Introduction to Wireless Intrusion Detection Systems

The IDS (Intrusion Detection System) is a common means of protecting networked systems from attack or malicious misuse. The development and rollout of an IDS can take many different forms in terms of equipment, protocols, connectivity, cost and automation. This is particularly true of WIDS (Wireless Intrusion Detection Systems) which have many more opportunities and challenges associated with data transmission through an open, shared medium.
The operation of a WIDS is a multistep process from origination of an attack through to human readable evaluation. Attention to the performance of each of the processes in the chain from attack detection to evaluation is imperative if an optimum solution is to be sought. At present, research focuses very much on each discrete aspect of a WIDS with little consideration to the operation of the whole system. Taking a holistic view of the technology shows the interconnectivity and inter-dependence between stages, leading to improvements and novel research areas for investigation.
This chapter will outline the general structure of Wireless Intrusion Detection Systems and briefly describe the functions of each development stage, categorised into the following 6 areas:
• Threat Identification,
• Architecture,
• Data Collection,
• Intrusion Detection,
• Alert Correlation,
• Evaluation.
These topics will be considered in broad terms designed for those new to the area. Focus will be placed on ensuring the readers are aware of the impact of choices made at early stages in WIDS development on future stages.

Intrusion detection techniques in wireless local area networks

This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.

Unique Challenges in WiFi Intrusion Detection

The Intrusion Detection System (IDS) is a common means of protecting networked systems from attack or malicious misuse. The deployment of an IDS can take many different forms dependent on protocols, usage and cost. This is particularly true of Wireless Intrusion Detection Systems (WIDS) which have many detection challenges associated with data transmission through an open, shared medium, facilitated by fundamental changes at the Physical and MAC layers. WIDS need to be considered in more detail at these lower layers than their wired counterparts as they face unique challenges. The remainder of this chapter will investigate three of these challenges where WiFi deviates significantly from that of wired counterparts:

• Attacks Specific to WiFi Networks: Outlining the additional threats which WIDS must account for: Denial of Service, Encryption Bypass and AP Masquerading attacks.

• The Effect of Deployment Architecture on WIDS Performance: Demonstrating that the deployment environment of a network protected by a WIDS can influence the prioritisation of attacks.

• The Importance of Live Data in WiFi Research: Investigating the different choices for research data sources with an emphasis on encouraging live network data collection for future WiFi research.

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

Optimal Sleep-Wake Scheduling for Quickest Intrusion Detection using wireless sensor Networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

A Dataset for Evaluating Intrusion Detection Systems in IEEE 802.11 Wireless Networks

Internet access by wireless networks has grown considerably in recent years. However, these networks are vulnerable to security problems, especially those related to denial of service attacks. Intrusion Detection Systems(IDS)are widely used to improve network security, but comparison among the several existing approaches is not a trivial task. This paper proposes building a datasetfor evaluating IDS in wireless environments. The data were captured in a real, operating network. We conducted tests using traditional IDS and achieved great results, which showed the effectiveness of our proposed approach.

Agent Based Intrusion Detection and Response System for Wireless LANs

Wireless LAN technology, despite the numerous advantages it has over competing technologies, has not seen widespread deployment. A primary reason for markets not adopting this technology is its failure to provide adequate security. Data that is sent over wireless links can be compromised with utmost ease. In this project, we propose a distributed agent based intrusion detection and response system for wireless LANs that can detect unauthorized wireless elements like access points, wireless clients that are in promiscuous mode etc. The system reacts to intrusions by either notifying the concerned personnel, in case of rogue access points and promiscuous nodes, or by blocking unauthorized users from accessing the network resources.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Efficient clustering approach for intrusion detection in adhoc networks

Mobile ad-hoc networks (MANETs) are temporary wireless networks useful in emergency rescue services, battlefields operations, mobile conferencing and a variety of other useful applications. Due to dynamic nature and lack of centralized monitoring points, these networks are highly vulnerable to attacks. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. We take benefit of the clustering concept in MANETs for the effective communication between nodes, where each cluster involves a number of member nodes and is managed by a cluster-head. It can be taken as an advantage in these battery and memory constrained networks for the purpose of intrusion detection, by separating tasks for the head and member nodes, at the same time providing opportunity for launching collaborative detection approach. The clustering schemes are generally used for the routing purposes to enhance the route efficiency. However, the effect of change of a cluster tends to change the route; thus degrades the performance. This paper presents a low overhead clustering algorithm for the benefit of detecting intrusion rather than efficient routing. It also discusses the intrusion detection techniques with the help of this simplified clustering scheme.

The effect of probe interval estimation on attack detection performance of a WLAN independent intrusion detection system

A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

Distributed Hybrid Agent Based Intrusion Detection and Real Time Response System

Wireless LANs are growing rapidly and security has always been a concern. We have implemented a hybrid system, which will not only detect active attacks like identity theft causing denial of service attacks, but will also detect the usage of access point discovery tools. The system responds in real time by sending out an alert to the network administrator.