Mobile Intrusion Detection System Research Articles

Analysis of a Fuzzy Based Intrusion Detection System in Wireless Ad Hoc Networks

Technology and its growth is considerably enormous. This massive growth allows the opening of new fields of application in the domain of wireless networking and mobile ad-hoc networks (MANET) is one of its kinds. Mobile ad hoc network is widely used from collaborative computing to time critical applications in indoor and outdoor environment. Mobility of ad hoc network makes very attractive in all areas of mobile applications. Nodes participating in mobile ad hoc networks are autonomous, self-configurable and act as a router as well. These types of networks are dynamic in nature and have sort life time. Dynamic nature and limitations of the wireless transmission medium make MANET unsecured and vulnerable to various attacks. It is very tough to implement security for this networks and it opens up doors for further research work on this area. There is a great scope for designing a system to identify attacks and take countermeasures to minimize it and keep the performance of the network within acceptable limits. Intrusion detection system is one of its kinds and considered as security mechanism for MANET. This thesis explores different types of intrusion detection system like misuse detection and anomaly detection for mobile ad hoc networks. Anomaly detection techniques for ad hoc networks depend on the characterization of normal behavior pattern of wireless nodes. This research work focuses on wireless node behavior based detection technique. Most of anomaly intrusion detection systems are focusing on upper layer traffic to a profile normal behavior of wireless node. This research work focus on media access control (MAC) layer and network layer of wireless node. It is inefficient to use a large feature set of MAC layer and network layer due to energy limitation in ad-hoc network. A minimal feature set from MAC layer and network layer were proposed. This research work proposed an anomaly intrusion detection system for mobile ad hoc network using fuzzy logic and weighted average method. The network performance of mobile ad hoc network with intrusion detection system was analyzed using various network parameters. Further the performance of the performance of the intrusion detection system was analyzed using detection rate and false alarms. Results show good improvement in detection rate and other performance metrics

Deep learning intrusion detection system for mobile ad hoc networks against flooding attacks

<p><span lang="EN-US">Mobile ad hoc networks (MANETs) are infrastructure-less, dynamic wireless networks and self-configuring, in which the nodes are resource constrained. With the exponential evolution of the paradigm of smart homes, smart cities, smart logistics, internet of things (IoT) and internet of vehicle (IoV), MANETs and their networks family, such as flying ad-hoc networks (FANETs), vehicular ad-hoc networks (VANETs), and wireless sensor network (WSN), are the backbone of the whole networks. Because of their multitude use, MANETs are vulnerable to various attacks, so intrusion detection systems (IDS) are used in MANETs to keep an eye on activities in order to spot any intrusions into networks. In this paper, we propose a knowledge-based intrusion detection system (KBIDS) to secure MANETs from two classes of distributed denial of service (DDoS) attacks, which are UDP/data and SYN flooding attacks. We use the approach of deep learning exactly deep neural network (DNN) with CICDDoS2019 dataset. Simulation results obtained show that the proposed architecture model can attain very interesting and encouraging performance and results (Accuracy, Precision, Recall and F1-score).</span></p>

Particle swarm optimisation algorithm-based intrusion detection system for mobile ad hoc network

Ad hoc network is the category of cooperative wireless mobile nodes with the absence of centralised authority or infrastructure. It is vulnerable to different types of attacks such as passive and active because of open environment, speedily varying topology and decentralised nodes. An attack by a malicious node known as 'black hole attack' can considerably diminishes ad hoc network performance and results in disintegration of network, inaccessible nodes and severely degrades network performance. Evaluation of the additional effect due to existence of malicious nodes and determination of the suitable measures to detect these nodes in the network is the prime objective of the research work. In order to overcome this misbehaviour activity in the network, a particle swarm optimisation algorithm-based intrusion detection system (PSO-IDS) for ad hoc networks is proposed. Swarm agents are effectively used to detect the malicious node by evaluating their packet behaviour based on packet delivery fraction (PDF), average delay, number of packets dropped and packet capture. A defence technique called IDS is deployed for prevention against black hole attack due to malicious nodes. The simulation study establishes that the proposed PSO-IDS algorithm improves the performance metrics like throughput and packet delivery ratio.

Particle swarm optimisation algorithm-based intrusion detection system for mobile ad hoc network

Particle swarm optimisation algorithm-based intrusion detection system for mobile ad hoc network

A novel support vector machine based intrusion detection system for mobile ad hoc networks

The performance of mobile ad hoc networks (MANETs) is significantly affected by the malicious nodes. One of the most common attacks in MANETs is denial of service (DoS); a type of intrusion specifically designed to target service integrity and availability of a certain network node. Hence, it is important to use an efficient intrusion detection system (IDS) that detects and removes the malicious nodes in the network to improve the performance by monitoring the network traffic continuously. The main contribution of this paper is the integration of an IDS into MANETs as a reliable and potent solution. A new approach to intrusion detection is developed based on support vector machine algorithm. The proposed IDS can detect the DoS type attacks at a high detection rate with a simple structure and short computing time. It is shown by extensive computer simulation that the proposed IDS improves the reliability of the network significantly by detecting and removing the malicious nodes in the system. The performance of the suggested approach is independent of the network routing protocol. The detection rate of the system is also not effected by node mobility and network size.

A swarm-based efficient distributed intrusion detection system for mobile ad hoc networks (MANET)

In mobile ad hoc network (MANET), the issues such as limited bandwidth availability, dynamic connectivity and so on cause the process of intrusion detection to be more complex. The nodes that monitor the malicious nodes should have necessary residual bandwidth and energy and should be trustable. In order to overcome these drawbacks, in this paper, we propose a swarm-based efficient distributed intrusion detection system for MANET. In this technique, swarm agents are utilised to select the nodes with highest trust value, residual bandwidth and residual energy as active nodes. Each active node monitors its neighbour nodes within its transmission range and collects the trust value from all monitored nodes. The active nodes adaptively change as per the trust thresholds. Upon collaborative exchange of the trust values of the monitored nodes among the active nodes, if the active node finds any node below a minimum trust threshold, then the node is marked as malicious. When the source receives alert message about the malicious node, a defence technique is deployed to filter the corresponding malicious node from the network. By simulation results, we show that the proposed approach is efficient intrusion detection mechanism for MANET.

CIDS: cross-layer intrusion detection system for mobile ad hoc networks

In mobile ad hoc networks (MANET), lack of centralised monitoring point and lack of clear line of defense pose serious challenges for intrusion detection systems (IDS). In this paper, we present CIDS, a cross-layer based intrusion detection system with enhanced security performance in mobile ad hoc networks. We utilise cross-layer interactions to gather measurements from different protocol layers to detect attacks with increased accuracy. We present a case study to analyse packet drop detection in ad hoc networks using cross-layer techniques. Compared to traditional watchdog detection, CIDS is more effective in distinguishing network misbehaviour from genuine network irregularities. Simulation results based on extensive experiments illustrate the robustness and reliability of CIDS through higher detection rate and lower false positives.