基于Agent人工智能的异构网络多重覆盖节点入侵检测系统设计

异构网络具有结构复杂、多重覆盖面积大等特征,使得网络入侵检测较为隐蔽,威胁网络运行的安全性;为此,对基于Agent人工智能的异构网络多重覆盖节点入侵检测系统进行了研究;通过检测Agent和通信Agent装设主机Agent,以Cisco Stealthwatch流量传感器作为异构网络传感器检测攻击行为,采用STM32L151RDT664位微控制器传输批量数据,由MAX3232芯片实现系统电平转化,实现硬件系统设计;软件部分设计入侵检测标准,采用传感器设备捕获网络实时数据,通过Agent技术解析异构网络协议并提取数据运行特征,综合考虑协议解析结果及与检测标准匹配度,实现异构网络多重覆盖节点入侵检测;经实验测试表明,基于Agent人工智能的异构网络多重覆盖节点入侵检测系统入侵行为的漏检率和入侵类型误检率的平均值仅为6%和5%,能够有效提高检测精度,减小检测误差。

基于多Agent的含DG智能配电网差动保护自愈方法

含DG智能配电网中的潮流方向随分布式发电的变化而变化,导致配电网故障自愈的效果难以保障,因此,提出基于多Agent的含DG智能配电网差动保护自愈方法。通过构建基于多Agent的MAS体系结构,将其应用于含DG智能配电网差动保护和自愈的控制,在MAS体系结构的数据处理层完成差动保护,并在MAS体系结构的协调控制层实现故障自愈。结果表明,该设计方法不仅可以恢复配电网故障区域的电力,而且在操作次数、线损及功率因数方面可达到较理想的效果。

Weighted average consensus problem in networks of agents with diverse time-delays

This paper studies the weighted average consensus problem for networks of agents with fixed directed asymmetric unbalance information exchange topology. We suppose that the classical distributed consensus protocol is destroyed by diverse time-delays which include communication time-delay and self time-delay. Based on the generalized Nyquist stability criterion and the Gerschgorin disk theorem, some sufficient conditions for the consensus of multi-agent systems are obtained. And we give the expression of the weighted average consensus value for our consensus protocol. Finally, numerical examples are presented to illustrate the theoretical results.

Node Coverage Algorithms in Wireless Sensor Networks Using Mobile Agents

This paper proposes fault tolerant algorithms for routing mobile agents in a single channel wireless sensor network which cover every node in the network. These algorithms use local knowledge (assume no knowledge of global deployment or topology, etc). We propose the algorithms and show mathematical analysis to support our claims. The paper ends with simulation studies and discussion of results.

Multi-agent cooperative intrusion response in mobile adhoc networks

The nature of adhoc networks makes them vulnerable to security attacks. Many security technologies such as intrusion prevention and intrusion detection are passive in response to intrusions in that their countermea- sures are only to protect the networks, and there is no automated network-wide counteraction against detected intrusions, the architecture of cooperation intrusion response based multi-agent is propose. The architecture is composed of mobile agents. Monitor agent resides on every node and monitors its neighbor nodes. Decision agent collects information from monitor nodes and detects an intrusion by security policies. When an intruder is found in the architecture, the block agents will get to the neighbor nodes of the intruder and form the mobile firewall to isolate the intruder. In the end, we evaluate it by simulation.

Predictive Tracking Control of Network-Based Agents With Communication Delays

This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.

Target Tracking and Obstacle Avoidance for Multi-agent Networks with Input Constraints

In this paper, the problems of target tracking and obstacle avoidance for multi-agent networks with input constraints are investigated. When there is a moving obstacle, the control objectives are to make the agents track a moving target and to avoid collisions among agents. First, without considering the input constraints, a novel distributed controller can be obtained based on the potential function. Second, at each sampling time, the control algorithm is optimized. Furthermore, to solve the problem that agents cannot effectively avoid the obstacles in dynamic environment where the obstacles are moving, a new velocity repulsive potential is designed. One advantage of the designed control algorithm is that each agent only requires local knowledge of its neighboring agents. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

Multi-Agent Network Intrusion Active Defense Model Based on Immune Theory

Inspired by the immune theory and multi-agent systems, an immune multi-agent active defense model for network intrusion is established. The concept of immune agent is introduced, and its running mechanism is established. The method, which uses antibody concentration to quantitatively describe the degree of intrusion danger, is presented. This model implements the multi-layer and distributed active defense mechanism for network intrusion. The experiment results show that this model is a good solution to the network security defense.

Application of mobile scanning agent in the network security

To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning agent. More attentions is paid to expound how to design and realize mobile scanning agent. Besides, it is also explained the programs of mobile scanning agent system. In the end, it expects mobile scanning agent.

Research on Application of Mobile Agent Based on Immune Algorithms in Ad Hoc Network

Ad Hoc network is a kind of multi hop, self-organizing wireless network without center. Each node in network can be used as host as well as router and it can form any network topology through wireless connections. Because of characteristics of itself, many new service items and application fields appear;meanwhile, it is also faced with many new security threats. Using immune agent can perceive the change of network node and make corresponding decision behavior, find the misbehavior nodes in the network as soon as possible and reduce the network attack and improve the immune competence of network.

Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.

