ABSTRACT Variants of malware and exploits are emerging globally at an ever‐increasing rate. There is a need to automate their detection by observing their footprints over network streams, but signature‐based intrusion detection systems alone cannot cope with the dynamic nature of modern security threats. In this paper, we approach intrusion detection as a classification problem and describe a system using exemplar‐based learning to correctly classify known classes of malware and to detect, learn and classify unknown malicious streams into classes. Copyright © 2013 John Wiley & Sons, Ltd.

Subjective assessment for measuring the Quality of Experience may require time-consuming and often expensive methods, and yet, quantitative and accurate user scores are desired. In order to obtain valid correlation between analytical model and user scores, assessment based on networking perspectives and human perception is required. In this study, we have utilized the orthogonal arrays using the Taguchi approach to construct the experiment to characterize the application as well as network performance metrics in our QoE assessment model for web-based systems.

Misuse-based intrusion detection systems alone cannot cope with the dynamic nature of the security threats faced today by organizations globally. Variants of malware and exploits are emerging on the global canvas at an ever-increasing rate. There is a need to automate their detection by observing their malicious footprints over network streams. In this paper we evaluate a proposed technique to measure the relative similarity or level of maliciousness between different categories of malicious network streams captured by honeynets. This is measured by quantifying areas of analogous information or entropy between incoming network streams and reference malicious samples. Machine learning methods are used to quickly cluster similar groups of streams from the datasets. This technique is then evaluated using a large dataset and the correctness of the classifier is verified by using `area under the receiver operating characteristic curves'(ROC AUC) measures across various string metric-based classifiers.

The use of passive optical networks (PONs) enables access rates of multi-Gbit/sec bandwidth and provision of quality of service for high definition multimedia services. In this paper, we consider and analyse a generic multi-priority dynamic bandwidth allocation (DBA) algorithm for TDM PONs serving multimedia traffic in an upstream link. PON traffic is served strictly according to its priority. We consider this DBA algorithm using two approaches: (i) the algorithm assigns a fixed service quantum to each priority service and (ii) different service quanta are assigned to different priority services. The mean message delay is evaluated using a multiqueue processor sharing (MPS) model and an MPS with Heterogeneous Traffic (MPS-HT)model for the two approaches respectively. The MPS model is a classical processor sharing model limited by the critical assumption that there is egalitarian service sharing among all users, which is inefficient for multimedia applications in PONs. We extend the MPS model to a general MPS-HT model that enables the analysis of message delay performance in the case where the service quanta may be different for different services.

Worldwide interoperability for microwave access (WiMAX) is based on the IEEE 802.16 Standard with mobility support from the 802.16e amendment and it enables convergence of mobile and fixed broadband wireless networks covering metropolitan and rural areas. WiMAX traffic management aims at providing efficient delivery of multimedia applications with a range of QoS requirements. Focussing on the point-to-multipoint mode, we propose a priority-based fair scheduling algorithm for subscriber stations to serve a mixture of uplink traffic from different scheduling services and provide an analytical model for evaluating user-perceived delay performance under this scheduling scheme. The model is supported and validated by a simulation study. We present numerical results to illustrate the effect of traffic load and other design parameters on WiMAX message delay.

Push-to-Talk (PTT) is a new mobile service which enables fast-access two-way communication between two or more users. This paper provides an approximate evaluation model for PTT delay performance using the General Packet Radio Service (GPRS) over Global System for Mobile Communications (GSM) networks and taking account of GSM and GPRS traffic loading. Cases with and without provision of strict priority for PTT traffic over GPRS data are considered. Our PTT/GPRS/GSM model is based on the following three modelling assumptions: (1) a quasistationary assumption on the behaviour of GPRS under GSM voice loading, (2) a M/G/1 processor sharing (PS) queueing model to analyse PTT packet queueing delay performance, and (3) independence between retransmission traffic and original traffic. The model is validated by simulation. We present numerical and simulation mean delay results to illustrate the effect of traffic load and various design parameters on PTT packet delay.

Conventional space-time codes can provide a significant improvement in system performance only if the signal paths are spatially uncorrelated, a condition that is hardly met in practice. In this paper, we mitigate this condition by combining a technique of eigenbeamforming, based on the channel correlation matrix, with orthogonal space-time block codes (O-STBC) at the transmitter side of the link. No feedback information from the receiver (the mobile station) is utilized in the proposed structure. Simulation results using 4-ary PSK signaling showed that this idea outperforms existing techniques in both uncorrelated and correlated channels in terms of bit-error rate and symbol-error rate.