立的Petri网模型有界、安全且无死锁,满足列车停站场景功能需求,模型的可靠性和有效性得以验证,为全自动无人驾驶系统的开发应用与安全分析提供理论支撑。

混合动态系统的混合Petri网(HSPN)模型

针对混合动态系统，提出一种混合 Ｐｅｔｒｉ网（ Ｈ Ｓ Ｐ Ｎ）模型，分析了该模型具有的特点及其运行规则。以冶金加热炉为例，给出了该系统的 Ｈ Ｓ Ｐ Ｎ 模型。

基于受控混杂Petri网(CHPN)的分层优化模型及其在炼油厂氢气管理中的应用

提出了一种基于受控混杂 Petri 网(CHPN)的分层优化建模结构,并将其应用于炼油厂的氢气网络优化管理中。这种分层优化结构将 CHPN 建立的过程仿真模型同传统的数学优化方法紧密结合在一起,上层的数学优化模型根据经济指标寻求最优解,下层CHPN 在上层最优解的控制下运行,可以根据工厂的实际生产条件的改变在计划期内及时调整调度安排,并保证经济指标的最优性。炼油厂氢气平衡管理建模实例显示,通过该方法获得的炼油厂氢气平衡调度方案减少了炼油厂生产过程中氢气资源的浪费现象,提高了企业的经济效益。

基于改进的方向性加权模糊Petri网配电网故障诊断

为提高配电网保护动作信息丢失时故障诊断的准确率及容错性,提出了基于改进的方向性加权模糊Petri网配电网故障诊断方法。首先,考虑故障发生时近后备保护对可疑故障元件故障诊断的影响,对可疑故障元件的各个故障蔓延方向进行建模;其次,在专家经验的基础上采用随机数对模型输入权值进行随机赋值;最后,在保护动作信息丢失时,跟踪改变可疑故障元件保护未动作的可信度取值,并分析该故障诊断方法的适应性与容错性。仿真结果表明,所提基于改进的方向性加权模糊Petri网配电网故障诊断模型在信息不完备或者保护及断路器拒动时,均具有较高的故障诊断准确率。

基于Petri网的无人机可充电传感器网络优化

为解决地面移动充电车难避障、易受干扰,以及数据收集受充电时间影响大的问题,提出包含一架数据收集无人机(unmanned aerial vehicle,UAV)和多架充电无人机的网络架构。首次提出广义同步连续自控Petri网系统(generalized synchronizing continuous cyber Petri net system,GSCCPNS),用于建立无人机的能量传输和运动控制模型,从可视化和数学两方面刻画网络的决策控制、能量流动和飞行轨迹。首先,利用等边三角形簇头覆盖法确定网络锚节点数量和节点总体能耗。然后,为了使无人机充电收益最大化,在传统模拟退火算法的基础上,引入局部搜索和交叉算子,并结合Petri网提出Petri模拟退火(Petri simulated annealing,Petri-SA)算法。大规模仿真表明,死节点比例降低11%~26%,飞行能耗降低7%~17%。

Capacitated stochastic coloured Petri net-based approach for computing two-terminal reliability of multi-state network

Classical network reliability problems assume both net- works and components have only binary states, fully working or fully failed states. But many actual networks are multi-state, such as communication networks and transportation networks. The nodes and arcs in the networks may be in intermediate states which are not fully working either fully failed. A simulation ap- proach for computing the two-terminal reliability of a multi-state network is described. Two-terminal reliability is defined as the probability that d units of demand can be supplied from the source to sink nodes under the time threshold T. The capacities of arcs may be in a stochastic state following any discrete or continuous distribution. The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and de- mand. To solve this problem, a capacitated stochastic coloured Petri net is proposed for modelling the system behaviour. Places and transitions respectively stand for the nodes and arcs of a net- work. Capacitated transition and self-modified token colour with route information are defined to describe the multi-state network. By the simulation, the two-terminal reliability and node importance can be estimated and the optimal route whose reliability is highest can also be given. Finally, two examples of different kinds of multi- state networks are given.

高校实验室危险化学品全过程管理Petri网模型及其应用

针对高校实验室危险化学品管理中存在的化学药剂种类多、监管周期长、流转环节多、使用过程动态变化等问题,文章在分析实验室危险化学品全过程管理流程的基础上,构建了高校实验室危险化学品全过程管理Petri网模型。计算分析和仿真验证结果表明,该模型具有有界性、可达性、安全性和活性等特性,是合理且有效的,可为高校实验室危险化学品全过程管理体系和溯源体系构建提供支撑。

基于Petri网的运输流程系统建模优化

通过Petri网对货拉拉运输流程的建模进行了优化,对传统货拉拉运输流程进行建模,并发现模型中存在一些不足,针对其不足进行相应的优化,加入了物品分类别运输和订单异常问题处理的方法,对其运输中产生纠纷的现象提出了一种解决方法。Petri网作为一种用于描述离散的、分布式系统的数学建模工具,它在货拉拉运输中的运用不仅提高了运输的效率,也同时提高了客户的满意度和服务的质量。将所构建的模型在PIPE软件中进行仿真,验证了该优化的合理性和可行性。

Neural network approach to blindestimation of PN spreading sequence in lower SNR DS/SS signals

An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extraction of unsupervised neural networks are exploited adequately. Theoretical analysis and experimental results are provided to show that this approach can work well on the lower S/N ratio input signals.

