IEEE 802.11 i Security and Vulnerabilities

Despite using a variety of comprehensive preventive security measures, the Robust Secure Networks (RSNs) remain vulnerable to a number of attacks. Failure of preventive measures to address all RSN vulnerabilities dictates the need for enhancing the performance of Wireless Intrusion Detection Systems (WIDSs) to detect all attacks on RSNs with less false positive and false negative rates

MedLAN: Compact mobile computing system for wireless information access in emergency hospital wards

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.As the need for faster, safer and more efficient healthcare delivery increases, medical consultants seek new ways of implementing a high quality telemedical system, using innovative technology. Until today, teleconsultation (the most common application of Telemedicine) was performed by transferring the patient from the Accidents and Emergency ward, to a specially equipped room, or by moving large and heavy machinery to the place where the patient resided. Both these solutions were unpractical, uneconomical and potentially dangerous. At the same time wireless networks became increasingly useful in point-of-care areas such as hospitals, because of their ease of use, low cost of installation and increased flexibility. This thesis presents an integrated system called MedLAN dedicated for use inside the A&E hospital wards. Its purpose is to wirelessly support high-quality live video, audio, high-resolution still images and networks support from anywhere there is WLAN coverage. It is capable of transmitting all of the above to a consultant residing either inside or outside the hospital, or even to an external place, thorough the use of the Internet. To implement that, it makes use of the existing IEEE 802.11b wireless technology. Initially, this thesis demonstrates that for specific scenarios (such as when using WLANs), DICOM specifications should be adjusted to accommodate for the reduced WLAN bandwidth. Near lossless compression has been used to send still images through the WLANs and the results have been evaluated by a number of consultants to decide whether they retain their diagnostic value. The thesis further suggests improvements on the existing 802.11b protocol. In particular, as the typical hospital environment suffers from heavy RF reflections, it suggests that an alternative method of modulation (OFDM) can be embedded in the 802.11b hardware to reduce the multipath effect, increase the throughput and thus the video quality sent by the MedLAN system. Finally, realising that the trust between a patient and a doctor is fundamental this thesis proposes a series of simple actions aiming at securing the MedLAN system. Additionally, a concrete security system is suggested, that encapsulates the existing WEP security protocol, over IPSec

Improving Dependability of Networks with Penalty and Revocation Mechanisms

Both malicious and non-malicious faults can dismantle computer networks. Thus, mitigating faults at various layers is essential in ensuring efficient and fair network resource utilization. In this thesis we take a step in this direction and study several ways to deal with faults by means of penalties and revocation mechanisms in networks that are lacking a centralized coordination point, either because of their scale or design. Compromised nodes can pose a serious threat to infrastructure, end-hosts and services. Such malicious elements can undermine the availability and fairness of networked systems. To deal with such nodes, we design and analyze protocols enabling their removal from the network in a fast and a secure way. We design these protocols for two different environments. In the former setting, we assume that there are multiple, but independent trusted points in the network which coordinate other nodes in the network. In the latter, we assume that all nodes play equal roles in the network and thus need to cooperate to carry out common functionality. We analyze these solutions and discuss possible deployment scenarios. Next we turn our attention to wireless edge networks. In this context, some nodes, without being malicious, can still behave in an unfair manner. To deal with the situation, we propose several self-penalty mechanisms. We implement the proposed protocols employing a commodity hardware and conduct experiments in real-world environments. The analysis of data collected in several measurement rounds revealed improvements in terms of higher fairness and throughput. We corroborate the results with simulations and an analytic model. And finally, we discuss how to measure fairness in dynamic settings, where nodes can have heterogeneous resource demands

Empirical Techniques To Detect Rogue Wireless Devices

Media Access Control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. We proposed a solution to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the Received Signal Strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a Wireless Local Area Network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16%, and 88.38% accuracy when the attacker is 8–13 m, 4–8 m, and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as Random Forests. We also proposed an anomaly detection solution to deal with situations where it is impossible to cover the whole intended area. The solution is totally passive and unsupervised (using unlabeled data points) to build the profile of the legitimate device. It only requires the training of one location which is the location of the legitimate device (unlike the misuse detection solution that train and simulate the existing of the attacker in every possible spot in the network diameter). The solution was tested in the same test-bed and yield about 79% overall accuracy. We build a misuseWireless Local Area Network Intrusion Detection System (WIDS) and discover some important fields in WLAN MAC-layer frame to differentiate the attackers from the legitimate devices. We tested several machine learning algorithms and found some promising ones to improve the accuracy and computation time on a public dataset. The best performing algorithms that we found are Extra Trees, Random Forests, and Bagging. We then used a majority voting technique to vote on these algorithms. Bagging classifier and our customized voting technique have good results (about 96.25 % and 96.32 %respectively) when tested on all the features. We also used a data mining technique based on Extra Trees ensemble method to find the most important features on AWID public dataset. After selecting the most 20 important features, Extra Trees and our voting technique are the best performing classifiers in term of accuracy (96.31 % and 96.32 % respectively)

A Wireless ECG Monitoring System for Healthcare

With aging of population, there has been a significant increase in the number of patients suffering from cardiovascular diseases. This results in an increased cost of healthcare associated with hospitalization, treatment and monitoring. In this paper, an architectural framework of a system that utilizes mobile technologies to enable continuous, wireless, electrocardiogram (ECG) monitoring of patients anytime anywhere is presented. The intelligent agents residing in the system detect any anomalous ECG readings and trigger an alarm that would be sent to the healthcare center in case of an emergency. The proposed system would not only provide a better quality of life to the patients by giving them the independence to move around freely in addition to continuous monitoring of heart but will also save healthcare costs associated with prolonged hospitalization of cardiac patients

PROVIDING REFERENCE CLIENT PERSPECTIVE FOR ENHANCED RADIO FREQUENCY AND ASSURANCE FUNCTION

Techniques are described through which a sensor can provide a client Radio Frequency (RF) perspective to a wireless infrastructure. This enables establishing ultimate close-loop telemetry data for root cause analysis on Wi-Fi® problems through an assurance engine. Exchange methods and enhanced measurement reports provide a client perspective of the ever-changing RF conditions autonomously or on-demand basis to the wireless infrastructure