Optimised Realistic Test Input Generation Using Web Services

Abstract. We introduce a multi-objective formulation of service-oriented testing, focusing on the balance between service price and reliability. We experimented with NSGA2 for this problem, investigating the effect on performance and quality of composition size, topology and the number of services discovered. For topologies small enough for exhaustive search we found that NSGA2 finds a pareto front very near (the fronts are a Euclidean distance of ∼ 0.00024 price-reliability points apart) the true pareto front. Regarding performance, we find that composition size has the strongest effect, with smaller topologies consuming more machine time; a curious effect we believe is due to the influence of crowding dis-tance. Regarding result quality, our results reveal that size and topology have more effect on the front found than the number of service choices discovered. As expected the cost-reliability relationship (logarithmic, lin-ear, exponential) is replicated in the front discovered when correlation is high, but as the price-reliability correlation decreases, we find fewer solutions on the front and the front becomes less smooth.

Towards Rapid Generation and Visualisation of Large 3D Urban Landscapes for Mobile Device Navigation

In this paper a procedural 3D modelling solution for mobile devices is presented based on scripting algorithms allowing for both the automatic and also semi-automatic creation of photorealistic quality virtual urban content. The combination of aerial images, GIS data, 2D ground maps and terrestrial photographs as input data coupled with a user-friendly customized interface permits the automatic and interactive generation of large-scale, accurate, georeferenced and fully-textured 3D virtual city content, content that can be specially optimized for use with mobile devices but also with navigational tasks in mind. Furthermore, a user-centred mobile virtual reality (VR) visualisation and interaction tool operating on PDAs (Personal Digital Assistants) for pedestrian navigation is also discussed. Via this engine, the import and display of various navigational file formats (2D and 3D) is supported, including a comprehensive front-end user-friendly graphical user interface providing immersive virtual 3D navigation

Reinforcement learning for efficient network penetration testing

Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way

Visual communication in urban planning and urban design

This report documents the current status of visual communication in urban design and planning. Visual communication is examined through discussion of standalone and network media, specifically concentrating on visualisation on the World Wide Web(WWW).Firstly, we examine the use of Solid and Geometric Modelling for visualising urban planning and urban design. This report documents and compares examples of the use of Virtual Reality Modelling Language (VRML) and proprietary WWW based Virtual Reality modelling software. Examples include the modelling of Bath and Glasgow using both VRML 1.0 and 2.0. A review is carried out on the use of Virtual Worldsand their role in visualising urban form within multi-user environments. The use of Virtual Worlds is developed into a case study of the possibilities and limitations of Virtual Internet Design Arenas (ViDAs), an initiative undertaken at the Centre for Advanced Spatial Analysis, University College London. The use of Virtual Worlds and their development towards ViDAs is seen as one of the most important developments in visual communication for urban planning and urban design since the development plan.Secondly, photorealistic media in the process of communicating plans is examined.The process of creating photorealistic media is documented, examples of the Virtual Streetscape and Wired Whitehall Virtual Urban Interface System are provided. The conclusion is drawn that although the use of photo-realistic media on the WWW provides a way to visually communicate planning information, its use is limited. The merging of photorealistic media and solid geometric modelling is reviewed in the creation of Augmented Reality. Augmented Reality is seen to provide an important step forward in the ability to quickly and easily visualise urban planning and urban design information.Thirdly, the role of visual communication of planning data through GIS is examined interms of desktop, three dimensional and Internet based GIS systems. The evolution to Internet GIS is seen as a critical component in the development of virtual cities which will allow urban planners and urban designers to visualise and model the complexity of the built environment in networked virtual reality.Finally a viewpoint is put forward of the Virtual City, linking Internet GIS with photorealistic multi-user Virtual Worlds. At present there are constraints on how far virtual cities can be developed, but a view is provided on how these networked virtual worlds are developing to aid visual communication in urban planning and urban design

Crisis Event Extraction Service (CREES) - Automatic Detection and Classification of Crisis-related Content on Social Media

Social media posts tend to provide valuable reports during crises. However, this information can be hidden in large amounts of unrelated documents. Providing tools that automatically identify relevant posts, event types (e.g., hurricane, floods, etc.) and information categories (e.g., reports on affected individuals, donations and volunteering, etc.) in social media posts is vital for their efficient handling and consumption. We introduce the Crisis Event Extraction Service (CREES), an open-source web API that automatically classifies posts during crisis situations. The API provides annotations for crisis-related documents, event types and information categories through an easily deployable and accessible web API that can be integrated into multiple platform and tools. The annotation service is backed by Convolutional Neural Networks (CNNs) and validated against traditional machine learning models. Results show that the CNN-based API results can be relied upon when dealing with specific crises with the benefits associated with the usage word embeddings

Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm

Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved in the model integration process, discuss modelling and software development approaches, and present preliminary results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant reaction and transport in bed-sediments