Distributed intrusion detection for mobile ad hoc networks

Mobile ad hoc networking （MANET） has become an exciting and important technology in recent years, because of the rapid proliferation of wireless devices. Mobile ad hoc networks is highly vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, and lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer sufficient and effective for those features. A distributed intrusion detection approach based on timed automata is given. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then the timed automata is constructed by the way of manually abstracting the correct behaviours of the node according to the routing protocol of dynamic source routing （DSR）. The monitor nodes can verify the behaviour of every nodes by timed automata, and validly detect real-time attacks without signatures of intrusion or trained data. Compared with the architecture where each node is its own IDS agent, the approach is much more efficient while maintaining the same level of effectiveness. Finally, the intrusion detection method is evaluated through simulation experiments.

WOA-DNN for Intelligent Intrusion Detection and Classification in MANET Services

Mobile ad-hoc networks(MANET)are garnering a lot of attention because of their potential to provide low-cost solutions to real-world communica-tions.MANETs are more vulnerable to security threats.Changes in nodes,band-width limits,and centralized control and management are some of the characteristics.IDS(Intrusion Detection System)are the aid for detection,deter-mination,and identification of illegal system activity such as use,copying,mod-ification,and destruction of data.To address the identified issues,academics have begun to concentrate on building IDS-based machine learning algorithms.Deep learning is a type of machine learning that can produce exceptional outcomes.This study proposes that WOA-DNN be used to detect and classify incursions in MANET(Whale Optimized Deep Neural Network Model)WOA(Whale Opti-mization Algorithm)and DNN(Deep Neural Network)are used to optimize the preprocessed data to construct a system for classifying and predicting unantici-pated cyber-attacks that are both effective and efficient.As a result,secure data transport to other nodes is provided,preventing intruder attacks.The invaders are found using the(Machine Learning)ML-IDS and WOA-DNN methods.The data is reduced in dimensionality using Principal Component Analysis(PCA),which improves the accuracy of the outputs.A classifier is used in forward propagation to predict whether a result is normal or malicious.To compare the traditional and proposed models’effectiveness,the accuracy of classification,detection of the attack rate,precision rate,and F-Measure,Recall are utilized.The proposed WOA-DNN model has higher assessment metrics and a 99.1%accuracy rate.WOA-DNN also has a greater assault detection rate than others,resulting in fewer false alarms.The classification accuracy of the proposed WOA-DNN model is 99.1%.

General Study of Mobile Agent Based Intrusion Detection System (IDS)

The extensive access of network interaction has made present networks more responsive to earlier intrusions. In distributed network intrusions, there are many computing nodes that are assisted by intruders. The evidence of intrusions is to be associated from all the held up nodes. From the last few years, mobile agent based technique in intrusion detection system (IDS) has been widely used to detect intrusion over distributed network. This paper presented survey of several existing mobile agent based intrusion detection system and comparative analysis report between them. Furthermore we have focused on each attribute of analysis, for example technique (NIDS, HIDS or Hybrid), behavior layer, detection techniques for analysis, uses of mobile agent and technology used by existing IDS, strength and issues. Their strengths and issues are situational wherever appropriate. We have observed that some of the existing techniques are used in IDS which causes low detection rate, behavior layers like TCP connection for packet capturing which is most important activity in NIDS and response time (technology execution time) with memory consumption by mobile agent as major issues.

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.

Cluster-based Intrusion Detection in Wireless Ad-Hoc Networks

There are inherent vulnerabilities that are not easily preventable in the mobile Ad-Hoc networks.To build a highly secure wireless Ad-Hoc network,intrusion detection and response techniques need to be deployed;The intrusion detection and cluster-based Ad-Hoc networks has been introduced,then,an architecture for better intrusion detection based on cluster using Data Mining in wireless Ad -Hoc networks has been shown.A statistical anomaly detection approach has been used.The anomaly detection and trace analysis have been done locally in each node and possibly through cooperation with clusterhead detection in the network.