A Parametric Colored Petri Net Model of a Switched Network

A parametric Colored Petri net model of the switched Ethernet network with the tree-like topology is developed. The model’s structure is the same for any given network and contains fixed number of nodes. The tree-like topology of a definite network is given as the marking of dedicated places. The model represents a network containing workstations, servers, switches, and provides the evaluation of the network response time. Besides topology, the parameters of the model are performances of hardware and software used within the network. Performance evaluation for the network of the railway dispatcher center is implemented. Topics of the steady-stable condition and the optimal choice of hardware are discussed.

A reliable routing algorithm based on fuzzy Petri net in mobile ad hoc networks

A novel reliable routing algorithm in mobile ad hoc networks using fuzzy Petri net with its reasoning mechanism was proposed to increase the reliability during the routing selection. The algorithm allows the structured representation of network topology, which has a fuzzy reasoning mechanism for finding the routing sprouting tree from the source node to the destination node in the mobile ad boc environment. Finally, by comparing the degree of reliability in the routing sprouting tree, the most reliable route can be computed. The algorithm not only offers the local reliability between each neighboring node, but also provides global reliability for the whole selected route. The algorithm can be applied to most existing on-demand routing protocols, and the simulation results show that the routing reliability is increased by more than 80% when applying the proposed algorithm to the ad hoc on demand distance vector routing protocol.

An SPN analysis method for parallel scheduling in Ad Hoc networks

In this paper, a new analytic method for modeling and evaluating mobile ad hoc networks (MANET) is proposed. Petri nets technique is introduced into MANET and a packet-flow parallel scheduling scheme is presented using Stochastic Petri Nets (SPN). The flowing of tokens is used in graphics mode to characterize dynamical features of sharing a single wireless channel. Through SPN reachability analysis and isomorphic continuous time Markov process equations, some network parameters, such as channel efficiency, one-hop transmission delay etc., can be obtained. Compared with conventional performance evaluation methods, the above parameters are mathematical expressions instead of test results from a simulator.

A New Method of Semantic Network Knowledge Representation Based on Extended Petri Net

Abstract： It was discussed that the way to reflect the internal relations between judgment and identification, the two most fundamental ways of thinking or cognition operations, during the course of the semantic network knowledge representation processing. A new extended Petri net is defined based on qualitative mapping, which strengths the expressive ability of the feature of thinking and the mode of action of brain. A model of semantic network knowledge representation based on new Petri net is given. Semantic network knowledge has a more efficient representation and reasoning mechanism. This model not only can reflect the characteristics of associative memory in semantic network knowledge representation, but also can use Petri net to express the criterion changes and its change law of recognition judgment, especially the cognitive operation of thinking based on extraction and integration of sensory characteristics to well express the thinking transition course from quantitative change to qualitative change of human cognition.

基于Petri网的配电网规划工作流模型

结合配电网规划工作实际情况,充分利用工作流技术,建立一套适用于配电网规划工作的Petri网模型。该模型可以清晰地展示配电网规划过程中各个业务环节之间的相关性,将整个配电网规划过程流程化,可以有效地协助配电网规划人员快速熟悉、掌握业务流程,快速提升配电网规划业务水平,为实现配电网规划工作业务的信息化管理打下基础。

基于赋色Petri网的反辐射导弹对雷达毁伤效率评估建模

针对反辐射导弹对雷达毁伤效率评估过程中,存在的评估结果不稳定问题,基于赋色Petri网构建了雷达毁伤效率评估模型。采用ZigBee协议构建赋色Petri网,并建立反辐射导弹对雷达毁伤效率参数分析模型。提取反辐射导弹对雷达毁伤评估统计特征量,采用反演特征分析方法,构建雷达毁伤效率大数据分析模型,并结合大数据参数融合和特征分析结果,求解反辐射导弹对雷达毁伤效率评估模型,将输出的评估信息传输至Web界面,实现反辐射导弹对雷达毁伤效率自动化评估。测试结果表明,采用该方法进行反辐射导弹对雷达毁伤效率评估建模的可靠性较高,评估效能较好。

A Neural Network Approach to Blind Estimation of PN Spreading Sequence in DS/SS Signals

In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.

Designing Genetic Regulatory Networks Using Fuzzy Petri Nets Approach

In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition （HFT） to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.