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.

Fast searching algorithm for candidate satellite-node set in NLMG

The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.

Enhancing an Incremental Clustering Algorithm for Web Page Collections

With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

Дизайнът на взаимодействията, масовата комуникация и предизвикателствата на споделеното експертно знание (Interaction Design, Mass Communication And the Challenge of Distributed Expertise)

This paper considers some of the implications of the rise of design as a master-metaphor of the information age. It compares the terms 'interaction design' and 'mass communication', suggesting that both can be seen as a contradiction in terms, inappropriately preserving an industrial-age division between producers and consumers. With the shift from mass media to interactive media, semiotic and political power seems to be shifting too - from media producers to designers. This paper argues that it is important for the new discipline of 'interactive design' not to fall into habits of thought inherited from the 'mass' industrial era. Instead it argues for the significance, for designers and producers alike, of what I call 'distributed expertise' -including social network markets, a DIY-culture, user-led innovation, consumer co-created content, and the use of Web 2.0 affordances for social, scientific and creative purposes as well as for entertainment. It considers the importance of the growth of 'distributed expertise' as part of a new paradigm in the growth of knowledge, which has 'evolved' through a number of phases, from 'abstraction' to 'representation', to 'productivity'. In the context of technologically mediated popular participation in the growth of knowledge and social relationships, the paper argues that design and media-production professions need to cross rather than to maintain the gap between experts and everyone else, enabling all the agents in the system to navigate the shift into the paradigm of mass productivity.

TraSe algorithm : automatic evolutionary morphing of electronic dance music

The TraSe (Transform-Select) algorithm has been developed to investigate the morphing of electronic music through automatically applying a series of deterministic compositional transformations to the source, guided towards a target by similarity metrics. This is in contrast to other morphing techniques such as interpolation or parameters or probabilistic variation. TraSe allows control over stylistic elements of the music through user-defined weighting of numerous compositional transformations. The formal evaluation of TraSe was mostly qualitative and occurred through nine participants completing an online questionnaire. The music generated by TraSe was generally felt to be less coherent than a human composed benchmark but in some cases judged as more creative.

Elliptic curve algorithm integration in the secure shell transport layer

This document describes algorithms based on Elliptic Cryptography (ECC) for use within the Secure Shell (SSH) transport protocol. In particular, it specifies Elliptic Curve Diffie-Hellman (ECDH) key agreement, Elliptic Curve Menezes-Qu-Vanstone (ECMQV) key agreement, and Elliptic Curve Digital Signature Algorithm (ECDSA) for use in the SSH Transport Layer protocol.

Population Monte Carlo Algorithm in High Dimensions

The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

QoS-based web service composition accommodating inter-service dependencies using minimal-conflict , hill-climbing repair genetic algorithm

In the field of semantic grid, QoS-based Web service composition is an important problem. In semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the composition consider not only QoS properties of Web services, but also inter service dependencies and conflicts which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address the Web service composition optimization problem in the presence of domain constraints and inter service dependencies and conflicts. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

Optimal allocation and sizing of DGs in distribution networks

In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined optimally. The objective is to minimize the loss and to improve the reliability. The constraints are the bus voltage, feeder current and the reactive power flowing back to the source side. The placement and size of DGs are optimized using a combination of Discrete Particle Swarm Optimization (DPSO) and Genetic Algorithm (GA). This increases the diversity of the optimizing variables in DPSO not to be stuck in the local minima. To evaluate the proposed algorithm, the semi-urban 37-bus distribution system connected at bus 2 of the Roy Billinton Test System (RBTS), which is located at the secondary side of a 33/11 kV distribution substation, is used. The results finally illustrate the efficiency of the proposed method.

Droop control of converter interfaced micro sources in rural distributed generation

This paper proposes new droop control methods for load sharing in a rural area with distributed generation. Highly resistive lines, typical of rural low voltage networks, always create a big challenge for conventional droop control. To overcome the conflict between higher feedback gain for better power sharing and system stability in angle droop, two control methods have been proposed. The first method considers no communication among the distributed generators (DGs) and regulates the converter output voltage and angle ensuring proper sharing of load in a system having strong coupling between real and reactive power due to high line resistance. The second method, based on a smattering of communication, modifies the reference output volt-age angle of the DGs depending on the active and reactive power flow in the lines connected to point of common coupling (PCC). It is shown that with the second proposed control method, an economical and minimum communication system can achieve significant improvement in load sharing. The difference in error margin between proposed control schemes and a more costly high bandwidth communication system is small and the later may not be justified considering the increase in cost. The proposed control shows stable operation of the system for a range of operating conditions while ensuring satisfactory load sharing.