A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

Mobile computing is the most powerful application for network com-munication and connectivity,given recent breakthroughs in thefield of wireless networks or Mobile Ad-hoc networks(MANETs).There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate precision.For most applications,a frame-work must ensure that the retrieved data reflects the transmitted data.Before driv-ing to other nodes,if the frame between the two nodes is deformed in the data-link layer,it must be repaired.Most link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it down.In other words,because of asset information must be secured from threats,information is a valu-able resource.In MANETs,some applications necessitate the use of a network method for detecting and blocking these assaults.Building a secure intrusion detection system in the network,which provides security to the nodes and route paths in the network,is a major difficulty in MANET.Attacks on the network can jeopardize security issues discovered by the intrusion detection system engine,which are then blocked by the network’s intrusion prevention engine.By bringing the Secure Intrusion Detection System(S-IDS)into the network,a new technique for implementing security goals and preventing attacks will be developed.The Secure Energy Routing(SER)protocol for MANETs is introduced in this study.The protocol addresses the issue of network security by detecting and preventing attacks in the network.The data transmission in the MANET is forwarded using Elliptical Curve Cryptography(ECC)with an objective to improve the level of security.Network Simulator–2 is used to simulate the network and experiments are compared with existing methods.

Detecting and adaptive responding mechanism for mobile WSN

Mobile wireless sensor network(WSN)composed by mobile terminals has a dynamic topology and can be widely used in various fields.However,the lack of centralized control,dynamic topology and limited energy supply make the network layer of mobile WSN be vulnerable to multiple attacks,such as black hole(BH),gray hole(GH),flooding attacks(FA)and rushing attacks(RU).Existing researches on intrusion attacks against mobile WSN,currently,tend to focus on targeted detection of certain types of attacks.The defense methods also have clear directionality and is unable to deal with indeterminate intrusion attacks.Therefore,this work will design an indeterminate intrusion attack oriented detecting and adaptive responding mechanism for mobile WSN.The proposed mechanism first uses a test sliding window(TSW)to improve the detecting accuracy,then constructs parameter models of confidence on attack(COA),network performance degradation(NPD)and adaptive responding behaviors list,finally adaptively responds according to the decision table,so as to improve the universality and flexibility of the detecting and adaptive responding mechanism.The simulation results show that the proposed mechanism can achieve multiple types of intrusion detecting in multiple attack scenarios,and can achieve effective response under low network consumption.

基于Mobile Agent的入侵检测系统模型的研究

提出了一个基于MobileAgent技术的入侵检测系统模型.该模型采用传送Agent实现关键主机的隐藏,提高系统的抗攻击性;采用分区域管理增强系统的扩展性及适应性;在CIDF通信协议下,采用协作Agent实现多个入侵检测系统的协同工作.此外,还对模型的优缺点做了分析,为将来MobileAgent在入侵检测系统中的应用提供一定的依据.

基于Mobile Agent数据挖掘技术的入侵检测系统

在分析当前入侵检测系统的基础上,提出了基于Mob ile Agent数据挖掘技术的入侵检测系统。该系统通过Mob ile Agent收集入侵检测所需要的数据,并通过数据挖掘产生不同的知识库,在入侵检测系统中建立了一套及时、完整和准确的数据收集机制。

基于Mobile Agent分布式入侵检测系统研究

将新型分布式处理技术——移动Agent与入侵检测融为一体,提出了一种基于移动Agent的分布式入侵检测系统(MADIDS)的结构模型,分析了各组成模块结构、功能特点及模块间的协作关系,实现了基于此结构的分布式入侵检测系统。采取了一些防范措施来保证分布式入侵检测系统自身的安全,使该系统具有良好的灵活性、鲁棒性和可扩展性。

基于MOBILE AGENT入侵检测系统的安全研究

通过考察国内外分布式移动入侵检测系统的发展现状,分析了目前基于MOB ILE AGENT(移动代理)的IDS应用所存在的安全问题,提出结合JAVA安全特性采用一种新型平台AGLETWORKBENCH开发MA IDS的技术研究.首先介绍了AGLET的基本知识,然后通过分析AGLET的工作流程,从几个方面论述了用AGLET可以为MOB ILE AGENT

基于Mobile Agents的新型分布式入侵检测系统

在分析一般入侵检测方法的基础上 ,提出了一种新的基于MobileAgent (MA)的分布式入侵检测方法 .该方法兼顾了原有的优点 ,并在一定程度上弥补了原有方法的不足 .重点讨论了MA在入侵检测系统中的应用 ,叙述了如何通过MAs之间的协作进行入侵检测 ,并利用MA的特性对入侵检测系统本身的安全性和抗毁灭性做了具体的论述 .提出的入侵检测结构提高了系统的抗毁性和自恢复能力 ,提高了入侵检测系统自身的安全性 .说明了系统的体系结构。