Multi-agent Based Modeling of Manufacturing Network

An intelligent manufacturing system is modeled currently from the viewpoint of manufacturing applications,and the network platform’s influence to manufacturing applications is not considered adequately. However any bottleneck in service oriented architecture (SOA) for the manufacturing network can affect the agility of the IT environment. In this paper,to achieve a trade-off between manufacturing resources and network resources,the manufacturing network is modeled with multi-agent,in which two kinds of basic elements,the manufacturing application unit and the network carrier of manufacturing information,are presented. And their main characters are described by colored petri net. The manufacturing application model drives the network platform that inversely provides this application model technology supports. The proposed multi-agent system is demonstrated through an example integration scenario involving production plan,resources management and execution subsystems. And the result suggests that analyzing and designing the system architecture of networked manufacturing should give due attention to the operation system as well as manufacturing applications.

Prediction Model of Antibacterial Activities for Inorganic Antibacterial Agents Based on Artificial Neural Networks

Quantitatively evaluation of antibacterial activities of inorganic antibacterial agents is an urgent problem to be solved. Using experimental data by an orthogonal design, a prediction model of the relation between conditions of preparing inorganic antibacterial agents and their antibacterial activities has been developed. This is accomplished by introducing BP artificial neural networks in the study of inorganic antibacterial agents. It provides a theoretical support for the development and research on inorganic antibacterial agents. Key words inorganic antibacterial agent - antibacterial activity - neural networks - nanometer material

Wireless Network Security: The Mobile Agent Approach

The broadcast nature of wireless network makes traditional link-layer attacks readily available to anyone within the range of the network. User authentication is best safeguard against the risk of unauthorized access to the wireless networks. The present 802.1× authentication scheme has some flaws, making mutual authentication impossible and open to man-in-the-middle attacks. These characteristics make traditional cryptographic mechanism provide weak security for the wireless environment. We have proposed the use of mobile agents to provide dependable Internet services delivery to users, this will guarantee secure authentication in wireless networks and we examine the feasibility of our solution and propose a model for wireless network security.

Design and Implementation of a Network Management System Based on Mobile RMON Agent

To improve the scalability of RMON-based network management, the concept of Mobile RMON Agent (MRA) was presented by combining the mobile agent technology with RMON. Then an MRA-based Network Management System (MRANMS) was designed and implemented. RMON functions were achieved by programming the mobile agent to make it capture and analyze packets locally. The experimental result on the Grasshopper platform indicates that MRA as a mobile agent can migrate to another subnet and calculate a RMON MIB value and TrafficMatrix in a subnet with 29 hosts. Furthermore, the behavior of MRA can be customized to achieve new RMON functions, such as the statistics of hostTable in RMON MIB. It can be concluded that MRANMS is based on the mode of distribution, and besides the compatibility with standard RMON, the system possesses scalability of management function.

协作自主AI Agent系统及工业系统网络安全应用研究

ChatGPT系列大规模语言模型已可应用于安全审计、侦察、攻击、检测、防护、逆向工程、应急响应与漏洞修复等多个方面,但直接使用这类模型存在违反监管政策和泄露企业敏感信息等问题。本文在自主AI技术基础上,研究了应用于企业局域网的协作AI Agent安全应用系统,基于5种中等大规模语言模型和Langchain等工具开发了原型系统。经安全应用测试,原型系统的网络扫描、威胁处置方法、安全工具推荐、下载链接等指标可达到ChatGPT性能的70%以上,仅在一致性、稳定性、可重复性方面有所差距。研究成果可以继续通过中等规模模型能力提升和制定自然语言输入句型规范,以及中等规模LLM协作系统,将能力逐步提升到ChatGPT大规模语言模型能力水平,并保留不泄露企业敏感信息优势,这将是革命性智能化地改变工业系统网络安全的一种途径。

Research and Design of Network Management Construction Based on Mobile AGENT

The technical characters of mobile agent （MA） originated in the distributional artificial intelligence domain is introduced. A network management construction based on agent （NMCA） is then proposed. The NMCA structure features are elaborated in detail. A prototype design of NMCA is given by using the jKQML programming. The establishment of NMCA platform will be helpful to reduce the correspondence load of network management and improves the efficiency and the expansion ability of network management systems.

A Mobile-Agent-Based Adaptive Data Fusion Algorithm for Multiple Signal Ensembles in Wireless Sensor Networks

Distributed Compressed Sensing (DCS) is an emerging field that exploits both intra- and inter-signal correlation structures and enables new distributed coding algorithms for multiple signal ensembles in wireless sensor networks. The DCS theory rests on the joint sparsity of a multi-signal ensemble. In this paper we propose a new mobile-agent-based Adaptive Data Fusion (ADF) algorithm to determine the minimum number of measurements each node required for perfectly joint reconstruction of multiple signal ensembles. We theoretically show that ADF provides the optimal strategy with as minimum total number of measurements as possible and hence reduces communication cost and network load. Simulation results indicate that ADF enjoys better performance than DCS and mobile-agent-based full data fusion algorithm including reconstruction performance and network energy efficiency.

基于免疫Agent的配电网电缆线路故障自愈系统

传统配电网电缆线路无法有效管理负荷,且故障自愈时间较长。为了解决这个问题,设计了基于免疫Agent的配电网电缆线路故障自愈系统。采用免疫Agent结构采集电缆线路异常数据,并将数据发送给各个电缆线路内的成员代理完成信息交互。采用双中央处理的智能控制终端,实现就地控制。采用联邦式通信服务器,协调Agent通信行为。构建故障自愈模型,设定拓扑约束条件,确定评估价指标,设计自愈执行步骤。根据实验结果可知,应用该方法后,98%以上的配电网电缆故障得以自愈,且耗时更短,应用效果非常理想。