AN IMMUNITY-BASED SECURITY ARCHITECTURE FOR MOBILE AD HOC NETWORKS

This paper focuses on investigating immunological principles in designing a multi-agent security architecture for intrusion detection and response in mobile ad hoc networks. In this approach, the immunity-based agents monitor the situation in the network. These agents can take appropriate actions according to the underlying security policies. Specifically, their activities are coordinated in a hierarchical fashion while sensing, communicating, decision and generating responses. Such an agent can learn and adapt to its environment dynamically and can detect both known and unknown intrusions. The proposed intrusion detection architecture is designed to be flexible, extendible, and adaptable that can perform real-time monitoring. This paper provides the conceptual view and a general framework of the proposed system. In the end, the architecture is illustrated by an example to show it can prevent the attack efficiently.

入侵检测系统中分布式Mobile Agent模型

通过在入侵检测系统中应用分布式移动代理技术,提出分布式入侵检测系统的框架结构,较全面地分析系统构成和工作方式。该模型充分利用移动代理独有特点,从而避免传统网络入侵检测系统得不足,提高入侵检测系统的效能。

基于Mobile Agent的智能化分布式入侵检测系统模型

入侵检测系统是用来监测攻击的防护手段,但是以往的一些结构难以适应现在的高速网络,误报和漏报频繁,而且它们大都不能智能的分析数据来自动更新规则或其它检测机制,网络管理人员工作繁重,入侵检测系统相互之间又是相互独立的,为了解决以上几个问题,我们提出了基于移动代理的智能化分布式入侵检测模型。

基于Mobile Agent的新型分布式入侵检测方法

在分析一般入侵检测方法的基础上,提出了一种新的基于Mobile Agent的入侵检测方法.与AAFID等入侵 检测方法相比,新方法提高了系统的抗毁坏性和自恢复能力.

基于MobileAgent的网络入侵检测技术

随着网络安全技术的发展，入侵检测系统（IDS）在网络环境中的应用越来越普遍，但传统的入侵检测技术存在诸多缺陷。而基于移动Agent的入侵检测是分布式计算技术和人工智能技术有机结合的产物，弥补了传统入侵检测的诸多不足。本文研究了移动Agent系统的体系结构、通信机制、数据安全及其研究现状和发展方向。

Security: A Core Issue in Mobile <i>Ad hoc</i>Networks

Computation is spanning from PC to Mobile devices. The Mobile Ad hoc Networks (MANETs) are optimal choice to accommodate this growing trend but there is a problem, security is the core issue. MANETs rely on wireless links for communication. Wireless networks are considered more exposed to security attacks as compared to wired networks, especially;MANETs are the soft target due to vulnerable in nature. Lack of infrastructure, open peer to peer connectivity, shared wireless medium, dynamic topology and scalability are the key characteristics of MANETs which make them ideal for security attacks. In this paper, we shall discuss in detail, what does security mean, why MANETs are more susceptible to security attacks than wired networks, taxonomy of network attacks and layer wise analysis of network attacks. Finally, we shall propose solutions to meet the security challenges, according to our framed security criteria.

Mobile Agent技术在企业网络安全防范中的应用——基于Mobile Agent的入侵检测系统研究

企业局域网建设是企业信息化进程中的核心要素,当前企业局域网普遍遭遇日益专业和复杂的网络安全问题,单单依靠防火墙技术已不能完全保障企业局域网安全,基于Mobile Agent的入侵检测系统的安全方案是针对当今网络安全状况和企业网络安全的重要尝试。

基于GRU神经网络的移动应用软件流量检测

针对移动应用软件流量呈动态变化趋势,导致检测结果不精准的问题,提出基于GRU神经网络的移动应用软件流量检测方法。基于GRU神经网络多层结构构建GRU神经网络检测模型,将恶意软件和非恶意软件流量特征转化为区域特征向量,根据特征转化结果降维处理入侵威胁数据,获取待检测恶意软件入侵训练集和测试集,完成移动应用软件异常流量辨识。根据辨识结果建立病毒库,设计GRU神经网络隐层单元结构,有效地捕获流量动态变化信息,划分异常流量入侵等级,实现移动应用软件流量检测。由实验结果可知,该方法在对应用软件进行流量检测时得到的结果与实际结果一致。在应用软件40~80天时检测出流量使用异常情况,使用流量为1050 MB,其余时间的流量使用正常,具有精准的软件流量检测效果。